node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
28,078 | 27 | Title: Electromagnets Under the Table: an Unobtrusive Magnetic Navigation System for Microsurgery
Abstract: Miniature magnetic tools have the potential to enable minimally invasive surgical techniques to be applied to space-restricted surgical procedures in areas such as neurosurgery. However, typical magnetic navigati... | [] | Train |
28,079 | 16 | Title: Active Semi-Supervised Learning by Exploring Per-Sample Uncertainty and Consistency
Abstract: Active Learning (AL) and Semi-supervised Learning are two techniques that have been studied to reduce the high cost of deep learning by using a small amount of labeled data and a large amount of unlabeled data. To impro... | [] | Test |
28,080 | 24 | Title: Feature Importance Measurement based on Decision Tree Sampling
Abstract: Random forest is effective for prediction tasks but the randomness of tree generation hinders interpretability in feature importance analysis. To address this, we proposed DT-Sampler, a SAT-based method for measuring feature importance in t... | [] | Train |
28,081 | 24 | Title: Random Feedback Alignment Algorithms to train Neural Networks: Why do they Align?
Abstract: Feedback alignment algorithms are an alternative to backpropagation to train neural networks, whereby some of the partial derivatives that are required to compute the gradient are replaced by random terms. This essentiall... | [] | Validation |
28,082 | 27 | Title: Collision-aware In-hand 6D Object Pose Estimation using Multiple Vision-based Tactile Sensors
Abstract: In this paper, we address the problem of estimating the in-hand 6D pose of an object in contact with multiple vision-based tactile sensors. We reason on the possible spatial configurations of the sensors along... | [
30938
] | Test |
28,083 | 30 | Title: EvolveMT: an Ensemble MT Engine Improving Itself with Usage Only
Abstract: This work proposes a method named EvolveMT for the efficient combination of multiple machine translation (MT) engines. The method selects the output from one engine for each segment, using online learning techniques to predict the most ap... | [] | Test |
28,084 | 24 | Title: Using Offline Data to Speed-up Reinforcement Learning in Procedurally Generated Environments
Abstract: One of the key challenges of Reinforcement Learning (RL) is the ability of agents to generalise their learned policy to unseen settings. Moreover, training RL agents requires large numbers of interactions with ... | [
23859
] | Train |
28,085 | 16 | Title: Medical visual question answering using joint self-supervised learning
Abstract: Visual Question Answering (VQA) becomes one of the most active research problems in the medical imaging domain. A well-known VQA challenge is the intrinsic diversity between the image and text modalities, and in the medical VQA task... | [] | Validation |
28,086 | 24 | Title: Permutation Equivariant Graph Framelets for Heterophilous Graph Learning
Abstract: The nature of heterophilous graphs is significantly different with that of homophilous graphs, which causes difficulties in early graph neural network models and suggests aggregations beyond 1-hop neighborhood. In this paper, we d... | [] | Test |
28,087 | 30 | Title: ChatGPT is Good but Bing Chat is Better for Vietnamese Students
Abstract: This study examines the efficacy of two SOTA large language models (LLMs), namely ChatGPT and Microsoft Bing Chat (BingChat), in catering to the needs of Vietnamese students. Although ChatGPT exhibits proficiency in multiple disciplines, B... | [
20739,
33220,
16841,
22286,
4850,
889
] | Train |
28,088 | 24 | Title: It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness
Abstract: Adversarial examples are inputs to machine learning models that an attacker has intentionally designed to confuse the model into making a mistake. Such examples pose a serious threat to the applicability of machine-learning... | [
13224,
1636
] | Train |
28,089 | 24 | Title: Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference
Abstract: Secure multi-party computation (MPC) allows users to offload machine learning inference on untrusted servers without having to share their privacy-sensitive data. Despite their strong security properties, MPC-based private i... | [
12156,
9076,
12944,
45652
] | Train |
28,090 | 4 | Title: AutoReP: Automatic ReLU Replacement for Fast Private Network Inference
Abstract: The growth of the Machine-Learning-As-A-Service (MLaaS) market has highlighted clients' data privacy and security issues. Private inference (PI) techniques using cryptographic primitives offer a solution but often have high computat... | [
19288,
11884,
17813
] | Train |
28,091 | 38 | Title: Retractions in Arts and Humanities: an Analysis of the Retraction Notices
Abstract: The aim of this work is to understand the retraction phenomenon in the arts and humanities domain through an analysis of the retraction notices: formal documents stating and describing the retraction of a particular publication. ... | [] | Train |
28,092 | 30 | Title: NESTLE: a No-Code Tool for Statistical Analysis of Legal Corpus
Abstract: The statistical analysis of large scale legal corpus can provide valuable legal insights. For such analysis one needs to (1) select a subset of the corpus using document retrieval tools, (2) structuralize text using information extraction ... | [] | Train |
28,093 | 16 | Title: Exploring Active 3D Object Detection from a Generalization Perspective
Abstract: To alleviate the high annotation cost in LiDAR-based 3D object detection, active learning is a promising solution that learns to select only a small portion of unlabeled data to annotate, without compromising model performance. Our ... | [
25760,
17673,
4310
] | Train |
28,094 | 16 | Title: The MONET dataset: Multimodal drone thermal dataset recorded in rural scenarios
Abstract: We present MONET, a new multimodal dataset captured using a thermal camera mounted on a drone that flew over rural areas, and recorded human and vehicle activities. We captured MONET to study the problem of object localisat... | [] | Validation |
28,095 | 24 | Title: Best arm identification in rare events
Abstract: We consider the best arm identification problem in the stochastic multi-armed bandit framework where each arm has a tiny probability of realizing large rewards while with overwhelming probability the reward is zero. A key application of this framework is in online... | [] | Train |
28,096 | 10 | Title: Rules based Heterogeneous Feature Transfer Learning using Fuzzy Inference
Abstract: Model transparency, label correlation learning and the robust-ness to label noise are crucial for multilabel learning. However, few existing methods study these three characteristics simultaneously. To address this challenge, we ... | [] | Train |
28,097 | 28 | Title: A Survey of Beam Management for mmWave and THz Communications Towards 6G
Abstract: Communication in millimeter wave (mmWave) and even terahertz (THz) frequency bands is ushering in a new era of wireless communications. Beam management, namely initial access and beam tracking, has been recognized as an essential ... | [
16200,
7667,
24551
] | Train |
28,098 | 24 | Title: Stabilizing GANs' Training with Brownian Motion Controller
Abstract: The training process of generative adversarial networks (GANs) is unstable and does not converge globally. In this paper, we examine the stability of GANs from the perspective of control theory and propose a universal higher-order noise-based c... | [] | Validation |
28,099 | 16 | Title: Confidence-based Reliable Learning under Dual Noises
Abstract: Deep neural networks (DNNs) have achieved remarkable success in a variety of computer vision tasks, where massive labeled images are routinely required for model optimization. Yet, the data collected from the open world are unavoidably polluted by no... | [
23049,
16807
] | Train |
28,100 | 4 | Title: SecOComp: A Fast and Secure Simultaneous Compression and Encryption Scheme
Abstract: We live in a data-driven era that involves the generation, collection and processing of a massive amount of data. This data often contains valuable intellectual property and sensitive user information that must be safeguarded. T... | [] | Train |
28,101 | 16 | Title: A Comprehensive Analysis of Real-World Image Captioning and Scene Identification
Abstract: Image captioning is a computer vision task that involves generating natural language descriptions for images. This method has numerous applications in various domains, including image retrieval systems, medicine, and vario... | [
10624,
2619,
45685
] | Train |
28,102 | 2 | Title: The Undecidability of Pattern Matching in Calculi Where Primitive Recursive Functions are Representable
Abstract: nan | [] | Test |
28,103 | 16 | Title: Generative-based Fusion Mechanism for Multi-Modal Tracking
Abstract: Generative models (GMs) have received increasing research interest for their remarkable capacity to achieve comprehensive understanding. However, their potential application in the domain of multi-modal tracking has remained relatively unexplor... | [
46154
] | Train |
28,104 | 16 | Title: Improving Pixel-based MIM by Reducing Wasted Modeling Capability
Abstract: There has been significant progress in Masked Image Modeling (MIM). Existing MIM methods can be broadly categorized into two groups based on the reconstruction target: pixel-based and tokenizer-based approaches. The former offers a simple... | [
42195,
20838
] | Train |
28,105 | 16 | Title: Waste Detection and Change Analysis based on Multispectral Satellite Imagery
Abstract: One of the biggest environmental problems of our time is the increase in illegal landfills in forests, rivers, on river banks and other secluded places. In addition, waste in rivers causes damage not only locally, but also dow... | [] | Validation |
28,106 | 24 | Title: Can Differentiable Decision Trees Learn Interpretable Reward Functions?
Abstract: There is an increasing interest in learning reward functions that model human intent and human preferences. However, many frameworks use blackbox learning methods that, while expressive, are difficult to interpret. We propose and e... | [
46149,
42581,
37087
] | Validation |
28,107 | 24 | Title: ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation
Abstract: The incredible capabilities of generative artificial intelligence models have inevitably led to their application in the domain of drug discovery. It is therefore of tremendous interest to develop met... | [
5447
] | Validation |
28,108 | 3 | Title: An Interpretive Framework for Narrower Immunity Under Section 230 of the Communications Decency Act
Abstract: Almost all courts to interpret Section 230 of the Communications Decency Act have construed its ambiguously worded immunity provision broadly, shielding Internet intermediaries from tort liability so lon... | [] | Train |
28,109 | 24 | Title: A Meta-heuristic Approach to Estimate and Explain Classifier Uncertainty
Abstract: Trust is a crucial factor affecting the adoption of machine learning (ML) models. Qualitative studies have revealed that end-users, particularly in the medical domain, need models that can express their uncertainty in decision-mak... | [] | Validation |
28,110 | 27 | Title: Flexible Supervised Autonomy for Exploration in Subterranean Environments
Abstract: While the capabilities of autonomous systems have been steadily improving in recent years, these systems still struggle to rapidly explore previously unknown environments without the aid of GPS-assisted navigation. The DARPA Subt... | [] | Train |
28,111 | 24 | Title: DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification
Abstract: The Internet of Things (IoT) has become an emerging trend that connects heterogeneous devices and enables them with new capabilities. Many applications exploit machine learning methodology to dissect collected data, and... | [
42344,
636
] | Train |
28,112 | 23 | Title: Representation Learning for Stack Overflow Posts: How Far are We?
Abstract: The tremendous success of Stack Overflow has accumulated an extensive corpus of software engineering knowledge, thus motivating researchers to propose various solutions for analyzing its content.The performance of such solutions hinges s... | [
18984,
34493
] | Train |
28,113 | 16 | Title: Shape-Aware Text-Driven Layered Video Editing
Abstract: Temporal consistency is essential for video editing applications. Existing work on layered representation of videos allows propagating edits consistently to each frame. These methods, however, can only edit object appearance rather than object shape changes... | [
20960,
25666,
1860,
21324,
39759,
22260,
17526
] | Train |
28,114 | 6 | Title: From Psychological Traits to Safety Warnings: Three Studies on Recommendations in a Smart Home Environment
Abstract: In this paper, we report on three experiments we have carried out in the context of the EMPATHY project, with the aim of helping users make better configuration choices in a smart home environment... | [] | Train |
28,115 | 10 | Title: Deep Q-Learning versus Proximal Policy Optimization: Performance Comparison in a Material Sorting Task
Abstract: This paper presents a comparison between two well-known deep Reinforcement Learning (RL) algorithms: Deep Q-Learning (DQN) and Proximal Policy optimization (PPO) in a simulated production system. We u... | [] | Train |
28,116 | 10 | Title: Reinforcement Learning Based Power Grid Day-Ahead Planning and AI-Assisted Control
Abstract: The ongoing transition to renewable energy is increasing the share of fluctuating power sources like wind and solar, raising power grid volatility and making grid operation increasingly complex and costly. In our prior w... | [
25095
] | Train |
28,117 | 4 | Title: A 334μW 0.158mm2 ASIC for Post-Quantum Key-Encapsulation Mechanism Saber with Low-latency Striding Toom-Cook Multiplication Authors Version
Abstract: The hard mathematical problems that assure the security of our current public-key cryptography (RSA, ECC) are broken if and when a quantum computer appears renderi... | [] | Train |
28,118 | 16 | Title: Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning
Abstract: We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowled... | [] | Validation |
28,119 | 30 | Title: Word sense extension
Abstract: Humans often make creative use of words to expressnovel senses. A long-standing effort in natural language processing hasbeen focusing on word sense disambiguation (WSD), but little has been explored about how the sense inventory of a word may be extended toward novel meanings. We ... | [] | Test |
28,120 | 16 | Title: Universal Semi-supervised Model Adaptation via Collaborative Consistency Training
Abstract: In this paper, we introduce a realistic and challenging domain adaptation problem called Universal Semi-supervised Model Adaptation (USMA), which i) requires only a pre-trained source model, ii) allows the source and targ... | [] | Train |
28,121 | 16 | Title: Hierarchical Semantic Perceptual Listener Head Video Generation: A High-performance Pipeline
Abstract: In dyadic speaker-listener interactions, the listener's head reactions along with the speaker's head movements, constitute an important non-verbal semantic expression together. The listener Head generation task... | [
29595
] | Validation |
28,122 | 16 | Title: Get3DHuman: Lifting StyleGAN-Human into a 3D Generative Model using Pixel-aligned Reconstruction Priors
Abstract: Fast generation of high-quality 3D digital humans is important to a vast number of applications ranging from entertainment to professional concerns. Recent advances in differentiable rendering have e... | [
32384
] | Train |
28,123 | 10 | Title: Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration
Abstract: We propose an image restoration algorithm that can control the perceptual quality and/or the mean square error (MSE) of any pre-trained model, trading one over the other at test time. Our algorithm is few-shot: Given ab... | [] | Train |
28,124 | 16 | Title: DeNoising-MOT: Towards Multiple Object Tracking with Severe Occlusions
Abstract: Multiple object tracking (MOT) tends to become more challenging when severe occlusions occur. In this paper, we analyze the limitations of traditional Convolutional Neural Network-based methods and Transformer-based methods in handl... | [
39370,
46154,
31169,
8767
] | Train |
28,125 | 22 | Title: Targeted Static Analysis for OCaml C Stubs: eliminating gremlins from the code
Abstract: Migration to OCaml 5 requires updating a lot of C bindings due to the removal of naked pointer support. Writing OCaml user-defined primitives in C is a necessity, but is unsafe and error-prone. It does not benefit from eithe... | [] | Train |
28,126 | 16 | Title: Stochastic Multi-Person 3D Motion Forecasting
Abstract: This paper aims to deal with the ignored real-world complexities in prior work on human motion forecasting, emphasizing the social properties of multi-person motion, the diversity of motion and social interactions, and the complexity of articulated motion. ... | [
38181
] | Train |
28,127 | 24 | Title: Asynchronously Trained Distributed Topographic Maps
Abstract: Topographic feature maps are low dimensional representations of data, that preserve spatial dependencies. Current methods of training such maps (e.g. self organizing maps - SOM, generative topographic maps) require centralized control and synchronous ... | [] | Validation |
28,128 | 30 | Title: NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization
Abstract: Accessing medical literature is difficult for laypeople as the content is written for specialists and contains medical jargon. Automated text simplification methods offer a potential means to ... | [
8756
] | Train |
28,129 | 27 | Title: Efficient Real-time Path Planning with Self-evolving Particle Swarm Optimization in Dynamic Scenarios
Abstract: Particle Swarm Optimization (PSO) has demonstrated efficacy in addressing static path planning problems. Nevertheless, such application on dynamic scenarios has been severely precluded by PSO's low com... | [] | Train |
28,130 | 6 | Title: A foolish consistency? Aligning interface objects hinders location recall and may induce collinear errors
Abstract: During our nearly constant use of digital devices, perhaps our most frequent need is to visually identify icons representing our content and invoke the actions to manipulate them. Almost since the ... | [] | Train |
28,131 | 10 | Title: If consciousness is dynamically relevant, artificial intelligence isn't conscious
Abstract: We demonstrate that if consciousness is relevant for the temporal evolution of a system's states -- that is, if it is dynamically relevant -- then AI systems cannot be conscious. That is because AI systems run on CPUs, GP... | [
31113,
87
] | Train |
28,132 | 24 | Title: An Adaptive Method for Weak Supervision with Drifting Data
Abstract: We introduce an adaptive method with formal quality guarantees for weak supervision in a non-stationary setting. Our goal is to infer the unknown labels of a sequence of data by using weak supervision sources that provide independent noisy sign... | [
41454
] | Validation |
28,133 | 16 | Title: Distilling Knowledge for Short-to-Long Term Trajectory Prediction
Abstract: Long-term trajectory forecasting is a challenging problem in the field of computer vision and machine learning. In this paper, we propose a new method dubbed Di-Long ("Distillation for Long-Term trajectory") for long-term trajectory fore... | [] | Train |
28,134 | 28 | Title: Universal Reverse Information Projections and Optimal E-statistics
Abstract: Information projections have found many important applications in probability theory, statistics, and related fields. In the field of hypothesis testing in particular, the reverse information projection (RIPr) has recently been shown to... | [] | Train |
28,135 | 30 | Title: Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging
Abstract: Climate change is the defining issue of our time, and we are at a defining moment. Various interest groups, social movement organizations, and individuals engage in collective action on this issue on social media. In addition,... | [] | Validation |
28,136 | 16 | Title: Parkinsons Disease Detection via Resting-State Electroencephalography Using Signal Processing and Machine Learning Techniques
Abstract: Parkinsons Disease (PD) is a neurodegenerative disorder resulting in motor deficits due to advancing degeneration of dopaminergic neurons. PD patients report experiencing tremor... | [] | Test |
28,137 | 27 | Title: HuBo-VLM: Unified Vision-Language Model designed for HUman roBOt interaction tasks
Abstract: Human robot interaction is an exciting task, which aimed to guide robots following instructions from human. Since huge gap lies between human natural language and machine codes, end to end human robot interaction models ... | [
10624,
13700,
381
] | Train |
28,138 | 13 | Title: Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
Abstract: Deep spiking neural networks (SNNs) have drawn much attention in recent years because of their low power consumption, biological rationality and event-driven proper... | [
1400,
39185,
34896
] | Validation |
28,139 | 30 | Title: Large Language Model for Science: A Study on P vs. NP
Abstract: In this work, we use large language models (LLMs) to augment and accelerate research on the P versus NP problem, one of the most important open problems in theoretical computer science and mathematics. Specifically, we propose Socratic reasoning, a ... | [
40610,
33220,
40018,
13510
] | Train |
28,140 | 30 | Title: Multi-hop Commonsense Knowledge Injection Framework for Zero-Shot Commonsense Question Answering
Abstract: Commonsense question answering (QA) research requires machines to answer questions based on commonsense knowledge. However, this research requires expensive labor costs to annotate data as the basis of rese... | [
19405,
37277
] | Train |
28,141 | 16 | Title: Semantic-SAM: Segment and Recognize Anything at Any Granularity
Abstract: In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advantages: semantic-awareness and granularity-abundance. To achie... | [
17633,
32995,
37254,
42599,
2984,
17390,
29112,
31225,
34074,
31323,
26269
] | Train |
28,142 | 27 | Title: Local Neural Descriptor Fields: Locally Conditioned Object Representations for Manipulation
Abstract: A robot operating in a household environment will see a wide range of unique and unfamiliar objects. While a system could train on many of these, it is infeasible to predict all the objects a robot will see. In ... | [
35541,
22805,
43693
] | Validation |
28,143 | 23 | Title: Answering Uncertain, Under-Specified API Queries Assisted by Knowledge-Aware Human-AI Dialogue
Abstract: Developers' API needs should be more pragmatic, such as seeking suggestive, explainable, and extensible APIs rather than the so-called best result. Existing API search research cannot meet these pragmatic nee... | [] | Test |
28,144 | 16 | Title: SMPLitex: A Generative Model and Dataset for 3D Human Texture Estimation from Single Image
Abstract: We propose SMPLitex, a method for estimating and manipulating the complete 3D appearance of humans captured from a single image. SMPLitex builds upon the recently proposed generative models for 2D images, and ext... | [
625,
44100
] | Train |
28,145 | 24 | Title: Fact or Artifact? Revise Layer-wise Relevance Propagation on various ANN Architectures
Abstract: Layer-wise relevance propagation (LRP) is a widely used and powerful technique to reveal insights into various artificial neural network (ANN) architectures. LRP is often used in the context of image classification. ... | [] | Validation |
28,146 | 24 | Title: Lightweight Modeling of User Context Combining Physical and Virtual Sensor Data
Abstract: The multitude of data generated by sensors available on users' mobile devices, combined with advances in machine learning techniques, support context-aware services in recognizing the current situation of a user (i.e., phys... | [
32773,
14759
] | Validation |
28,147 | 6 | Title: Multimodal User Authentication in Smart Environments: Survey of User Attitudes
Abstract: As users shift from interacting actively with devices with screens to interacting seamlessly with smart environments, novel models of user authentication will be needed to maintain the security and privacy of user data. To u... | [] | Train |
28,148 | 16 | Title: Zero-shot Referring Image Segmentation with Global-Local Context Features
Abstract: Referring image segmentation (RIS) aims to find a segmentation mask given a referring expression grounded to a region of the input image. Collecting labelled datasets for this task, however, is notoriously costly and labor-intens... | [
44197,
14599,
11240,
5583,
12953,
34943
] | Train |
28,149 | 31 | Title: Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems
Abstract: Existing research efforts for multi-interest candidate matching in recommender systems mainly focus on improving model architecture or incorporating additional information, neglecting the importance of training schemes. Th... | [
26678,
30131,
21302
] | Train |
28,150 | 13 | Title: Bi-level Multi-objective Evolutionary Learning: A Case Study on Multi-task Graph Neural Topology Search
Abstract: The construction of machine learning models involves many bi-level multi-objective optimization problems (BL-MOPs), where upper level (UL) candidate solutions must be evaluated via training weights o... | [] | Train |
28,151 | 30 | Title: Benchmarking Large Language Models for News Summarization
Abstract: Large language models (LLMs) have shown promise for automatic summarization but the reasons behind their successes are poorly understood. By conducting a human evaluation on ten LLMs across different pretraining methods, prompts, and model scale... | [
28294,
18441,
25737,
38167,
9240,
39451,
35101,
24479,
27039,
11425,
8482,
11809,
22051,
44833,
31648,
28580,
14635,
14380,
37935,
27440,
18741,
12087,
13495,
26810,
6075,
35388,
17349,
42949,
24524,
9934,
18515,
6485,
26199,
8286,
25830,
1639,
... | Train |
28,152 | 30 | Title: Multilingual Few-Shot Learning via Language Model Retrieval
Abstract: Transformer-based language models have achieved remarkable success in few-shot in-context learning and drawn a lot of research interest. However, these models' performance greatly depends on the choice of the example prompts and also has high ... | [] | Train |
28,153 | 23 | Title: Automated Static Warning Identification via Path-based Semantic Representation
Abstract: Despite their ability to aid developers in detecting potential defects early in the software development life cycle, static analysis tools often suffer from precision issues (i.e., high false positive rates of reported alarm... | [] | Test |
28,154 | 24 | Title: The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks
Abstract: Do neural networks, trained on well-understood algorithmic tasks, reliably rediscover known algorithms for solving those tasks? Several recent studies, on tasks ranging from group arithmetic to in-context linear regressi... | [
38338,
2342,
7758,
4434,
38834,
34426
] | Test |
28,155 | 30 | Title: Can Large Language Models Infer and Disagree Like Humans?
Abstract: Large Language Models (LLMs) have shown stellar achievements in solving a broad range of tasks. When generating text, it is common to sample tokens from these models: whether LLMs closely align with the human disagreement distribution has not be... | [
40192,
24841,
30029,
846,
14609,
12602
] | Train |
28,156 | 16 | Title: Cross-view Action Recognition Understanding From Exocentric to Egocentric Perspective
Abstract: Understanding action recognition in egocentric videos has emerged as a vital research topic with numerous practical applications. With the limitation in the scale of egocentric data collection, learning robust deep le... | [] | Test |
28,157 | 16 | Title: Improving Knowledge Distillation Via Transferring Learning Ability
Abstract: Existing knowledge distillation methods generally use a teacher-student approach, where the student network solely learns from a well-trained teacher. However, this approach overlooks the inherent differences in learning abilities betwe... | [] | Train |
28,158 | 30 | Title: ContrastWSD: Enhancing Metaphor Detection with Word Sense Disambiguation Following the Metaphor Identification Procedure
Abstract: This paper presents ContrastWSD, a RoBERTa-based metaphor detection model that integrates the Metaphor Identification Procedure (MIP) and Word Sense Disambiguation (WSD) to extract a... | [
36962,
19127
] | Test |
28,159 | 18 | Title: Physical Implementation of a Tunable Memristor-based Chua's Circuit
Abstract: Nonlinearity is a central feature in demanding computing applications that aim to deal with tasks such as optimization or classification. Furthermore, the consensus is that nonlinearity should not be only exploited at the algorithm lev... | [] | Train |
28,160 | 8 | Title: Federated Multi-Agent Deep Reinforcement Learning for Dynamic and Flexible 3D Operation of 5G Multi-MAP Networks
Abstract: This paper addresses the efficient management of Mobile Access Points (MAPs), which are Unmanned Aerial Vehicles (UAV), in 5G networks. We propose a two-level hierarchical architecture, whic... | [
13944,
14990
] | Train |
28,161 | 23 | Title: DAppSCAN: Building Large-Scale Datasets for Smart Contract Weaknesses in DApp Projects
Abstract: The Smart Contract Weakness Classification Registry (SWC Registry) is a widely recognized list of smart contract weaknesses specific to the Ethereum platform. In recent years, significant research efforts have been d... | [] | Train |
28,162 | 26 | Title: Finding Influencers in Complex Networks: An Effective Deep Reinforcement Learning Approach
Abstract: Maximizing influences in complex networks is a practically important but computationally challenging task for social network analysis, due to its NP- hard nature. Most current approximation or heuristic methods e... | [] | Test |
28,163 | 16 | Title: SPTS v2: Single-Point Scene Text Spotting
Abstract: End-to-end scene text spotting has made significant progress due to its intrinsic synergy between text detection and recognition. Previous methods commonly regard manual annotations such as horizontal rectangles, rotated rectangles, quadrangles, and polygons as... | [
37498
] | Test |
28,164 | 16 | Title: Three Towers: Flexible Contrastive Learning with Pretrained Image Models
Abstract: We introduce Three Towers (3T), a flexible method to improve the contrastive learning of vision-language models by incorporating pretrained image classifiers. While contrastive models are usually trained from scratch, LiT (Zhai et... | [] | Train |
28,165 | 24 | Title: Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph Transformers
Abstract: The ability to anticipate technical expertise and capability evolution trends globally is essential for national and global security, especially in safety-critical domains like nuclear non... | [] | Train |
28,166 | 25 | Title: Contrastive Learning-Based Audio to Lyrics Alignment for Multiple Languages
Abstract: Lyrics alignment gained considerable attention in recent years. State-of-the-art systems either re-use established speech recognition toolkits, or design end-to-end solutions involving a Connectionist Temporal Classification (C... | [] | Train |
28,167 | 30 | Title: HausaNLP at SemEval-2023 Task 10: Transfer Learning, Synthetic Data and Side-information for Multi-level Sexism Classification
Abstract: We present the findings of our participation in the SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS) task, a shared task on offensive language (sexism) detec... | [
16936
] | Train |
28,168 | 25 | Title: Towards Measuring and Scoring Speaker Diarization Fairness
Abstract: Speaker diarization, or the task of finding"who spoke and when", is now used in almost every speech processing application. Nevertheless, its fairness has not yet been evaluated because there was no protocol to study its biases one by one. In t... | [] | Train |
28,169 | 7 | Title: Towards Additively Manufactured Metamaterials with Powder Inclusions for Controllable Dissipation: The Critical Influence of Packing Density
Abstract: Particle dampers represent a simple yet effective means to reduce unwanted oscillations when attached to structural components. Powder bed fusion additive manufac... | [
35361
] | Validation |
28,170 | 24 | Title: Knowledge-Guided Additive Modeling For Supervised Regression
Abstract: Learning processes by exploiting restricted domain knowledge is an important task across a plethora of scientific areas, with more and more hybrid methods combining data-driven and model-based approaches. However, while such hybrid methods ha... | [] | Validation |
28,171 | 16 | Title: Adaptive Semantic Consistency for Cross-domain Few-shot Classification
Abstract: Cross-domain few-shot classification (CD-FSC) aims to identify novel target classes with a few samples, assuming that there exists a domain shift between source and target domains. Existing state-of-the-art practices typically pre-t... | [] | Train |
28,172 | 25 | Title: SoundSieve: Seconds-Long Audio Event Recognition on Intermittently-Powered Systems
Abstract: A fundamental problem of every intermittently-powered sensing system is that signals acquired by these systems over a longer period in time are also intermittent. As a consequence, these systems fail to capture parts of ... | [
16976,
17032
] | Test |
28,173 | 16 | Title: SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation
Abstract: Learning models on one labeled dataset that generalize well on another domain is a difficult task, as several shifts might happen between the data domains. This is notably the case for lidar data, for which models can exhibit large p... | [
4443,
27237,
21093
] | Train |
28,174 | 24 | Title: Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning
Abstract: We investigate policy transfer using image-to-semantics translation to mitigate learning difficulties in vision-based robotics control agents. This problem assumes two environments: a simulator environment with semant... | [] | Train |
28,175 | 30 | Title: Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion
Abstract: nan | [] | Train |
28,176 | 24 | Title: Learning Variational Neighbor Labels for Test-Time Domain Generalization
Abstract: This paper strives for domain generalization, where models are trained exclusively on source domains before being deployed at unseen target domains. We follow the strict separation of source training and target testing but exploit... | [
21091,
26605,
5651,
26803,
43608,
3291
] | Train |
28,177 | 16 | Title: Fooling State-of-the-art Deepfake Detection with High-quality Deepfakes
Abstract: Due to the rising threat of deepfakes to security and privacy, it is most important to develop robust and reliable detectors. In this paper, we examine the need for high-quality samples in the training datasets of such detectors. A... | [] | Train |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.