yuntian-deng/ak-paper-selection-deberta
Text Classification • 0.4B • Updated • 4 • 5
arxiv_id stringlengths 10 10 | published stringlengths 20 20 | titles stringlengths 9 243 | authors sequencelengths 1 389 | abstract stringlengths 96 3.09k | categories sequencelengths 1 10 | selected bool 2
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|---|---|---|---|---|---|---|
2305.03264 | 2023-05-05T03:37:25Z | Robust Face Morphing Attack Detection Using Fusion of Multiple Features
and Classification Techniques | [
"Jag Mohan Singh Sushma Venkatesh Raghavendra Ramachandra"
] | Face Recognition System (FRS) are shown to be vulnerable to morphed images of
newborns. Detecting morphing attacks stemming from face images of newborn is
important to avoid unwanted consequences, both for security and society. In
this paper, we present a new reference-based/Differential Morphing Attack
Detection (MAD)... | [
"cs.CV"
] | false |
2305.03277 | 2023-05-05T04:28:48Z | FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofing | [
"Ajian Liu",
"Zichang Tan",
"Zitong Yu",
"Chenxu Zhao",
"Jun Wan",
"Yanyan Liang",
"Zhen Lei",
"Du Zhang",
"Stan Z. Li",
"Guodong Guo"
] | The availability of handy multi-modal (i.e., RGB-D) sensors has brought about
a surge of face anti-spoofing research. However, the current multi-modal face
presentation attack detection (PAD) has two defects: (1) The framework based on
multi-modal fusion requires providing modalities consistent with the training
input,... | [
"cs.CV"
] | false |
2305.03302 | 2023-05-05T06:10:15Z | High-Fidelity 3D Face Generation from Natural Language Descriptions | [
"Menghua Wu",
"Hao Zhu",
"Linjia Huang",
"Yiyu Zhuang",
"Yuanxun Lu",
"Xun Cao"
] | Synthesizing high-quality 3D face models from natural language descriptions
is very valuable for many applications, including avatar creation, virtual
reality, and telepresence. However, little research ever tapped into this task.
We argue the major obstacle lies in 1) the lack of high-quality 3D face data
with descrip... | [
"cs.CV"
] | false |
2305.03327 | 2023-05-05T07:15:49Z | FlowText: Synthesizing Realistic Scene Text Video with Optical Flow
Estimation | [
"Yuzhong Zhao",
"Weijia Wu",
"Zhuang Li",
"Jiahong Li",
"Weiqiang Wang"
] | Current video text spotting methods can achieve preferable performance,
powered with sufficient labeled training data. However, labeling data manually
is time-consuming and labor-intensive. To overcome this, using low-cost
synthetic data is a promising alternative. This paper introduces a novel video
text synthesis tec... | [
"cs.CV"
] | false |
2305.03347 | 2023-05-05T08:00:14Z | A Large Cross-Modal Video Retrieval Dataset with Reading Comprehension | [
"Weijia Wu",
"Yuzhong Zhao",
"Zhuang Li",
"Jiahong Li",
"Hong Zhou",
"Mike Zheng Shou",
"Xiang Bai"
] | Most existing cross-modal language-to-video retrieval (VR) research focuses
on single-modal input from video, i.e., visual representation, while the text
is omnipresent in human environments and frequently critical to understand
video. To study how to retrieve video with both modal inputs, i.e., visual and
text semanti... | [
"cs.CV"
] | false |
2305.03351 | 2023-05-05T08:11:31Z | Leaf Cultivar Identification via Prototype-enhanced Learning | [
"Yiyi Zhang",
"Zhiwen Ying",
"Ying Zheng",
"Cuiling Wu",
"Nannan Li",
"Jun Wang",
"Xianzhong Feng",
"Xiaogang Xu"
] | Plant leaf identification is crucial for biodiversity protection and
conservation and has gradually attracted the attention of academia in recent
years. Due to the high similarity among different varieties, leaf cultivar
recognition is also considered to be an ultra-fine-grained visual
classification (UFGVC) task, whic... | [
"cs.CV"
] | false |
2305.03393 | 2023-05-05T09:38:47Z | Optimized Table Tokenization for Table Structure Recognition | [
"Maksym Lysak",
"Ahmed Nassar",
"Nikolaos Livathinos",
"Christoph Auer",
"Peter Staar"
] | Extracting tables from documents is a crucial task in any document conversion
pipeline. Recently, transformer-based models have demonstrated that
table-structure can be recognized with impressive accuracy using
Image-to-Markup-Sequence (Im2Seq) approaches. Taking only the image of a table,
such models predict a sequenc... | [
"cs.CV"
] | false |
2305.03425 | 2023-05-05T10:46:05Z | GAANet: Ghost Auto Anchor Network for Detecting Varying Size Drones in
Dark | [
"Misha Urooj Khan",
"Maham Misbah",
"Zeeshan Kaleem",
"Yansha Deng",
"Abbas Jamalipour"
] | The usage of drones has tremendously increased in different sectors spanning
from military to industrial applications. Despite all the benefits they offer,
their misuse can lead to mishaps, and tackling them becomes more challenging
particularly at night due to their small size and low visibility conditions. To
overcom... | [
"cs.CV"
] | false |
2305.03487 | 2023-05-05T12:57:04Z | HD2Reg: Hierarchical Descriptors and Detectors for Point Cloud
Registration | [
"Canhui Tang",
"Yiheng Li",
"Shaoyi Du",
"Guofa Wang",
"Zhiqiang Tian"
] | Feature Descriptors and Detectors are two main components of feature-based
point cloud registration. However, little attention has been drawn to the
explicit representation of local and global semantics in the learning of
descriptors and detectors. In this paper, we present a framework that
explicitly extracts dual-lev... | [
"cs.CV"
] | false |
2305.03595 | 2023-05-05T15:00:14Z | HSCNet++: Hierarchical Scene Coordinate Classification and Regression
for Visual Localization with Transformer | [
"Shuzhe Wang",
"Zakaria Laskar",
"Iaroslav Melekhov",
"Xiaotian Li",
"Yi Zhao",
"Giorgos Tolias",
"Juho Kannala"
] | Visual localization is critical to many applications in computer vision and
robotics. To address single-image RGB localization, state-of-the-art
feature-based methods match local descriptors between a query image and a
pre-built 3D model. Recently, deep neural networks have been exploited to
regress the mapping between... | [
"cs.CV"
] | false |
2305.03640 | 2023-05-05T15:56:46Z | Asynchronous Events-based Panoptic Segmentation using Graph Mixer Neural
Network | [
"Sanket Kachole",
"Yusra Alkendi",
"Fariborz Baghaei Naeini",
"Dimitrios Makris",
"Yahya Zweiri"
] | In the context of robotic grasping, object segmentation encounters several
difficulties when faced with dynamic conditions such as real-time operation,
occlusion, low lighting, motion blur, and object size variability. In response
to these challenges, we propose the Graph Mixer Neural Network that includes a
novel coll... | [
"cs.CV"
] | false |
2305.03226 | 2023-05-05T01:03:37Z | Sign-Coded Exposure Sensing for Noise-Robust High-Speed Imaging | [
"R. Wes Baldwin",
"Vijayan Asari",
"Keigo Hirakawa"
] | We present a novel Fourier camera, an in-hardware optical compression of
high-speed frames employing pixel-level sign-coded exposure where pixel
intensities temporally modulated as positive and negative exposure are combined
to yield Hadamard coefficients. The orthogonality of Walsh functions ensures
that the noise is ... | [
"eess.IV",
"cs.CV"
] | false |
2305.03252 | 2023-05-05T02:43:16Z | HeteroEdge: Addressing Asymmetry in Heterogeneous Collaborative
Autonomous Systems | [
"Mohammad Saeid Anwar",
"Emon Dey",
"Maloy Kumar Devnath",
"Indrajeet Ghosh",
"Naima Khan",
"Jade Freeman",
"Timothy Gregory",
"Niranjan Suri",
"Kasthuri Jayaraja",
"Sreenivasan Ramasamy Ramamurthy",
"Nirmalya Roy"
] | Gathering knowledge about surroundings and generating situational awareness
for IoT devices is of utmost importance for systems developed for smart urban
and uncontested environments. For example, a large-area surveillance system is
typically equipped with multi-modal sensors such as cameras and LIDARs and is
required ... | [
"cs.DC",
"cs.CV"
] | false |
2305.03289 | 2023-05-05T05:39:12Z | BadSAM: Exploring Security Vulnerabilities of SAM via Backdoor Attacks | [
"Zihan Guan",
"Mengxuan Hu",
"Zhongliang Zhou",
"Jielu Zhang",
"Sheng Li",
"Ninghao Liu"
] | Recently, the Segment Anything Model (SAM) has gained significant attention
as an image segmentation foundation model due to its strong performance on
various downstream tasks. However, it has been found that SAM does not always
perform satisfactorily when faced with challenging downstream tasks. This has
led downstrea... | [
"cs.CV",
"cs.AI"
] | false |
2305.03343 | 2023-05-05T07:53:13Z | LOGO-Former: Local-Global Spatio-Temporal Transformer for Dynamic Facial
Expression Recognition | [
"Fuyan Ma",
"Bin Sun",
"Shutao Li"
] | Previous methods for dynamic facial expression recognition (DFER) in the wild
are mainly based on Convolutional Neural Networks (CNNs), whose local
operations ignore the long-range dependencies in videos. Transformer-based
methods for DFER can achieve better performances but result in higher FLOPs and
computational cos... | [
"cs.CV",
"cs.MM"
] | false |
2305.03352 | 2023-05-05T08:13:53Z | Contrastive Learning for Low-light Raw Denoising | [
"Taoyong Cui",
"Yuhan Dong"
] | Image/video denoising in low-light scenes is an extremely challenging problem
due to limited photon count and high noise. In this paper, we propose a novel
approach with contrastive learning to address this issue. Inspired by the
success of contrastive learning used in some high-level computer vision tasks,
we bring in... | [
"cs.CV",
"cs.AI"
] | false |
2305.03378 | 2023-05-05T09:16:06Z | Towards Effective Collaborative Learning in Long-Tailed Recognition | [
"Zhengzhuo Xu",
"Zenghao Chai",
"Chengyin Xu",
"Chun Yuan",
"Haiqin Yang"
] | Real-world data usually suffers from severe class imbalance and long-tailed
distributions, where minority classes are significantly underrepresented
compared to the majority ones. Recent research prefers to utilize multi-expert
architectures to mitigate the model uncertainty on the minority, where
collaborative learnin... | [
"cs.CV",
"cs.LG"
] | false |
2305.03383 | 2023-05-05T09:28:22Z | WWFedCBMIR: World-Wide Federated Content-Based Medical Image Retrieval | [
"Zahra Tabatabaei",
"Yuandou Wang",
"Adrián Colomer",
"Javier Oliver Moll",
"Zhiming Zhao",
"Valery Naranjo"
] | The paper proposes a Federated Content-Based Medical Image Retrieval
(FedCBMIR) platform that utilizes Federated Learning (FL) to address the
challenges of acquiring a diverse medical data set for training CBMIR models.
CBMIR assists pathologists in diagnosing breast cancer more rapidly by
identifying similar medical i... | [
"eess.IV",
"cs.CV"
] | false |
2305.03387 | 2023-05-05T09:33:34Z | AsConvSR: Fast and Lightweight Super-Resolution Network with Assembled
Convolutions | [
"Jiaming Guo",
"Xueyi Zou",
"Yuyi Chen",
"Yi Liu",
"Jia Hao",
"Jianzhuang Liu",
"Youliang Yan"
] | In recent years, videos and images in 720p (HD), 1080p (FHD) and 4K (UHD)
resolution have become more popular for display devices such as TVs, mobile
phones and VR. However, these high resolution images cannot achieve the
expected visual effect due to the limitation of the internet bandwidth, and
bring a great challeng... | [
"eess.IV",
"cs.CV"
] | false |
2305.03416 | 2023-05-05T10:29:29Z | Evolution under Length Constraints for CNN Architecture design | [
"Ousmane Youme",
"Jean Marie Dembele",
"Eugene C. Ezin",
"Christophe Cambier"
] | In recent years, the CNN architectures designed by evolution algorithms have
proven to be competitive with handcrafted architectures designed by experts.
However, these algorithms need a lot of computational power, which is beyond
the capabilities of most researchers and engineers. To overcome this problem,
we propose ... | [
"cs.CV",
"cs.NE"
] | false |
2305.03500 | 2023-05-05T13:20:41Z | High-Level Context Representation for Emotion Recognition in Images | [
"Willams de Lima Costa",
"Estefania Talavera Martinez",
"Lucas Silva Figueiredo",
"Veronica Teichrieb"
] | Emotion recognition is the task of classifying perceived emotions in people.
Previous works have utilized various nonverbal cues to extract features from
images and correlate them to emotions. Of these cues, situational context is
particularly crucial in emotion perception since it can directly influence the
emotion of... | [
"cs.CV",
"cs.HC"
] | false |
2305.03601 | 2023-05-05T15:05:07Z | Human Attention-Guided Explainable Artificial Intelligence for Computer
Vision Models | [
"Guoyang Liu",
"Jindi Zhang",
"Antoni B. Chan",
"Janet H. Hsiao"
] | We examined whether embedding human attention knowledge into saliency-based
explainable AI (XAI) methods for computer vision models could enhance their
plausibility and faithfulness. We first developed new gradient-based XAI
methods for object detection models to generate object-specific explanations by
extending the c... | [
"cs.CV",
"cs.AI",
"68T45",
"I.2.0; I.4.0"
] | false |
2305.03706 | 2023-05-05T17:38:00Z | Fine-Grained Product Classification on Leaflet Advertisements | [
"Daniel Ladwig",
"Bianca Lamm",
"Janis Keuper"
] | In this paper, we describe a first publicly available fine-grained product
recognition dataset based on leaflet images. Using advertisement leaflets,
collected over several years from different European retailers, we provide a
total of 41.6k manually annotated product images in 832 classes. Further, we
investigate thre... | [
"cs.CV",
"cs.LG"
] | false |
2305.03726 | 2023-05-05T17:59:46Z | Otter: A Multi-Modal Model with In-Context Instruction Tuning | [
"Bo Li",
"Yuanhan Zhang",
"Liangyu Chen",
"Jinghao Wang",
"Jingkang Yang",
"Ziwei Liu"
] | Large language models (LLMs) have demonstrated significant universal
capabilities as few/zero-shot learners in various tasks due to their
pre-training on vast amounts of text data, as exemplified by GPT-3, which
boosted to InstrctGPT and ChatGPT, effectively following natural language
instructions to accomplish real-wo... | [
"cs.CV",
"cs.CL"
] | true |
2305.03810 | 2023-05-05T19:26:06Z | Distilled Mid-Fusion Transformer Networks for Multi-Modal Human Activity
Recognition | [
"Jingcheng Li",
"Lina Yao",
"Binghao Li",
"Claude Sammut"
] | Human Activity Recognition is an important task in many human-computer
collaborative scenarios, whilst having various practical applications. Although
uni-modal approaches have been extensively studied, they suffer from data
quality and require modality-specific feature engineering, thus not being
robust and effective ... | [
"cs.HC",
"cs.CV"
] | false |
2305.03844 | 2023-05-05T20:47:42Z | Physics-based network fine-tuning for robust quantitative susceptibility
mapping from high-pass filtered phase | [
"Jinwei Zhang",
"Alexey Dimov",
"Chao Li",
"Hang Zhang",
"Thanh D. Nguyen",
"Pascal Spincemaille",
"Yi Wang"
] | Purpose: To improve the generalization ability of convolutional neural
network (CNN) based prediction of quantitative susceptibility mapping (QSM)
from high-pass filtered phase (HPFP) image. Methods: The proposed network
addresses two common generalization issues that arise when using a pre-trained
network to predict Q... | [
"eess.IV",
"cs.CV"
] | false |
2305.13261 | 2023-05-05T07:44:23Z | A Review of Benchmarks for Visual Defect Detection in the Manufacturing
Industry | [
"Philippe Carvalho",
"Alexandre Durupt",
"Yves Grandvalet"
] | The field of industrial defect detection using machine learning and deep
learning is a subject of active research. Datasets, also called benchmarks, are
used to compare and assess research results. There is a number of datasets in
industrial visual inspection, of varying quality. Thus, it is a difficult task
to determi... | [
"cs.CV",
"cs.LG"
] | false |
2305.03273 | 2023-05-05T04:11:00Z | Semantic Segmentation using Vision Transformers: A survey | [
"Hans Thisanke",
"Chamli Deshan",
"Kavindu Chamith",
"Sachith Seneviratne",
"Rajith Vidanaarachchi",
"Damayanthi Herath"
] | Semantic segmentation has a broad range of applications in a variety of
domains including land coverage analysis, autonomous driving, and medical image
analysis. Convolutional neural networks (CNN) and Vision Transformers (ViTs)
provide the architecture models for semantic segmentation. Even though ViTs
have proven suc... | [
"cs.CV",
"cs.AI",
"cs.LG"
] | false |
2305.03330 | 2023-05-05T07:22:20Z | Solution existence, uniqueness, and stability of discrete basis
sinograms in multispectral CT | [
"Yu Gao",
"Xiaochuan Pan",
"Chong Chen"
] | This work investigates conditions for quantitative image reconstruction in
multispectral computed tomography (MSCT), which remains a topic of active
research. In MSCT, one seeks to obtain from data the spatial distribution of
linear attenuation coefficient, referred to as a virtual monochromatic image
(VMI), at a given... | [
"math.NA",
"cs.CV",
"cs.NA",
"physics.med-ph",
"65R32, 94A08, 65F22, 65J22, 65D18"
] | false |
2305.03350 | 2023-05-05T08:11:00Z | Reconstructing Training Data from Multiclass Neural Networks | [
"Gon Buzaglo",
"Niv Haim",
"Gilad Yehudai",
"Gal Vardi",
"Michal Irani"
] | Reconstructing samples from the training set of trained neural networks is a
major privacy concern. Haim et al. (2022) recently showed that it is possible
to reconstruct training samples from neural network binary classifiers, based
on theoretical results about the implicit bias of gradient methods. In this
work, we pr... | [
"cs.LG",
"cs.CR",
"cs.CV"
] | false |
2305.03413 | 2023-05-05T10:26:50Z | Domain-agnostic segmentation of thalamic nuclei from joint structural
and diffusion MRI | [
"Henry F. J. Tregidgo",
"Sonja Soskic",
"Mark D. Olchanyi",
"Juri Althonayan",
"Benjamin Billot",
"Chiara Maffei",
"Polina Golland",
"Anastasia Yendiki",
"Daniel C. Alexander",
"Martina Bocchetta",
"Jonathan D. Rohrer",
"Juan Eugenio Iglesias"
] | The human thalamus is a highly connected subcortical grey-matter structure
within the brain. It comprises dozens of nuclei with different function and
connectivity, which are affected differently by disease. For this reason, there
is growing interest in studying the thalamic nuclei in vivo with MRI. Tools are
available... | [
"eess.IV",
"cs.CV",
"cs.LG",
"q-bio.QM"
] | false |
2305.03572 | 2023-05-05T14:29:24Z | Learn how to Prune Pixels for Multi-view Neural Image-based Synthesis | [
"Marta Milovanović",
"Enzo Tartaglione",
"Marco Cagnazzo",
"Félix Henry"
] | Image-based rendering techniques stand at the core of an immersive experience
for the user, as they generate novel views given a set of multiple input
images. Since they have shown good performance in terms of objective and
subjective quality, the research community devotes great effort to their
improvement. However, t... | [
"cs.MM",
"cs.AI",
"cs.CV"
] | false |
2305.03691 | 2023-05-05T17:09:01Z | Mining bias-target Alignment from Voronoi Cells | [
"Rémi Nahon",
"Van-Tam Nguyen",
"Enzo Tartaglione"
] | Despite significant research efforts, deep neural networks are still
vulnerable to biases: this raises concerns about their fairness and limits
their generalization. In this paper, we propose a bias-agnostic approach to
mitigate the impact of bias in deep neural networks. Unlike traditional
debiasing approaches, we rel... | [
"cs.LG",
"cs.AI",
"cs.CV",
"cs.CY"
] | false |
2305.03724 | 2023-05-05T17:58:45Z | DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV
Perception | [
"Yunze Man",
"Liang-Yan Gui",
"Yu-Xiong Wang"
] | Closing the domain gap between training and deployment and incorporating
multiple sensor modalities are two challenging yet critical topics for
self-driving. Existing work only focuses on single one of the above topics,
overlooking the simultaneous domain and modality shift which pervasively exists
in real-world scenar... | [
"cs.CV",
"cs.AI",
"cs.RO"
] | false |
2305.03253 | 2023-05-05T02:46:22Z | VicunaNER: Zero/Few-shot Named Entity Recognition using Vicuna | [
"Bin Ji"
] | Large Language Models (LLMs, e.g., ChatGPT) have shown impressive zero- and
few-shot capabilities in Named Entity Recognition (NER). However, these models
can only be accessed via online APIs, which may cause data leak and
non-reproducible problems. In this paper, we propose VicunaNER, a zero/few-shot
NER framework bas... | [
"cs.CL"
] | false |
2305.03256 | 2023-05-05T03:02:41Z | Stylized Data-to-Text Generation: A Case Study in the E-Commerce Domain | [
"Liqiang Jing",
"Xuemeng Song",
"Xuming Lin",
"Zhongzhou Zhao",
"Wei Zhou",
"Liqiang Nie"
] | Existing data-to-text generation efforts mainly focus on generating a
coherent text from non-linguistic input data, such as tables and
attribute-value pairs, but overlook that different application scenarios may
require texts of different styles. Inspired by this, we define a new task,
namely stylized data-to-text gene... | [
"cs.CL"
] | false |
2305.03268 | 2023-05-05T03:49:14Z | Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework | [
"Ruochen Zhao",
"Xingxuan Li",
"Shafiq Joty",
"Chengwei Qin",
"Lidong Bing"
] | As large language models (LLMs) have become the norm in NLP, demonstrating
good performance in generation and reasoning tasks, one of its most fatal
disadvantages is the lack of factual correctness. Generating unfactual texts
not only leads to lower performances but also degrades the trust and validity
of their applica... | [
"cs.CL"
] | false |
2305.03296 | 2023-05-05T05:50:26Z | TransESC: Smoothing Emotional Support Conversation via Turn-Level State
Transition | [
"Weixiang Zhao",
"Yanyan Zhao",
"Shilong Wang",
"Bing Qin"
] | Emotion Support Conversation (ESC) is an emerging and challenging task with
the goal of reducing the emotional distress of people. Previous attempts fail
to maintain smooth transitions between utterances in ESC because they ignore to
grasp the fine-grained transition information at each dialogue turn. To solve
this pro... | [
"cs.CL"
] | false |
2305.03300 | 2023-05-05T06:05:45Z | LLM-RM at SemEval-2023 Task 2: Multilingual Complex NER using
XLM-RoBERTa | [
"Rahul Mehta",
"Vasudeva Varma"
] | Named Entity Recognition(NER) is a task of recognizing entities at a token
level in a sentence. This paper focuses on solving NER tasks in a multilingual
setting for complex named entities. Our team, LLM-RM participated in the
recently organized SemEval 2023 task, Task 2: MultiCoNER II,Multilingual
Complex Named Entity... | [
"cs.CL"
] | false |
2305.03314 | 2023-05-05T06:43:56Z | Block the Label and Noise: An N-Gram Masked Speller for Chinese Spell
Checking | [
"Haiyun Yang"
] | Recently, Chinese Spell Checking(CSC), a task to detect erroneous characters
in a sentence and correct them, has attracted extensive interest because of its
wide applications in various NLP tasks. Most of the existing methods have
utilized BERT to extract semantic information for CSC task. However, these
methods direct... | [
"cs.CL"
] | false |
2305.03407 | 2023-05-05T10:17:22Z | Online Gesture Recognition using Transformer and Natural Language
Processing | [
"G. C. M. Silvestre",
"F. Balado",
"O. Akinremi",
"M. Ramo"
] | The Transformer architecture is shown to provide a powerful machine
transduction framework for online handwritten gestures corresponding to glyph
strokes of natural language sentences. The attention mechanism is successfully
used to create latent representations of an end-to-end encoder-decoder model,
solving multi-lev... | [
"cs.CL"
] | false |
2305.03429 | 2023-05-05T11:03:03Z | Simulating H.P. Lovecraft horror literature with the ChatGPT large
language model | [
"Eduardo C. Garrido-Merchán",
"José Luis Arroyo-Barrigüete",
"Roberto Gozalo-Brizuela"
] | In this paper, we present a novel approach to simulating H.P. Lovecraft's
horror literature using the ChatGPT large language model, specifically the
GPT-4 architecture. Our study aims to generate text that emulates Lovecraft's
unique writing style and themes, while also examining the effectiveness of
prompt engineering... | [
"cs.CL"
] | false |
2305.03461 | 2023-05-05T12:06:01Z | Interactive Acquisition of Fine-grained Visual Concepts by Exploiting
Semantics of Generic Characterizations in Discourse | [
"Jonghyuk Park",
"Alex Lascarides",
"Subramanian Ramamoorthy"
] | Interactive Task Learning (ITL) concerns learning about unforeseen domain
concepts via natural interactions with human users. The learner faces a number
of significant constraints: learning should be online, incremental and
few-shot, as it is expected to perform tangible belief updates right after
novel words denoting ... | [
"cs.CL"
] | false |
2305.03715 | 2023-05-05T17:55:49Z | Large Language Models in Ambulatory Devices for Home Health Diagnostics:
A case study of Sickle Cell Anemia Management | [
"Oluwatosin Ogundare",
"Subuola Sofolahan"
] | This study investigates the potential of an ambulatory device that
incorporates Large Language Models (LLMs) in cadence with other specialized ML
models to assess anemia severity in sickle cell patients in real time. The
device would rely on sensor data that measures angiogenic material levels to
assess anemia severity... | [
"cs.CL"
] | false |
2305.03788 | 2023-05-05T18:39:07Z | Harnessing the Power of BERT in the Turkish Clinical Domain: Pretraining
Approaches for Limited Data Scenarios | [
"Hazal Türkmen",
"Oğuz Dikenelli",
"Cenk Eraslan",
"Mehmet Cem Çallı",
"Süha Süreyya Özbek"
] | In recent years, major advancements in natural language processing (NLP) have
been driven by the emergence of large language models (LLMs), which have
significantly revolutionized research and development within the field.
Building upon this progress, our study delves into the effects of various
pre-training methodolog... | [
"cs.CL"
] | false |
2305.03796 | 2023-05-05T18:54:40Z | Transformer Working Memory Enables Regular Language Reasoning and
Natural Language Length Extrapolation | [
"Ta-Chung Chi",
"Ting-Han Fan",
"Alexander I. Rudnicky",
"Peter J. Ramadge"
] | Unlike recurrent models, conventional wisdom has it that Transformers cannot
perfectly model regular languages. Inspired by the notion of working memory, we
propose a new Transformer variant named RegularGPT. With its novel combination
of Weight-Sharing, Adaptive-Depth, and Sliding-Dilated-Attention, RegularGPT
constru... | [
"cs.CL"
] | false |
2305.03819 | 2023-05-05T19:47:41Z | Adapting Transformer Language Models for Predictive Typing in
Brain-Computer Interfaces | [
"Shijia Liu",
"David A. Smith"
] | Brain-computer interfaces (BCI) are an important mode of alternative and
augmentative communication for many people. Unlike keyboards, many BCI systems
do not display even the 26 letters of English at one time, let alone all the
symbols in more complex systems. Using language models to make character-level
predictions,... | [
"cs.CL"
] | false |
2305.03851 | 2023-05-05T21:20:02Z | Large Language Models in Sport Science & Medicine: Opportunities, Risks
and Considerations | [
"Mark Connor",
"Michael O'Neill"
] | This paper explores the potential opportunities, risks, and challenges
associated with the use of large language models (LLMs) in sports science and
medicine. LLMs are large neural networks with transformer style architectures
trained on vast amounts of textual data, and typically refined with human
feedback. LLMs can ... | [
"cs.CL",
"I.2.7"
] | false |
2305.03873 | 2023-05-05T23:22:16Z | Train Global, Tailor Local: Minimalist Multilingual Translation into
Endangered Languages | [
"Zhong Zhou",
"Jan Niehues",
"Alex Waibel"
] | In many humanitarian scenarios, translation into severely low resource
languages often does not require a universal translation engine, but a
dedicated text-specific translation engine. For example, healthcare records,
hygienic procedures, government communication, emergency procedures and
religious texts are all limit... | [
"cs.CL"
] | false |
2305.03262 | 2023-05-05T03:28:49Z | Rescue Conversations from Dead-ends: Efficient Exploration for
Task-oriented Dialogue Policy Optimization | [
"Yangyang Zhao",
"Zhenyu Wang",
"Mehdi Dastani",
"Shihan Wang"
] | Training a dialogue policy using deep reinforcement learning requires a lot
of exploration of the environment. The amount of wasted invalid exploration
makes their learning inefficient. In this paper, we find and define an
important reason for the invalid exploration: dead-ends. When a conversation
enters a dead-end st... | [
"cs.HC",
"cs.CL"
] | false |
2305.03287 | 2023-05-05T05:32:50Z | Low-Resource Multi-Granularity Academic Function Recognition Based on
Multiple Prompt Knowledge | [
"Jiawei Liu",
"Zi Xiong",
"Yi Jiang",
"Yongqiang Ma",
"Wei Lu",
"Yong Huang",
"Qikai Cheng"
] | Fine-tuning pre-trained language models (PLMs), e.g., SciBERT, generally
requires large numbers of annotated data to achieve state-of-the-art
performance on a range of NLP tasks in the scientific domain. However,
obtaining the fine-tune data for scientific NLP task is still challenging and
expensive. Inspired by recent... | [
"cs.CL",
"cs.AI"
] | false |
2305.03299 | 2023-05-05T06:03:54Z | Open Information Extraction via Chunks | [
"Kuicai Dong",
"Aixin Sun",
"Jung-Jae Kim",
"Xiaoli Li"
] | Open Information Extraction (OIE) aims to extract relational tuples from
open-domain sentences. Existing OIE systems split a sentence into tokens and
recognize token spans as tuple relations and arguments. We instead propose
Sentence as Chunk sequence (SaC) and recognize chunk spans as tuple relations
and arguments. We... | [
"cs.CL",
"cs.AI"
] | false |
2305.03458 | 2023-05-05T12:00:58Z | Multi-View Graph Representation Learning for Answering Hybrid Numerical
Reasoning Question | [
"Yifan Wei",
"Fangyu Lei",
"Yuanzhe Zhang",
"Jun Zhao",
"Kang Liu"
] | Hybrid question answering (HybridQA) over the financial report contains both
textual and tabular data, and requires the model to select the appropriate
evidence for the numerical reasoning task. Existing methods based on
encoder-decoder framework employ a expression tree-based decoder to solve
numerical reasoning probl... | [
"cs.CL",
"cs.AI"
] | false |
2305.03573 | 2023-05-05T14:30:20Z | In-context Learning as Maintaining Coherency: A Study of On-the-fly
Machine Translation Using Large Language Models | [
"Suzanna Sia",
"Kevin Duh"
] | The phenomena of in-context learning has typically been thought of as
"learning from examples". In this work which focuses on Machine Translation, we
present a perspective of in-context learning as the desired generation task
maintaining coherency with its context, i.e., the prompt examples. We first
investigate random... | [
"cs.CL",
"cs.AI"
] | false |
2305.03661 | 2023-05-05T16:28:44Z | Predicting COVID-19 and pneumonia complications from admission texts | [
"Dmitriy Umerenkov",
"Oleg Cherkashin",
"Alexander Nesterov",
"Victor Gombolevskiy",
"Irina Demko",
"Alexander Yalunin",
"Vladimir Kokh"
] | In this paper we present a novel approach to risk assessment for patients
hospitalized with pneumonia or COVID-19 based on their admission reports. We
applied a Longformer neural network to admission reports and other textual data
available shortly after admission to compute risk scores for the patients. We
used patien... | [
"cs.CL",
"cs.AI"
] | false |
2305.03793 | 2023-05-05T18:47:18Z | Towards Zero-Shot Frame Semantic Parsing with Task Agnostic Ontologies
and Simple Labels | [
"Danilo Ribeiro",
"Omid Abdar",
"Jack Goetz",
"Mike Ross",
"Annie Dong",
"Kenneth Forbus",
"Ahmed Mohamed"
] | Frame semantic parsing is an important component of task-oriented dialogue
systems. Current models rely on a significant amount training data to
successfully identify the intent and slots in the user's input utterance. This
creates a significant barrier for adding new domains to virtual assistant
capabilities, as creat... | [
"cs.CL",
"cs.LG",
"I.2.7; I.2.6"
] | false |
2305.03845 | 2023-05-05T20:49:40Z | CLaC at SemEval-2023 Task 2: Comparing Span-Prediction and
Sequence-Labeling approaches for NER | [
"Harsh Verma",
"Sabine Bergler"
] | This paper summarizes the CLaC submission for the MultiCoNER 2 task which
concerns the recognition of complex, fine-grained named entities. We compare
two popular approaches for NER, namely Sequence Labeling and Span Prediction.
We find that our best Span Prediction system performs slightly better than our
best Sequenc... | [
"cs.CL",
"cs.AI"
] | false |
2305.06157 | 2023-05-05T08:59:03Z | Implications of Multi-Word Expressions on English to Bharti Braille
Machine Translation | [
"Nisheeth Joshi",
"Pragya Katyayan"
] | In this paper, we have shown the improvement of English to Bharti Braille
machine translation system. We have shown how we can improve a baseline NMT
model by adding some linguistic knowledge to it. This was done for five
language pairs where English sentences were translated into five Indian
languages and then subsequ... | [
"cs.CL",
"cs.AI"
] | false |
2305.06475 | 2023-05-05T09:21:13Z | A Model for Translation of Text from Indian Languages to Bharti Braille
Characters | [
"Nisheeth Joshi",
"Pragya Katyayan"
] | People who are visually impaired face a lot of difficulties while studying.
One of the major causes to this is lack of available text in Bharti Braille
script. In this paper, we have suggested a scheme to convert text in major
Indian languages into Bharti Braille. The system uses a hybrid approach where
at first the te... | [
"cs.CL",
"cs.AI"
] | false |
2305.03336 | 2023-05-05T07:40:41Z | QCRI at SemEval-2023 Task 3: News Genre, Framing and Persuasion
Techniques Detection using Multilingual Models | [
"Maram Hasanain",
"Ahmed Oumar El-Shangiti",
"Rabindra Nath Nandi",
"Preslav Nakov",
"Firoj Alam"
] | Misinformation spreading in mainstream and social media has been misleading
users in different ways. Manual detection and verification efforts by
journalists and fact-checkers can no longer cope with the great scale and quick
spread of misleading information. This motivated research and industry efforts
to develop syst... | [
"cs.CL",
"cs.AI",
"cs.CY",
"68T50",
"F.2.2; I.2.7"
] | false |
2305.03356 | 2023-05-05T08:20:09Z | From Parse-Execute to Parse-Execute-Refine: Improving Semantic Parser
for Complex Question Answering over Knowledge Base | [
"Wangzhen Guo",
"Linyin Luo",
"Hanjiang Lai",
"Jian Yin"
] | Parsing questions into executable logical forms has showed impressive results
for knowledge-base question answering (KBQA). However, complex KBQA is a more
challenging task that requires to perform complex multi-step reasoning.
Recently, a new semantic parser called KoPL has been proposed to explicitly
model the reason... | [
"cs.CL",
"cs.AI",
"cs.LG"
] | false |
2305.03369 | 2023-05-05T08:53:57Z | The MuSe 2023 Multimodal Sentiment Analysis Challenge: Mimicked
Emotions, Cross-Cultural Humour, and Personalisation | [
"Lukas Christ",
"Shahin Amiriparian",
"Alice Baird",
"Alexander Kathan",
"Niklas Müller",
"Steffen Klug",
"Chris Gagne",
"Panagiotis Tzirakis",
"Eva-Maria Meßner",
"Andreas König",
"Alan Cowen",
"Erik Cambria",
"Björn W. Schuller"
] | The MuSe 2023 is a set of shared tasks addressing three different
contemporary multimodal affect and sentiment analysis problems: In the Mimicked
Emotions Sub-Challenge (MuSe-Mimic), participants predict three continuous
emotion targets. This sub-challenge utilises the Hume-Vidmimic dataset
comprising of user-generated... | [
"cs.LG",
"cs.AI",
"cs.CL",
"cs.MM"
] | false |
2305.03660 | 2023-05-05T16:28:03Z | Retrieval Augmented Chest X-Ray Report Generation using OpenAI GPT
models | [
"Mercy Ranjit",
"Gopinath Ganapathy",
"Ranjit Manuel",
"Tanuja Ganu"
] | We propose Retrieval Augmented Generation (RAG) as an approach for automated
radiology report writing that leverages multimodally aligned embeddings from a
contrastively pretrained vision language model for retrieval of relevant
candidate radiology text for an input radiology image and a general domain
generative model... | [
"cs.CL",
"cs.AI",
"cs.IR",
"cs.LG",
"I.2; J.3; H.3"
] | false |
2305.03742 | 2023-05-05T07:24:46Z | Improved Logical Reasoning of Language Models via Differentiable
Symbolic Programming | [
"Hanlin Zhang",
"Jiani Huang",
"Ziyang Li",
"Mayur Naik",
"Eric Xing"
] | Pre-trained large language models (LMs) struggle to perform logical reasoning
reliably despite advances in scale and compositionality. In this work, we
tackle this challenge through the lens of symbolic programming. We propose
DSR-LM, a Differentiable Symbolic Reasoning framework where pre-trained LMs
govern the percep... | [
"cs.AI",
"cs.CL",
"cs.LG"
] | false |
2305.04927 | 2023-05-05T08:25:07Z | Detecting and Reasoning of Deleted Tweets before they are Posted | [
"Hamdy Mubarak",
"Samir Abdaljalil",
"Azza Nassar",
"Firoj Alam"
] | Social media platforms empower us in several ways, from information
dissemination to consumption. While these platforms are useful in promoting
citizen journalism, public awareness etc., they have misuse potentials.
Malicious users use them to disseminate hate-speech, offensive content, rumor
etc. to gain social and po... | [
"cs.CL",
"cs.AI",
"cs.CY",
"68T50",
"F.2.2; I.2.7"
] | false |
2305.03648 | 2023-05-05T16:10:31Z | On the Effectiveness of Equivariant Regularization for Robust Online
Continual Learning | [
"Lorenzo Bonicelli",
"Matteo Boschini",
"Emanuele Frascaroli",
"Angelo Porrello",
"Matteo Pennisi",
"Giovanni Bellitto",
"Simone Palazzo",
"Concetto Spampinato",
"Simone Calderara"
] | Humans can learn incrementally, whereas neural networks forget previously
acquired information catastrophically. Continual Learning (CL) approaches seek
to bridge this gap by facilitating the transfer of knowledge to both previous
tasks (backward transfer) and future ones (forward transfer) during training.
Recent re... | [
"cs.LG"
] | false |
2305.03740 | 2023-05-05T02:21:08Z | Judge Me in Context: A Telematics-Based Driving Risk Prediction
Framework in Presence of Weak Risk Labels | [
"Sobhan Moosavi",
"Rajiv Ramnath"
] | Driving risk prediction has been a topic of much research over the past few
decades to minimize driving risk and increase safety. The use of demographic
information in risk prediction is a traditional solution with applications in
insurance planning, however, it is difficult to capture true driving behavior
via such co... | [
"cs.LG"
] | false |
2305.03784 | 2023-05-05T18:34:49Z | Neural Exploitation and Exploration of Contextual Bandits | [
"Yikun Ban",
"Yuchen Yan",
"Arindam Banerjee",
"Jingrui He"
] | In this paper, we study utilizing neural networks for the exploitation and
exploration of contextual multi-armed bandits. Contextual multi-armed bandits
have been studied for decades with various applications. To solve the
exploitation-exploration trade-off in bandits, there are three main techniques:
epsilon-greedy, T... | [
"cs.LG"
] | false |
2305.03863 | 2023-05-05T22:25:42Z | Software-based Automatic Differentiation is Flawed | [
"Daniel Johnson",
"Trevor Maxfield",
"Yongxu Jin",
"Ronald Fedkiw"
] | Various software efforts embrace the idea that object oriented programming
enables a convenient implementation of the chain rule, facilitating so-called
automatic differentiation via backpropagation. Such frameworks have no
mechanism for simplifying the expressions (obtained via the chain rule) before
evaluating them. ... | [
"cs.LG"
] | false |
2305.03178 | 2023-05-05T12:16:01Z | Contrastive Learning for Sleep Staging based on Inter Subject
Correlation | [
"Tongxu Zhang",
"Bei Wang"
] | In recent years, multitudes of researches have applied deep learning to
automatic sleep stage classification. Whereas actually, these works have paid
less attention to the issue of cross-subject in sleep staging. At the same
time, emerging neuroscience theories on inter-subject correlations can provide
new insights for... | [
"eess.SP",
"cs.LG"
] | false |
2305.03224 | 2023-05-05T01:02:08Z | Carbon Price Forecasting with Quantile Regression and Feature Selection | [
"Tianqi Pang",
"Kehui Tan",
"Chenyou Fan"
] | Carbon futures has recently emerged as a novel financial asset in the trading
markets such as the European Union and China. Monitoring the trend of the
carbon price has become critical for both national policy-making as well as
industrial manufacturing planning. However, various geopolitical, social, and
economic facto... | [
"cs.LG",
"q-fin.ST"
] | false |
2305.03249 | 2023-05-05T02:27:27Z | PMP: Learning to Physically Interact with Environments using Part-wise
Motion Priors | [
"Jinseok Bae",
"Jungdam Won",
"Donggeun Lim",
"Cheol-Hui Min",
"Young Min Kim"
] | We present a method to animate a character incorporating multiple part-wise
motion priors (PMP). While previous works allow creating realistic articulated
motions from reference data, the range of motion is largely limited by the
available samples. Especially for the interaction-rich scenarios, it is
impractical to att... | [
"cs.GR",
"cs.LG"
] | false |
2305.03263 | 2023-05-05T03:29:34Z | Bayesian Reinforcement Learning with Limited Cognitive Load | [
"Dilip Arumugam",
"Mark K. Ho",
"Noah D. Goodman",
"Benjamin Van Roy"
] | All biological and artificial agents must learn and make decisions given
limits on their ability to process information. As such, a general theory of
adaptive behavior should be able to account for the complex interactions
between an agent's learning history, decisions, and capacity constraints.
Recent work in computer... | [
"cs.LG",
"cs.AI"
] | false |
2305.03414 | 2023-05-05T10:27:23Z | Adaptive Graph Convolutional Subspace Clustering | [
"Lai Wei",
"Zhengwei Chen",
"Jun Yin",
"Changming Zhu",
"Rigui Zhou",
"Jin Liu"
] | Spectral-type subspace clustering algorithms have shown excellent performance
in many subspace clustering applications. The existing spectral-type subspace
clustering algorithms either focus on designing constraints for the
reconstruction coefficient matrix or feature extraction methods for finding
latent features of o... | [
"cs.LG",
"cs.AI"
] | false |
2305.03452 | 2023-05-05T11:56:26Z | A technical note on bilinear layers for interpretability | [
"Lee Sharkey"
] | The ability of neural networks to represent more features than neurons makes
interpreting them challenging. This phenomenon, known as superposition, has
spurred efforts to find architectures that are more interpretable than standard
multilayer perceptrons (MLPs) with elementwise activation functions. In this
note, I ex... | [
"cs.LG",
"cs.NE"
] | false |
2305.03555 | 2023-05-05T14:04:52Z | Contrastive Graph Clustering in Curvature Spaces | [
"Li Sun",
"Feiyang Wang",
"Junda Ye",
"Hao Peng",
"Philip S. Yu"
] | Graph clustering is a longstanding research topic, and has achieved
remarkable success with the deep learning methods in recent years.
Nevertheless, we observe that several important issues largely remain open. On
the one hand, graph clustering from the geometric perspective is appealing but
has rarely been touched bef... | [
"cs.LG",
"stat.ML"
] | false |
2305.03574 | 2023-05-05T14:30:29Z | Scope Restriction for Scalable Real-Time Railway Rescheduling: An
Exploratory Study | [
"Erik Nygren",
"Christian Eichenberger",
"Emma Frejinger"
] | With the aim to stimulate future research, we describe an exploratory study
of a railway rescheduling problem. A widely used approach in practice and state
of the art is to decompose these complex problems by geographical scope.
Instead, we propose defining a core problem that restricts a rescheduling
problem in respon... | [
"math.OC",
"cs.LG"
] | false |
2305.03623 | 2023-05-05T15:33:39Z | Optimizing Hyperparameters with Conformal Quantile Regression | [
"David Salinas",
"Jacek Golebiowski",
"Aaron Klein",
"Matthias Seeger",
"Cedric Archambeau"
] | Many state-of-the-art hyperparameter optimization (HPO) algorithms rely on
model-based optimizers that learn surrogate models of the target function to
guide the search. Gaussian processes are the de facto surrogate model due to
their ability to capture uncertainty but they make strong assumptions about the
observation... | [
"cs.LG",
"stat.ML"
] | false |
2305.03710 | 2023-05-05T17:50:50Z | Data Encoding For Healthcare Data Democratisation and Information
Leakage Prevention | [
"Anshul Thakur",
"Tingting Zhu",
"Vinayak Abrol",
"Jacob Armstrong",
"Yujiang Wang",
"David A. Clifton"
] | The lack of data democratization and information leakage from trained models
hinder the development and acceptance of robust deep learning-based healthcare
solutions. This paper argues that irreversible data encoding can provide an
effective solution to achieve data democratization without violating the
privacy constra... | [
"cs.LG",
"cs.CR"
] | false |
2305.03741 | 2023-05-05T07:03:24Z | AmGCL: Feature Imputation of Attribute Missing Graph via Self-supervised
Contrastive Learning | [
"Xiaochuan Zhang",
"Mengran Li",
"Ye Wang",
"Haojun Fei"
] | Attribute graphs are ubiquitous in multimedia applications, and graph
representation learning (GRL) has been successful in analyzing attribute graph
data. However, incomplete graph data and missing node attributes can have a
negative impact on media knowledge discovery. Existing methods for handling
attribute missing g... | [
"cs.LG",
"cs.AI"
] | false |
2305.03743 | 2023-05-05T10:04:03Z | Learning Sentinel-2 reflectance dynamics for data-driven assimilation
and forecasting | [
"Anthony Frion",
"Lucas Drumetz",
"Guillaume Tochon",
"Mauro Dalla Mura",
"Abdeldjalil Aïssa El Bey"
] | Over the last few years, massive amounts of satellite multispectral and
hyperspectral images covering the Earth's surface have been made publicly
available for scientific purpose, for example through the European Copernicus
project. Simultaneously, the development of self-supervised learning (SSL)
methods has sparked g... | [
"eess.IV",
"cs.LG"
] | false |
2305.03814 | 2023-05-05T19:42:11Z | Deep Labeling of fMRI Brain Networks | [
"Ammar Ahmed Pallikonda Latheef",
"Sejal Ghate",
"Zhipeng Hui",
"Alberto Santamaria-Pang",
"Ivan Tarapov",
"Haris I Sair",
"Craig K Jones"
] | Resting State Networks (RSNs) of the brain extracted from Resting State
functional Magnetic Resonance Imaging (RS-fMRI) are used in the pre-surgical
planning to guide the neurosurgeon. This is difficult, though, as expert
knowledge is required to label each of the RSNs. There is a lack of efficient
and standardized met... | [
"cs.LG",
"q-bio.NC"
] | false |
2305.03855 | 2023-05-05T21:43:00Z | Robust A-Optimal Experimental Design for Bayesian Inverse Problems | [
"Ahmed Attia",
"Sven Leyffer",
"Todd Munson"
] | Optimal design of experiments for Bayesian inverse problems has recently
gained wide popularity and attracted much attention, especially in the
computational science and Bayesian inversion communities. An optimal design
maximizes a predefined utility function that is formulated in terms of the
elements of an inverse pr... | [
"math.OC",
"cs.LG",
"62K05, 35Q62, 62F15, 35R30, 35Q93, 65C60, 93E35"
] | false |
2305.04889 | 2023-05-05T14:34:20Z | Improving Real-Time Bidding in Online Advertising Using Markov Decision
Processes and Machine Learning Techniques | [
"Parikshit Sharma"
] | Real-time bidding has emerged as an effective online advertising technique.
With real-time bidding, advertisers can position ads per impression, enabling
them to optimise ad campaigns by targeting specific audiences in real-time.
This paper proposes a novel method for real-time bidding that combines deep
learning and r... | [
"cs.IR",
"cs.LG"
] | false |
2305.05621 | 2023-05-05T16:22:17Z | Deep Learning-based Estimation for Multitarget Radar Detection | [
"Mamady Delamou",
"Ahmad Bazzi",
"Marwa Chafii",
"El Mehdi Amhoud"
] | Target detection and recognition is a very challenging task in a wireless
environment where a multitude of objects are located, whether to effectively
determine their positions or to identify them and predict their moves. In this
work, we propose a new method based on a convolutional neural network (CNN) to
estimate th... | [
"eess.SP",
"cs.LG"
] | false |
2305.03257 | 2023-05-05T03:09:33Z | Data-driven and Physics Informed Modelling of Chinese Hamster Ovary Cell
Bioreactors | [
"Tianqi Cui",
"Tom S. Bertalan",
"Nelson Ndahiro",
"Pratik Khare",
"Michael Betenbaugh",
"Costas Maranas",
"Ioannis G. Kevrekidis"
] | Fed-batch culture is an established operation mode for the production of
biologics using mammalian cell cultures. Quantitative modeling integrates both
kinetics for some key reaction steps and optimization-driven metabolic flux
allocation, using flux balance analysis; this is known to lead to certain
mathematical incon... | [
"q-bio.QM",
"cs.LG",
"math.DS"
] | false |
2305.03286 | 2023-05-05T05:02:41Z | Composite Motion Learning with Task Control | [
"Pei Xu",
"Xiumin Shang",
"Victor Zordan",
"Ioannis Karamouzas"
] | We present a deep learning method for composite and task-driven motion
control for physically simulated characters. In contrast to existing
data-driven approaches using reinforcement learning that imitate full-body
motions, we learn decoupled motions for specific body parts from multiple
reference motions simultaneousl... | [
"cs.GR",
"cs.AI",
"cs.LG"
] | true |
2305.03295 | 2023-05-05T05:50:07Z | Decentralized diffusion-based learning under non-parametric limited
prior knowledge | [
"Paweł Wachel",
"Krzysztof Kowalczyk",
"Cristian R. Rojas"
] | We study the problem of diffusion-based network learning of a nonlinear
phenomenon, $m$, from local agents' measurements collected in a noisy
environment. For a decentralized network and information spreading merely
between directly neighboring nodes, we propose a non-parametric learning
algorithm, that avoids raw data... | [
"stat.ML",
"cs.LG",
"cs.MA"
] | false |
2305.03331 | 2023-05-05T07:22:30Z | Generic and Robust Root Cause Localization for Multi-Dimensional Data in
Online Service Systems | [
"Zeyan Li",
"Junjie Chen",
"Yihao Chen",
"Chengyang Luo",
"Yiwei Zhao",
"Yongqian Sun",
"Kaixin Sui",
"Xiping Wang",
"Dapeng Liu",
"Xing Jin",
"Qi Wang",
"Dan Pei"
] | Localizing root causes for multi-dimensional data is critical to ensure
online service systems' reliability. When a fault occurs, only the measure
values within specific attribute combinations are abnormal. Such attribute
combinations are substantial clues to the underlying root causes and thus are
called root causes o... | [
"cs.SE",
"cs.LG",
"cs.PF"
] | false |
2305.03360 | 2023-05-05T08:23:56Z | A Survey on Offline Model-Based Reinforcement Learning | [
"Haoyang He"
] | Model-based approaches are becoming increasingly popular in the field of
offline reinforcement learning, with high potential in real-world applications
due to the model's capability of thoroughly utilizing the large historical
datasets available with supervised learning techniques. This paper presents a
literature revi... | [
"cs.LG",
"cs.AI",
"cs.SY",
"eess.SY",
"I.2.6; I.2.8"
] | false |
2305.03365 | 2023-05-05T08:33:28Z | Repairing Deep Neural Networks Based on Behavior Imitation | [
"Zhen Liang",
"Taoran Wu",
"Changyuan Zhao",
"Wanwei Liu",
"Bai Xue",
"Wenjing Yang",
"Ji Wang"
] | The increasing use of deep neural networks (DNNs) in safety-critical systems
has raised concerns about their potential for exhibiting ill-behaviors. While
DNN verification and testing provide post hoc conclusions regarding unexpected
behaviors, they do not prevent the erroneous behaviors from occurring. To
address this... | [
"cs.LG",
"cs.AI",
"cs.SE",
"68N99, , 68T99",
"D.2.5; I.2.5"
] | false |
2305.03395 | 2023-05-05T09:40:28Z | Sparsifying Bayesian neural networks with latent binary variables and
normalizing flows | [
"Lars Skaaret-Lund",
"Geir Storvik",
"Aliaksandr Hubin"
] | Artificial neural networks (ANNs) are powerful machine learning methods used
in many modern applications such as facial recognition, machine translation,
and cancer diagnostics. A common issue with ANNs is that they usually have
millions or billions of trainable parameters, and therefore tend to overfit to
the training... | [
"stat.ML",
"cs.LG",
"stat.CO",
"stat.ME",
"62-02, 62-09, 62F07, 62F15, 62J12, 62J05, 62J99, 62M05, 05A16,\n 60J22, 92D20, 90C27, 90C59",
"G.1.2; G.1.6; G.2.1; G.3; I.2.0; I.2.6; I.2.8; I.5.1; I.6; I.6.4"
] | false |
2305.03474 | 2023-05-05T12:36:18Z | Zoo Guide to Network Embedding | [
"Anthony Baptista",
"Rubén J. Sánchez-García",
"Anaïs Baudot",
"Ginestra Bianconi"
] | Networks have provided extremely successful models of data and complex
systems. Yet, as combinatorial objects, networks do not have in general
intrinsic coordinates and do not typically lie in an ambient space. The process
of assigning an embedding space to a network has attracted lots of interest in
the past few decad... | [
"cs.SI",
"cs.LG",
"math-ph",
"math.MP"
] | false |
2305.03547 | 2023-05-05T13:56:40Z | Over-the-Air Federated Averaging with Limited Power and Privacy Budgets | [
"Na Yan",
"Kezhi Wang",
"Cunhua Pan",
"Kok Keong Chai",
"Feng Shu",
"Jiangzhou Wang"
] | To jointly overcome the communication bottleneck and privacy leakage of
wireless federated learning (FL), this paper studies a differentially private
over-the-air federated averaging (DP-OTA-FedAvg) system with a limited sum
power budget. With DP-OTA-FedAvg, the gradients are aligned by an alignment
coefficient and agg... | [
"cs.LG",
"cs.CR",
"cs.IT",
"math.IT"
] | false |
2305.03568 | 2023-05-05T14:19:46Z | A vector quantized masked autoencoder for audiovisual speech emotion
recognition | [
"Samir Sadok",
"Simon Leglaive",
"Renaud Séguier"
] | While fully-supervised models have been shown to be effective for audiovisual
speech emotion recognition (SER), the limited availability of labeled data
remains a major challenge in the field. To address this issue, self-supervised
learning approaches, such as masked autoencoders (MAEs), have gained popularity
as poten... | [
"cs.SD",
"cs.LG",
"cs.MM",
"eess.AS"
] | false |
2305.03739 | 2023-05-05T01:54:38Z | Neural Architecture Search for Intel Movidius VPU | [
"Qian Xu",
"Victor Li",
"Crews Darren S"
] | Hardware-aware Neural Architecture Search (NAS) technologies have been
proposed to automate and speed up model design to meet both quality and
inference efficiency requirements on a given hardware. Prior arts have shown
the capability of NAS on hardware specific network design. In this whitepaper,
we further extend the... | [
"cs.NE",
"cs.AR",
"cs.LG"
] | false |
2305.03761 | 2023-05-05T18:00:09Z | Weakly-Supervised Anomaly Detection in the Milky Way | [
"Mariel Pettee",
"Sowmya Thanvantri",
"Benjamin Nachman",
"David Shih",
"Matthew R. Buckley",
"Jack H. Collins"
] | Large-scale astrophysics datasets present an opportunity for new machine
learning techniques to identify regions of interest that might otherwise be
overlooked by traditional searches. To this end, we use Classification Without
Labels (CWoLa), a weakly-supervised anomaly detection method, to identify cold
stellar strea... | [
"astro-ph.GA",
"cs.LG",
"hep-ph",
"physics.data-an"
] | false |
2305.03797 | 2023-05-05T18:55:32Z | Materials Informatics: An Algorithmic Design Rule | [
"Bhupesh Bishnoi"
] | Materials informatics, data-enabled investigation, is a "fourth paradigm" in
materials science research after the conventional empirical approach,
theoretical science, and computational research. Materials informatics has two
essential ingredients: fingerprinting materials proprieties and the theory of
statistical infe... | [
"cond-mat.mtrl-sci",
"cond-mat.stat-mech",
"cs.LG",
"37E25, 46N30, 05C85, 60G25, 62C10, 62M20, 68Q32, 93E10",
"I.2.3; J.2; G.2.2; G.3"
] | false |
2305.03804 | 2023-05-05T19:13:00Z | Equivariant Neural Networks for Spin Dynamics Simulations of Itinerant
Magnets | [
"Yu Miyazaki"
] | I present a novel equivariant neural network architecture for the large-scale
spin dynamics simulation of the Kondo lattice model. This neural network mainly
consists of tensor-product-based convolution layers and ensures two
equivariances: translations of the lattice and rotations of the spins. I
implement equivariant... | [
"cond-mat.str-el",
"cond-mat.dis-nn",
"cond-mat.mtrl-sci",
"cs.LG"
] | false |
2305.03835 | 2023-05-05T20:30:30Z | Spatiotemporal Transformer for Stock Movement Prediction | [
"Daniel Boyle",
"Jugal Kalita"
] | Financial markets are an intriguing place that offer investors the potential
to gain large profits if timed correctly. Unfortunately, the dynamic,
non-linear nature of financial markets makes it extremely hard to predict
future price movements. Within the US stock exchange, there are a countless
number of factors that ... | [
"cs.LG",
"cs.AI",
"cs.CE"
] | false |
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