Split (1)

train · 203k rows

node_id int64 0 76.9k	label int64 0 39	text stringlengths 13 124k	neighbors listlengths 0 3.32k	mask stringclasses 4 values
45,778	13	Title: Dynamic Training of Liquid State Machines Abstract: Spiking Neural Networks (SNNs) emerged as a promising solution in the field of Artificial Neural Networks (ANNs), attracting the attention of researchers due to their ability to mimic the human brain and process complex information with remarkable speed and acc...	[]	Test
45,779	2	Title: Causal models in string diagrams Abstract: The framework of causal models provides a principled approach to causal reasoning, applied today across many scientific domains. Here we present this framework in the language of string diagrams, interpreted formally using category theory. A class of string diagrams, ca...	[ 21053 ]	Train
45,780	24	Title: A Platform-Agnostic Deep Reinforcement Learning Framework for Effective Sim2Real Transfer in Autonomous Driving Abstract: Deep Reinforcement Learning (DRL) has shown remarkable success in solving complex tasks across various research fields. However, transferring DRL agents to the real world is still challenging...	[ 11019 ]	Train
45,781	16	Title: Boosting Semi-Supervised Learning by bridging high and low-confidence predictions Abstract: Pseudo-labeling is a crucial technique in semi-supervised learning (SSL), where artificial labels are generated for unlabeled data by a trained model, allowing for the simultaneous training of labeled and unlabeled data i...	[]	Test
45,782	24	Title: ProtoVAE: Prototypical Networks for Unsupervised Disentanglement Abstract: Generative modeling and self-supervised learning have in recent years made great strides towards learning from data in a completely unsupervised way. There is still however an open area of investigation into guiding a neural network to en...	[]	Validation
45,783	30	Title: Topological Interpretations of GPT-3 Abstract: This is an experiential study of investigating a consistent method for deriving the correlation between sentence vector and semantic meaning of a sentence. We first used three state-of-the-art word/sentence embedding methods including GPT-3, Word2Vec, and Sentence-B...	[ 29649 ]	Train
45,784	30	Title: Improving Cross-lingual Information Retrieval on Low-Resource Languages via Optimal Transport Distillation Abstract: Benefiting from transformer-based pre-trained language models, neural ranking models have made significant progress. More recently, the advent of multilingual pre-trained language models provides ...	[ 3593, 7954, 28982 ]	Validation
45,785	16	Title: A Satellite Imagery Dataset for Long-Term Sustainable Development in United States Cities Abstract: Cities play an important role in achieving sustainable development goals (SDGs) to promote economic growth and meet social needs. Especially satellite imagery is a potential data source for studying sustainable ur...	[]	Validation
45,786	36	Title: Online Coalition Formation under Random Arrival or Coalition Dissolution Abstract: Coalition formation considers the question of how to partition a set of $n$ agents into disjoint coalitions according to their preferences. We consider a cardinal utility model with additively separable aggregation of preferences ...	[]	Validation
45,787	4	Title: Data-Centric Machine Learning Approach for Early Ransomware Detection and Attribution Abstract: Researchers have proposed a wide range of ransomware detection and analysis schemes. However, most of these efforts have focused on older families targeting Windows 7/8 systems. Hence there is a critical need to devel...	[ 40513 ]	Train
45,788	16	Title: Defect Transfer GAN: Diverse Defect Synthesis for Data Augmentation Abstract: Data-hunger and data-imbalance are two major pitfalls in many deep learning approaches. For example, on highly optimized production lines, defective samples are hardly acquired while non-defective samples come almost for free. The defe...	[ 27414 ]	Test
45,789	16	Title: DARC: Distribution-Aware Re-Coloring Model for Generalizable Nucleus Segmentation Abstract: Nucleus segmentation is usually the first step in pathological image analysis tasks. Generalizable nucleus segmentation refers to the problem of training a segmentation model that is robust to domain gaps between the sour...	[]	Train
45,790	5	Title: Developing Distributed High-performance Computing Capabilities of an Open Science Platform for Robust Epidemic Analysis Abstract: COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among domain experts, ...	[ 43681 ]	Train
45,791	24	Title: Bridging the Gap between Chemical Reaction Pretraining and Conditional Molecule Generation with a Unified Model Abstract: Chemical reactions are the fundamental building blocks of drug design and organic chemistry research. In recent years, there has been a growing need for a large-scale deep-learning framework ...	[]	Train
45,792	30	Title: MAT: Mixed-Strategy Game of Adversarial Training in Fine-tuning Abstract: Fine-tuning large-scale pre-trained language models has been demonstrated effective for various natural language processing (NLP) tasks. Previous studies have established that incorporating adversarial training during the fine-tuning stage...	[ 34919 ]	Train
45,793	16	Title: Dense Affinity Matching for Few-Shot Segmentation Abstract: Few-Shot Segmentation (FSS) aims to segment the novel class images with a few annotated samples. In this paper, we propose a dense affinity matching (DAM) framework to exploit the support-query interaction by densely capturing both the pixel-to-pixel an...	[ 14934 ]	Validation
45,794	24	Title: Experimenting with an Evaluation Framework for Imbalanced Data Learning (EFIDL) Abstract: Introduction Data imbalance is one of the crucial issues in big data analysis with fewer labels. For example, in real-world healthcare data, spam detection labels, and financial fraud detection datasets. Many data balance m...	[]	Test
45,795	16	Title: PV-SSD: A Projection and Voxel-based Double Branch Single-Stage 3D Object Detector Abstract: LIDAR-based 3D object detection and classification is crucial for autonomous driving. However, inference in real-time from extremely sparse 3D data poses a formidable challenge. To address this issue, a common approach i...	[ 41128 ]	Test
45,796	25	Title: Adapting Meter Tracking Models to Latin American Music Abstract: Beat and downbeat tracking models have improved significantly in recent years with the introduction of deep learning methods. However, despite these improvements, several challenges remain. Particularly, the adaptation of available models to underr...	[]	Test
45,797	36	Title: Distributed Learning Dynamics for Coalitional Games Abstract: In the framework of transferable utility coalitional games, a scoring (characteristic) function determines the value of any subset/coalition of agents. Agents decide on both which coalitions to form and the allocations of the values of the formed coal...	[]	Train
45,798	16	Title: Enhancing Mobile Privacy and Security: A Face Skin Patch-Based Anti-Spoofing Approach Abstract: As Facial Recognition System(FRS) is widely applied in areas such as access control and mobile payments due to its convenience and high accuracy. The security of facial recognition is also highly regarded. The Face an...	[]	Train
45,799	16	Title: Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds Abstract: Rotational invariance is a popular inductive bias used by many fields in machine learning, such as computer vision and machine learning for quantum chemistry. Rotation-invariant machine learning methods...	[]	Train
45,800	2	Title: Proceedings Nineteenth conference on Theoretical Aspects of Rationality and Knowledge Abstract: The TARK conference (Theoretical Aspects of Rationality and Knowledge) is a conference that aims to bring together researchers from a wide variety of fields, including computer science, artificial intelligence, game t...	[]	Train
45,801	24	Title: Differentiable Bayesian Structure Learning with Acyclicity Assurance Abstract: Score-based approaches in the structure learning task are thriving because of their scalability. Continuous relaxation has been the key reason for this advancement. Despite achieving promising outcomes, most of these methods are still...	[ 24784, 28562 ]	Train
45,802	11	Title: Collision Detection for Multi-Robot Motion Planning with Efficient Quad-Tree Update and Skipping Abstract: This paper presents a novel and efficient collision checking approach called Updating and Collision Check Skipping Quad-tree (USQ) for multi-robot motion planning. USQ extends the standard quad-tree data st...	[]	Train
45,803	16	Title: Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models Abstract: A long standing goal in neuroscience has been to elucidate the functional organization of the brain. Within higher visual cortex, functional accounts have remained relatively coarse, focusing on regions of in...	[ 23285 ]	Train
45,804	6	Title: Synergi: A Mixed-Initiative System for Scholarly Synthesis and Sensemaking Abstract: Efficiently reviewing scholarly literature and synthesizing prior art are crucial for scientific progress. Yet, the growing scale of publications and the burden of knowledge make synthesis of research threads more challenging th...	[ 39594, 8141, 43949, 43410, 35580 ]	Validation
45,805	30	Title: NorQuAD: Norwegian Question Answering Dataset Abstract: In this paper we present NorQuAD: the first Norwegian question answering dataset for machine reading comprehension. The dataset consists of 4,752 manually created question-answer pairs. We here detail the data collection procedure and present statistics of ...	[ 6101 ]	Train
45,806	22	Title: Communicating Actor Automata - Modelling Erlang Processes as Communicating Machines Abstract: Brand and Zafiropulo's notion of Communicating Finite-State Machines (CFSMs) provides a succinct and powerful model of message-passing concurrency, based around channels. However, a major variant of message-passing conc...	[]	Train
45,807	16	Title: rPPG-MAE: Self-supervised Pre-training with Masked Autoencoders for Remote Physiological Measurement Abstract: Remote photoplethysmography (rPPG) is an important technique for perceiving human vital signs, which has received extensive attention. For a long time, researchers have focused on supervised methods tha...	[ 22249, 10253 ]	Test
45,808	25	Title: The DKU Post-Challenge Audio-Visual Wake Word Spotting System for the 2021 MISP Challenge: Deep Analysis Abstract: This paper further explores our previous wake word spotting system ranked 2-nd in Track 1 of the MISP Challenge 2021. First, we investigate a robust unimodal approach based on 3D and 2D convolution ...	[]	Train
45,809	28	Title: Resonant Tunneling Diode-Based THz SWIPT for Microscopic 6G IoT Devices Abstract: In this paper, we study terahertz (THz) simultaneous wireless information and power transfer (SWIPT) for future micro-scale 6G Internet-of-Things (IoT) networks. Since Schottky diodes are not efficient for THz energy harvesting (EH...	[ 1390 ]	Validation
45,810	16	Title: Exploring vision transformer layer choosing for semantic segmentation Abstract: Extensive work has demonstrated the effectiveness of Vision Transformers. The plain Vision Transformer tends to obtain multi-scale features by selecting fixed layers, or the last layer of features aiming to achieve higher performance...	[]	Train
45,811	4	Title: Adaptive Bi-Recommendation and Self-Improving Network for Heterogeneous Domain Adaptation-Assisted IoT Intrusion Detection Abstract: As Internet of Things (IoT) devices become prevalent, using intrusion detection to protect IoT from malicious intrusions is of vital importance. However, the data scarcity of IoT h...	[ 36279 ]	Test
45,812	2	Title: Old and New Benchmarks for Relative Termination of String Rewrite Systems Abstract: We provide a critical assessment of the current set of benchmarks for relative SRS termination in the Termination Problems Database (TPDB): most of the benchmarks in Waldmann_19 and ICFP_10_relative are, in fact, strictly termina...	[ 14181 ]	Test
45,813	24	Title: Deep neural networks architectures from the perspective of manifold learning Abstract: Despite significant advances in the field of deep learning in ap-plications to various areas, an explanation of the learning pro-cess of neural network models remains an important open ques-tion. The purpose of this paper is a...	[]	Validation
45,814	24	Title: AnoOnly: Semi-Supervised Anomaly Detection with the Only Loss on Anomalies Abstract: Semi-supervised anomaly detection (SSAD) methods have demonstrated their effectiveness in enhancing unsupervised anomaly detection (UAD) by leveraging few-shot but instructive abnormal instances. However, the dominance of homoge...	[ 23646 ]	Train
45,815	16	Title: Enhancing Visual Domain Adaptation with Source Preparation Abstract: Robotic Perception in diverse domains such as low-light scenarios, where new modalities like thermal imaging and specialized night-vision sensors are increasingly employed, remains a challenge. Largely, this is due to the limited availability o...	[ 32376 ]	Train
45,816	24	Title: Non-Stationary Policy Learning for Multi-Timescale Multi-Agent Reinforcement Learning Abstract: In multi-timescale multi-agent reinforcement learning (MARL), agents interact across different timescales. In general, policies for time-dependent behaviors, such as those induced by multiple timescales, are non-stati...	[]	Test
45,817	24	Title: Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties Abstract: nan	[ 43005, 41325, 22823 ]	Train
45,818	30	Title: Acquiring Frame Element Knowledge with Deep Metric Learning for Semantic Frame Induction Abstract: The semantic frame induction tasks are defined as a clustering of words into the frames that they evoke, and a clustering of their arguments according to the frame element roles that they should fill. In this paper...	[ 30283 ]	Validation
45,819	31	Title: Dataset of Natural Language Queries for E-Commerce Abstract: Shopping online is more and more frequent in our everyday life. For e-commerce search systems, understanding natural language coming through voice assistants, chatbots or from conversational search is an essential ability to understand what the user re...	[ 10197 ]	Validation
45,820	24	Title: A Closer Look at the Adversarial Robustness of Deep Equilibrium Models Abstract: Deep equilibrium models (DEQs) refrain from the traditional layer-stacking paradigm and turn to find the fixed point of a single layer. DEQs have achieved promising performance on different applications with featured memory efficien...	[ 17992, 33414 ]	Train
45,821	30	Title: LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked Abstract: Large language models (LLMs) have skyrocketed in popularity in recent years due to their ability to generate high-quality text in response to human prompting. However, these models have been shown to have the potential to generate ...	[ 37411, 31653, 14536, 17295, 10800, 41328, 4565, 43641, 43327 ]	Test
45,822	30	Title: Evaluation of ChatGPT Family of Models for Biomedical Reasoning and Classification Abstract: Recent advances in large language models (LLMs) have shown impressive ability in biomedical question-answering, but have not been adequately investigated for more specific biomedical applications. This study investigates...	[ 3624, 13224, 42908, 23759, 35824, 21880, 27161, 14620, 23421 ]	Train
45,823	13	Title: Expressivity of Spiking Neural Networks Abstract: This article studies the expressive power of spiking neural networks where information is encoded in the firing time of neurons. The implementation of spiking neural networks on neuromorphic hardware presents a promising choice for future energy-efficient AI appl...	[ 13700 ]	Validation
45,824	4	Title: Mitigating Adversarial Effects of False Data Injection Attacks in Power Grid Abstract: Deep Neural Networks have proven to be highly accurate at a variety of tasks in recent years. The benefits of Deep Neural Networks have also been embraced in power grids to detect False Data Injection Attacks (FDIA) while cond...	[]	Train
45,825	37	Title: Interactive Text-to-SQL Generation via Editable Step-by-Step Explanations Abstract: Relational databases play an important role in this Big Data era. However, it is challenging for non-experts to fully unleash the analytical power of relational databases, since they are not familiar with database languages such ...	[ 11757 ]	Train
45,826	30	Title: MacLaSa: Multi-Aspect Controllable Text Generation via Efficient Sampling from Compact Latent Space Abstract: Multi-aspect controllable text generation aims to generate fluent sentences that possess multiple desired attributes simultaneously. Traditional methods either combine many operators in the decoding stag...	[]	Train
45,827	6	Title: Social Visual Behavior Analytics for Autism Therapy of Children Based on Automated Mutual Gaze Detection Abstract: Social visual behavior, as a type of non-verbal communication, plays a central role in studying social cognitive processes in interactive and complex settings of autism therapy interventions. Howeve...	[ 37116, 35582 ]	Train
45,828	24	Title: PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation Abstract: Spatiotemporal data mining plays an important role in air quality monitoring, crowd flow modeling, and climate forecasting. However, the originally collected spatiotemporal data in real-world scenarios is usually incomplete due to ...	[ 27257, 32869, 36743 ]	Train
45,829	16	Title: ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents Abstract: Keyword spotting (KWS) in historical documents is an important tool for the initial exploration of digitized collections. Nowadays, the most efficient KWS methods are relying on machine learning techniques tha...	[]	Train
45,830	24	Title: Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond Abstract: Recent research shows that when Gradient Descent (GD) is applied to neural networks, the loss almost never decreases monotonically. Instead, the loss oscillates as gradient descent converges ...	[ 29813 ]	Test
45,831	30	Title: ASPER: Answer Set Programming Enhanced Neural Network Models for Joint Entity-Relation Extraction Abstract: A plethora of approaches have been proposed for joint entity-relation (ER) extraction. Most of these methods largely depend on a large amount of manually annotated training data. However, manual data ann...	[]	Test
45,832	16	Title: Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer Abstract: Unsupervised Domain Adaptation (UDA) can effectively address domain gap issues in real-world image Super-Resolution (SR) by accessing both the source and target data. Considering privacy policies or tran...	[ 33722, 35179 ]	Train
45,833	16	Title: Z-GMOT: Zero-shot Generic Multiple Object Tracking Abstract: Despite the significant progress made in recent years, Multi-Object Tracking (MOT) approaches still suffer from several limitations, including their reliance on prior knowledge of tracking targets, which necessitates the costly annotation of large labe...	[]	Train
45,834	24	Title: Learning the effective order of a hypergraph dynamical system Abstract: Dynamical systems on hypergraphs can display a rich set of behaviours not observable for systems with pairwise interactions. Given a distributed dynamical system with a putative hypergraph structure, an interesting question is thus how much ...	[ 23590 ]	Train
45,835	5	Title: Towards Lightweight Data Integration using Multi-workflow Provenance and Data Observability Abstract: Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Edge-to-Cloud continuum. Integrat...	[ 2728, 19377, 32891, 6544 ]	Validation
45,836	16	Title: Meta-Auxiliary Network for 3D GAN Inversion Abstract: Real-world image manipulation has achieved fantastic progress in recent years. GAN inversion, which aims to map the real image to the latent code faithfully, is the first step in this pipeline. However, existing GAN inversion methods fail to achieve high reco...	[]	Train
45,837	16	Title: Rethinking Image-based Table Recognition Using Weakly Supervised Methods Abstract: Most of the previous methods for table recognition rely on training datasets containing many richly annotated table images. Detailed table image annotation, e.g., cell or text bounding box annotation, however, is costly and often ...	[ 11432 ]	Test
45,838	30	Title: HanoiT: Enhancing Context-aware Translation via Selective Context Abstract: nan	[ 8460 ]	Train
45,839	16	Title: Hinting Pipeline and Multivariate Regression CNN for Maize Kernel Counting on the Ear Abstract: Maize is a highly nutritional cereal widely used for human and animal consumption and also as raw material by the biofuels industries. This highlights the importance of precisely quantifying the corn grain productivit...	[]	Train
45,840	4	Title: Image encryption for Offshore wind power based on 2D-LCLM and Zhou Yi Eight Trigrams Abstract: Offshore wind power is an important part of the new power system, due to the complex and changing situation at ocean, its normal operation and maintenance cannot be done without information such as images, therefore, i...	[]	Test
45,841	24	Title: HiGen: Hierarchical Graph Generative Networks Abstract: Most real-world graphs exhibit a hierarchical structure, which is often overlooked by existing graph generation methods. To address this limitation, we propose a novel graph generative network that captures the hierarchical nature of graphs and successively...	[]	Train
45,842	24	Title: On the Implicit Bias of Linear Equivariant Steerable Networks: Margin, Generalization, and Their Equivalence to Data Augmentation Abstract: We study the implicit bias of gradient flow on linear equivariant steerable networks in group-invariant binary classification. Our findings reveal that the parameterized pre...	[]	Train
45,843	2	Title: Primal logic of information Abstract: Primal logic arose in access control; it has a remarkably efficient (linear time) decision procedure for its entailment problem. But primal logic is a general logic of information. In the realm of arbitrary items of information (infons), conjunction, disjunction, and implica...	[]	Train
45,844	30	Title: A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction Abstract: Knowledge of syntax includes knowledge of rare, idiosyncratic constructions. LLMs must overcome frequency biases in order to master such constructions. In this study, I prompt GPT-3 to give accept...	[ 19720, 37100, 4558, 14606, 22643, 16441 ]	Train
45,845	28	Title: Knot Theory and Error-Correcting Codes Abstract: This paper builds a novel bridge between algebraic coding theory and mathematical knot theory, with applications in both directions. We give methods to construct error-correcting codes starting from the colorings of a knot, describing through a series of results h...	[]	Train
45,846	28	Title: Improved Gilbert-Varshamov bounds for hopping cyclic codes and optical orthogonal codes Abstract: Hopping cyclic codes (HCCs) are (non-linear) cyclic codes with the additional property that the $n$ cyclic shifts of every given codeword are all distinct, where $n$ is the code length. Constant weight binary hoppin...	[]	Test
45,847	30	Title: Can ChatGPT Assess Human Personalities? A General Evaluation Framework Abstract: Large Language Models (LLMs) especially ChatGPT have produced impressive results in various areas, but their potential human-like psychology is still largely unexplored. Existing works study the virtual personalities of LLMs but rar...	[ 17668, 23462, 31238, 45127, 6094, 36528, 45680, 26357, 35545, 12538, 7421 ]	Validation
45,848	30	Title: Exploring the Benefits of Training Expert Language Models over Instruction Tuning Abstract: Recently, Language Models (LMs) instruction-tuned on multiple tasks, also known as multitask-prompted fine-tuning (MT), have shown the capability to generalize to unseen tasks. Previous work has shown that scaling the num...	[ 13185, 7270, 37383, 5192, 39273, 6538, 43209, 12142, 3696, 14609, 16179, 2996, 10964, 34963, 44537, 7678 ]	Train
45,849	24	Title: ExcelFormer: A Neural Network Surpassing GBDTs on Tabular Data Abstract: Though deep neural networks have gained enormous successes in various fields (e.g., computer vision) with supervised learning, they have so far been still trailing after the performances of GBDTs on tabular data. Delving into this task, we ...	[ 34971, 4701, 46086 ]	Validation
45,850	30	Title: The Effectiveness of a Dynamic Loss Function in Neural Network Based Automated Essay Scoring Abstract: Neural networks and in particular the attention mechanism have brought significant advances to the field of Automated Essay Scoring. Many of these systems use a regression-based model which may be prone to unde...	[ 25455 ]	Validation
45,851	16	Title: The Stable Signature: Rooting Watermarks in Latent Diffusion Models Abstract: Generative image modeling enables a wide range of applications but raises ethical concerns about responsible deployment. This paper introduces an active strategy combining image watermarking and Latent Diffusion Models. The goal is for...	[ 14499, 6091, 29200, 2897, 14353, 19249, 19378, 26003, 11895, 34074, 37211 ]	Train
45,852	24	Title: Asymmetric matrix sensing by gradient descent with small random initialization Abstract: We study matrix sensing, which is the problem of reconstructing a low-rank matrix from a few linear measurements. It can be formulated as an overparameterized regression problem, which can be solved by factorized gradient de...	[ 33844, 3807 ]	Test
45,853	24	Title: Proportionally Representative Clustering Abstract: In recent years, there has been a surge in effort to formalize notions of fairness in machine learning. We focus on clustering -- one of the fundamental tasks in unsupervised machine learning. We propose a new axiom ``proportional representation fairness'' (PRF)...	[]	Train
45,854	4	Title: S3C2 Summit 2023-02: Industry Secure Supply Chain Summit Abstract: Recent years have shown increased cyber attacks targeting less secure elements in the software supply chain and causing fatal damage to businesses and organizations. Past well-known examples of software supply chain attacks are the SolarWinds or ...	[]	Train
45,855	10	Title: Contrastive Explanations of Multi-agent Optimization Solutions Abstract: In many real-world scenarios, agents are involved in optimization problems. Since most of these scenarios are over-constrained, optimal solutions do not always satisfy all agents. Some agents might be unhappy and ask questions of the form `...	[]	Train
45,856	4	Title: RényiTester: A Variational Approach to Testing Differential Privacy Abstract: Governments and industries have widely adopted differential privacy as a measure to protect users' sensitive data, creating the need for new implementations of differentially private algorithms. In order to properly test and audit thes...	[ 39614 ]	Test
45,857	5	Title: DFlow: Efficient Dataflow-based Invocation Workflow Execution for Function-as-a-Service Abstract: The Serverless Computing is becoming increasingly popular due to its ease of use and fine-grained billing. These features make it appealing for stateful application or serverless workflow. However, current serverles...	[]	Train
45,858	16	Title: Robust Proxy: Improving Adversarial Robustness by Robust Proxy Learning Abstract: Recently, it has been widely known that deep neural networks are highly vulnerable and easily broken by adversarial attacks. To mitigate the adversarial vulnerability, many defense algorithms have been proposed. Recently, to improv...	[ 17379 ]	Validation
45,859	30	Title: Answering Subjective Induction Questions on Products by Summarizing Multi-sources Multi-viewpoints Knowledge Abstract: This paper proposes a new task in the field of Answering Subjective Induction Question on Products (SUBJPQA). The answer to this kind of question is non-unique, but can be interpreted from many ...	[ 12341 ]	Validation
45,860	3	Title: Netizens, Academicians, and Information Professionals' Opinions About AI With Special Reference To ChatGPT Abstract: This study aims to understand the perceptions and opinions of academicians towards ChatGPT-3 by collecting and analyzing social media comments, and a survey was conducted with library and informat...	[]	Test
45,861	24	Title: How Does Attention Work in Vision Transformers? A Visual Analytics Attempt Abstract: Vision transformer (ViT) expands the success of transformer models from sequential data to images. The model decomposes an image into many smaller patches and arranges them into a sequence. Multi-head self-attentions are then ap...	[ 31099 ]	Train
45,862	5	Title: Computron: Serving Distributed Deep Learning Models with Model Parallel Swapping Abstract: Many of the most performant deep learning models today in fields like language and image understanding are fine-tuned models that contain billions of parameters. In anticipation of workloads that involve serving many of su...	[ 9403, 13700, 40630 ]	Train
45,863	23	Title: APIContext2Com: Code Comment Generation by Incorporating Pre-Defined API Documentation Abstract: Code comments are significantly helpful in comprehending software programs and also aid developers to save a great deal of time in software maintenance. Code comment generation aims to automatically predict comments ...	[ 6866 ]	Train
45,864	16	Title: Combination of Single and Multi-frame Image Super-resolution: An Analytical Perspective Abstract: Super-resolution is the process of obtaining a high-resolution image from one or more low-resolution images. Single image super-resolution (SISR) and multi-frame super-resolution (MFSR) methods have been evolved alm...	[]	Validation
45,865	27	Title: Design Considerations for 3RRR Parallel Robots with Lightweight, Approximate Static-Balancing Abstract: Balancing parallel robots throughout their workspace while avoiding the use of balancing masses and respecting design practicality constraints is difficult. Medical robots demand such compact and lightweight d...	[]	Validation
45,866	16	Title: Egocentric Video Task Translation @ Ego4D Challenge 2022 Abstract: This technical report describes the EgoTask Translation approach that explores relations among a set of egocentric video tasks in the Ego4D challenge. To improve the primary task of interest, we propose to leverage existing models developed for o...	[ 8271 ]	Test
45,867	23	Title: Applying information theory to software evolution Abstract: Although information theory has found success in disciplines, the literature on its applications to software evolution is limit. We are still missing artifacts that leverage the data and tooling available to measure how the information content of a proj...	[]	Validation
45,868	13	Title: Reducing ANN-SNN Conversion Error through Residual Membrane Potential Abstract: Spiking Neural Networks (SNNs) have received extensive academic attention due to the unique properties of low power consumption and high-speed computing on neuromorphic chips. Among various training methods of SNNs, ANN-SNN conversio...	[ 22536, 25384, 36842, 39312, 22837 ]	Train
45,869	23	Title: On Code Reuse from StackOverflow: An Exploratory Study on Jupyter Notebook Abstract: Jupyter Notebook is a popular tool among data analysts and scientists for working with data. It provides a way to combine code, documentation, and visualizations in a single, interactive environment, facilitating code reuse. Whi...	[]	Train
45,870	24	Title: HiSSNet: Sound Event Detection and Speaker Identification via Hierarchical Prototypical Networks for Low-Resource Headphones Abstract: Modern noise-cancelling headphones have significantly improved users' auditory experiences by removing unwanted background noise, but they can also block out sounds that matter t...	[]	Train
45,871	24	Title: Adversarial Sampling for Fairness Testing in Deep Neural Network Abstract: In this research, we focus on the usage of adversarial sampling to test for the fairness in the prediction of deep neural network model across different classes of image in a given dataset. While several framework had been proposed to ens...	[]	Train
45,872	30	Title: IUTEAM1 at MEDIQA-Chat 2023: Is simple fine tuning effective for multi layer summarization of clinical conversations? Abstract: Clinical conversation summarization has become an important application of Natural language Processing. In this work, we intend to analyze summarization model ensembling approaches, tha...	[]	Test
45,873	4	Title: Automatic Increase Market Systems (AIMS): Towards a deterministic theory for cryptocurrencies Abstract: The popularity of cryptocurrencies has grown significantly in recent years, and they have become an important asset for internet trading. One of the main drawbacks of cryptocurrencies is the high volatility an...	[]	Train
45,874	24	Title: Learning Physical Models that Can Respect Conservation Laws Abstract: Recent work in scientific machine learning (SciML) has focused on incorporating partial differential equation (PDE) information into the learning process. Much of this work has focused on relatively ``easy'' PDE operators (e.g., elliptic and p...	[ 4680, 35958 ]	Test
45,875	16	Title: Chat2Map: Efficient Scene Mapping from Multi-Ego Conversations Abstract: Can conversational videos captured from multiple egocentric viewpoints reveal the map of a scene in a cost-efficient way? We seek to answer this question by proposing a new problem: efficiently building the map of a previously unseen 3D env...	[ 8854 ]	Validation
45,876	24	Title: A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing Abstract: In this paper, we take a preliminary step towards solving the problem of causal discovery in knowledge tracing, i.e., finding the underlying causal relationship among different skills from real-world student response data. This pro...	[]	Test
45,877	24	Title: DRIP: Deep Regularizers for Inverse Problems Abstract: In this paper we consider inverse problems that are mathematically ill-posed. That is, given some (noisy) data, there is more than one solution that approximately fits the data. In recent years, deep neural techniques that find the most appropriate solution,...	[]	Train

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