node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
21,078 | 16 | Title: Towards Language-guided Interactive 3D Generation: LLMs as Layout Interpreter with Generative Feedback
Abstract: Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within the 3D space. Recen... | [
27426,
37987,
13700,
33220,
13510,
2222,
3609,
41146,
3067,
541,
10527
] | Train |
21,079 | 27 | Title: Improving safety in physical human-robot collaboration via deep metric learning
Abstract: Direct physical interaction with robots is becoming increasingly important in flexible production scenarios, but robots without protective fences also pose a greater risk to the operator. In order to keep the risk potential... | [
20252
] | Test |
21,080 | 24 | Title: Autonomous Soft Tissue Retraction Using Demonstration-Guided Reinforcement Learning
Abstract: In the context of surgery, robots can provide substantial assistance by performing small, repetitive tasks such as suturing, needle exchange, and tissue retraction, thereby enabling surgeons to concentrate on more compl... | [
17466
] | Train |
21,081 | 24 | Title: GFlowNets for AI-Driven Scientific Discovery
Abstract: Tackling the most pressing problems for humanity, such as the climate crisis and the threat of global pandemics, requires accelerating the pace of scientific discovery. While science has traditionally relied... | [
43749,
34630,
15438,
24784,
17457,
19858,
29809,
17308
] | Train |
21,082 | 23 | Title: Neural-FEBI: Accurate Function Identification in Ethereum Virtual Machine Bytecode
Abstract: nan | [
34006
] | Train |
21,083 | 24 | Title: Batch Updating of a Posterior Tree Distribution over a Meta-Tree
Abstract: Previously, we proposed a probabilistic data generation model represented by an unobservable tree and a sequential updating method to calculate a posterior distribution over a set of trees. The set is called a meta-tree. In this paper, we... | [] | Validation |
21,084 | 3 | Title: OMOD: An open-source tool for creating disaggregated mobility demand based on OpenStreetMap
Abstract: nan | [] | Train |
21,085 | 24 | Title: Turning Privacy-preserving Mechanisms against Federated Learning
Abstract: Recently, researchers have successfully employed Graph Neural Networks (GNNs) to build enhanced recommender systems due to their capability to learn patterns from the interaction between involved entities. In addition, previous studies ha... | [] | Train |
21,086 | 16 | Title: Evaluating the Reliability of CNN Models on Classifying Traffic and Road Signs using LIME
Abstract: The objective of this investigation is to evaluate and contrast the effectiveness of four state-of-the-art pre-trained models, ResNet-34, VGG-19, DenseNet-121, and Inception V3, in classifying traffic and road sig... | [] | Validation |
21,087 | 30 | Title: TransFool: An Adversarial Attack against Neural Machine Translation Models
Abstract: Deep neural networks have been shown to be vulnerable to small perturbations of their inputs, known as adversarial attacks. In this paper, we investigate the vulnerability of Neural Machine Translation (NMT) models to adversaria... | [
11174,
12297,
5208,
12218,
5086
] | Train |
21,088 | 28 | Title: On the Degrees of Freedom of RIS-Aided Holographic MIMO Systems
Abstract: In this paper, we study surface-based communication systems based on different levels of channel state information for system optimization. We analyze the system performance in terms of rate and degrees of freedom (DoF). We show that the d... | [] | Validation |
21,089 | 3 | Title: ChatGPT and Works Scholarly: Best Practices and Legal Pitfalls in Writing with AI
Abstract: Recent advances in artificial intelligence (AI) have raised questions about whether the use of AI is appropriate and legal in various professional contexts. Here, we present a perspective on how scholars may approach writ... | [
13239
] | Validation |
21,090 | 24 | Title: Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method
Abstract: Graph Representation Learning (GRL) is an influential methodology, enabling a more profound understanding of graph-structured data and aiding graph clustering, a critical task across various domains. The... | [] | Train |
21,091 | 16 | Title: Meta-Causal Learning for Single Domain Generalization
Abstract: Single domain generalization aims to learn a model from a single training domain (source domain) and apply it to multiple unseen test domains (target domains). Existing methods focus on expanding the distribution of the training domain to cover the ... | [
24630,
28176,
15814
] | Train |
21,092 | 13 | Title: PAO: A general particle swarm algorithm with exact dynamics and closed-form transition densities
Abstract: A great deal of research has been conducted in the consideration of meta-heuristic optimisation methods that are able to find global optima in settings that gradient based optimisers have traditionally stru... | [] | Validation |
21,093 | 16 | Title: Instant Domain Augmentation for LiDAR Semantic Segmentation
Abstract: Despite the increasing popularity of LiDAR sensors, perception algorithms using 3D LiDAR data struggle with the sensor-bias problem. Specifically, the performance of perception algorithms significantly drops when an unseen specification of the... | [
41730,
29224,
13165,
28173,
13532,
38270
] | Train |
21,094 | 16 | Title: Free-Form Composition Networks for Egocentric Action Recognition
Abstract: Egocentric action recognition is gaining significant attention in the field of human action recognition. In this paper, we address data scarcity issue in egocentric action recognition from a compositional generalization perspective. To ta... | [] | Train |
21,095 | 27 | Title: An ensemble of online estimation methods for one degree-of-freedom models of unmanned surface vehicles: applied theory and preliminary field results with eight vehicles
Abstract: In this paper we report an experimental evaluation of three popular methods for online system identification of unmanned surface vehic... | [] | Train |
21,096 | 16 | Title: Learning Context-aware Classifier for Semantic Segmentation
Abstract: Semantic segmentation is still a challenging task for parsing diverse contexts in different scenes, thus the fixed classifier might not be able to well address varying feature distributions during testing. Different from the mainstream literat... | [
13824,
8769,
34314,
35754
] | Train |
21,097 | 24 | Title: Is dataset condensation a silver bullet for healthcare data sharing?
Abstract: Safeguarding personal information is paramount for healthcare data sharing, a challenging issue without any silver bullet thus far. We study the prospect of a recent deep-learning advent, dataset condensation (DC), in sharing healthca... | [] | Train |
21,098 | 24 | Title: Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback
Abstract: The ensemble method is a promising way to mitigate the overestimation issue in Q-learning, where multiple function approximators are used to estimate the action values. It is known that the estimation bias hinges heavily on the... | [
1808,
30200
] | Train |
21,099 | 16 | Title: NoisyTwins: Class-Consistent and Diverse Image Generation Through StyleGANs
Abstract: StyleGANs are at the forefront of controllable image generation as they produce a latent space that is semantically disentangled, making it suitable for image editing and manipulation. However, the performance of StyleGANs seve... | [] | Train |
21,100 | 26 | Title: Measuring Centralization of Online Platforms Through Size and Interconnection of Communities
Abstract: Decentralized architecture offers a robust and flexible structure for online platforms, since centralized moderation and computation can be easy to disrupt with targeted attacks. However, a platform offering a ... | [
32977,
4492
] | Train |
21,101 | 24 | Title: Autodecompose: A generative self-supervised model for semantic decomposition
Abstract: We introduce Autodecompose, a novel self-supervised generative model that decomposes data into two semantically independent properties: the desired property, which captures a specific aspect of the data (e.g. the voice in an a... | [] | Test |
21,102 | 31 | Title: Self-supervised Contrastive BERT Fine-tuning for Fusion-Based Reviewed-Item Retrieval
Abstract: nan | [
4498
] | Train |
21,103 | 3 | Title: Use case cards: a use case reporting framework inspired by the European AI Act
Abstract: Despite recent efforts by the Artificial Intelligence (AI) community to move towards standardised procedures for documenting models, methods, systems or datasets, there is currently no methodology focused on use cases aligne... | [
37648
] | Validation |
21,104 | 24 | Title: Avalanche: A PyTorch Library for Deep Continual Learning
Abstract: Continual learning is the problem of learning from a nonstationary stream of data, a fundamental issue for sustainable and efficient training of deep neural networks over time. Unfortunately, deep learning libraries only provide primitives for of... | [
15129,
23466,
39220
] | Test |
21,105 | 24 | Title: GUAP: Graph Universal Attack Through Adversarial Patching
Abstract: Graph neural networks (GNNs) are a class of effective deep learning models for node classification tasks; yet their predictive capability may be severely compromised under adversarially designed unnoticeable perturbations to the graph structure ... | [
26138
] | Train |
21,106 | 30 | Title: Semantic Structure Enhanced Event Causality Identification
Abstract: Event Causality Identification (ECI) aims to identify causal relations between events in unstructured texts.This is a very challenging task, because causal relations are usually expressed by implicit associations between events.Existing methods... | [] | Train |
21,107 | 27 | Title: Modeling Group Dynamics for Personalized Robot-Mediated Interactions
Abstract: The field of human-human-robot interaction (HHRI) uses social robots to positively influence how humans interact with each other. This objective requires models of human understanding that consider multiple humans in an interaction as... | [
40143
] | Test |
21,108 | 16 | Title: Autonomous Underwater Robotic System for Aquaculture Applications
Abstract: Aquaculture is a thriving food-producing sector producing over half of the global fish consumption. However, these aquafarms pose significant challenges such as biofouling, vegetation, and holes within their net pens and have a profound ... | [] | Test |
21,109 | 4 | Title: SemDiff: Binary Similarity Detection by Diffing Key-Semantics Graphs
Abstract: Binary similarity detection is a critical technique that has been applied in many real-world scenarios where source code is not available, e.g., bug search, malware analysis, and code plagiarism detection. Existing works are ineffecti... | [] | Train |
21,110 | 8 | Title: Introducing Peer Copy - A Fully Decentralized Peer-to-Peer File Transfer Tool
Abstract: Peer Copy is a decentralized, peer-to-peer file transfer tool based on libp2p. It allows any two parties that are either both on the same network or connected via the internet to transfer the contents of a file based on a par... | [] | Validation |
21,111 | 30 | Title: Speech Emotion Diarization: Which Emotion Appears When?
Abstract: Speech Emotion Recognition (SER) typically relies on utterance-level solutions. However, emotions conveyed through speech should be considered as discrete speech events with definite temporal boundaries, rather than attributes of the entire uttera... | [] | Train |
21,112 | 16 | Title: ContactArt: Learning 3D Interaction Priors for Category-level Articulated Object and Hand Poses Estimation
Abstract: We propose a new dataset and a novel approach to learning hand-object interaction priors for hand and articulated object pose estimation. We first collect a dataset using visual teleoperation, whe... | [
15221
] | Test |
21,113 | 4 | Title: Privacy in Population Protocols with Probabilistic Scheduling
Abstract: The population protocol model introduced by Angluin et al. in 2006 offers a theoretical framework for designing and analyzing distributed algorithms among limited-resource mobile agents. While the original population protocol model considers... | [] | Train |
21,114 | 16 | Title: Corner Detection Based on Multi-directional Gabor Filters with Multi-scales
Abstract: Gabor wavelet is an essential tool for image analysis and computer vision tasks. Local structure tensors with multiple scales are widely used in local feature extraction. Our research indicates that the current corner detection... | [] | Train |
21,115 | 16 | Title: Learning Common Rationale to Improve Self-Supervised Representation for Fine-Grained Visual Recognition Problems
Abstract: Self-supervised learning (SSL) strategies have demonstrated remarkable performance in various recognition tasks. However, both our preliminary investigation and recent studies suggest that t... | [] | Train |
21,116 | 16 | Title: What can a cook in Italy teach a mechanic in India? Action Recognition Generalisation Over Scenarios and Locations
Abstract: We propose and address a new generalisation problem: can a model trained for action recognition successfully classify actions when they are performed within a previously unseen scenario an... | [
8854
] | Train |
21,117 | 22 | Title: Separated and Shared Effects in Higher-Order Languages
Abstract: Effectful programs interact in ways that go beyond simple input-output, making compositional reasoning challenging. Existing work has shown that when such programs are ``separate'', i.e., when programs do not interfere with each other, it can be ea... | [] | Validation |
21,118 | 16 | Title: OA-BEV: Bringing Object Awareness to Bird's-Eye-View Representation for Multi-Camera 3D Object Detection
Abstract: The recent trend for multi-camera 3D object detection is through the unified bird's-eye view (BEV) representation. However, directly transforming features extracted from the image-plane view to BEV ... | [
11097,
39131
] | Train |
21,119 | 20 | Title: Insertion-Only Dynamic Connectivity in General Disk Graphs
Abstract: Let $S \subseteq \mathbb{R}^2$ be a set of $n$ \emph{sites} in the plane, so that every site $s \in S$ has an \emph{associated radius} $r_s>0$. Let $D(S)$ be the \emph{disk intersection graph} defined by $S$, i.e., the graph with vertex set $S$... | [] | Validation |
21,120 | 34 | Title: Sampling from Network Reliability in Near-linear Time
Abstract: We give a $\widetilde{O}(n)$ time sampler for independent sets of a matroid with $n$ elements. As an application, there is a near-linear time sampler for the all-terminal network reliability. | [] | Train |
21,121 | 27 | Title: Deep Reinforcement Learning for Concentric Tube Robot Path Following
Abstract: As surgical interventions trend towards minimally invasive approaches, Concentric Tube Robots (CTRs) have been explored for various interventions such as brain, eye, fetoscopic, lung, cardiac and prostate surgeries. Arranged concentri... | [] | Train |
21,122 | 23 | Title: PENTACET data - 23 Million Contextual Code Comments and 250,000 SATD comments
Abstract: Most Self-Admitted Technical Debt (SATD) research utilizes explicit SATD features such as ‘TODO’ and ‘FIXME’ for SATD detection. A closer look reveals several SATD research uses simple SATD (‘Easy to Find’) code comments with... | [] | Test |
21,123 | 24 | Title: Calibrating a Deep Neural Network with Its Predecessors
Abstract: Confidence calibration - the process to calibrate the output probability distribution of neural networks - is essential for safety-critical applications of such networks. Recent works verify the link between mis-calibration and overfitting. Howeve... | [] | Test |
21,124 | 16 | Title: Cross-Modal Video to Body-joints Augmentation for Rehabilitation Exercise Quality Assessment
Abstract: Exercise-based rehabilitation programs have been shown to enhance quality of life and reduce mortality and rehospitalizations. AI-driven virtual rehabilitation programs enable patients to complete exercises ind... | [
45269
] | Test |
21,125 | 16 | Title: RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths
Abstract: Text-to-image generation has recently witnessed remarkable achievements. We introduce a text-conditional image diffusion model, termed RAPHAEL, to generate highly artistic images, which accurately portray the text prompts, encompass... | [
15713,
2860,
8308,
46197,
28532,
15896,
34074,
10332
] | Train |
21,126 | 31 | Title: What's happening in your neighborhood? A Weakly Supervised Approach to Detect Local News
Abstract: Local news articles are a subset of news that impact users in a geographical area, such as a city, county, or state. Detecting local news (Step 1) and subsequently deciding its geographical location as well as radi... | [
28638
] | Train |
21,127 | 30 | Title: The Internal State of an LLM Knows When its Lying
Abstract: While Large Language Models (LLMs) have shown exceptional performance in various tasks, their (arguably) most prominent drawback is generating inaccurate or false information with a confident tone. In this paper, we hypothesize that the LLM's internal s... | [
28805,
13073,
21011,
44063,
3231,
9518,
28607,
46016,
10179,
13510,
11476,
35927,
12888,
38764,
13678,
43376,
37360,
42747,
13564
] | Train |
21,128 | 30 | Title: A Hybrid Architecture for Out of Domain Intent Detection and Intent Discovery
Abstract: Intent Detection is one of the tasks of the Natural Language Understanding (NLU) unit in task-oriented dialogue systems. Out of Scope (OOS) and Out of Domain (OOD) inputs may run these systems into a problem. On the other sid... | [
29393,
6524
] | Train |
21,129 | 10 | Title: Formally Explaining Neural Networks within Reactive Systems
Abstract: Deep neural networks (DNNs) are increasingly being used as controllers in reactive systems. However, DNNs are highly opaque, which renders it difficult to explain and justify their actions. To mitigate this issue, there has been a surge of int... | [
17698,
28934,
28518,
32332,
13786
] | Test |
21,130 | 28 | Title: Goal-oriented Tensor: Beyond Age of Information Towards Semantics-Empowered Goal-Oriented Communications
Abstract: Optimizations premised on open-loop metrics such as Age of Information (AoI) indirectly enhance the system's decision-making utility. We therefore propose a novel closed-loop metric named Goal-orien... | [
7008,
15176,
22443,
19179
] | Train |
21,131 | 16 | Title: Deep Convolutional Tables: Deep Learning without Convolutions
Abstract: We propose a novel formulation of deep networks that do not use dot-product neurons and rely on a hierarchy of voting tables instead, denoted as convolutional tables (CTs), to enable accelerated CPU-based inference. Convolutional layers are ... | [] | Train |
21,132 | 30 | Title: A Practical Toolkit for Multilingual Question and Answer Generation
Abstract: Generating questions along with associated answers from a text has applications in several domains, such as creating reading comprehension tests for students, or improving document search by providing auxiliary questions and answers ba... | [
35001
] | Train |
21,133 | 30 | Title: Towards Arabic Multimodal Dataset for Sentiment Analysis
Abstract: Multimodal Sentiment Analysis (MSA) has recently become a centric research direction for many real-world applications. This proliferation is due to the fact that opinions are central to almost all human activities and are key influencers of our b... | [] | Train |
21,134 | 24 | Title: Topological Deep Learning: A Review of an Emerging Paradigm
Abstract: Topological data analysis (TDA) provides insight into data shape. The summaries obtained by these methods are principled global descriptions of multi-dimensional data whilst exhibiting stable properties such as robustness to deformation and no... | [
38664,
28697
] | Train |
21,135 | 16 | Title: Deep Learning Technique for Human Parsing: A Survey and Outlook
Abstract: Human parsing aims to partition humans in image or video into multiple pixel-level semantic parts. In the last decade, it has gained significantly increased interest in the computer vision community and has been utilized in a broad range o... | [] | Test |
21,136 | 27 | Title: PIEKF-VIWO: Visual-Inertial-Wheel Odometry using Partial Invariant Extended Kalman Filter
Abstract: Invariant Extended Kalman Filter (IEKF) has been successfully applied in Visual-inertial Odometry (VIO) as an advanced achievement of Kalman filter, showing great potential in sensor fusion. In this paper, we prop... | [] | Train |
21,137 | 24 | Title: Understanding Generalization in the Interpolation Regime using the Rate Function
Abstract: In this paper, we present a novel characterization of the smoothness of a model based on basic principles of Large Deviation Theory. In contrast to prior work, where the smoothness of a model is normally characterized by a... | [] | Validation |
21,138 | 27 | Title: Deep Reinforcement Learning-Based Control for Stomach Coverage Scanning of Wireless Capsule Endoscopy
Abstract: Due to its non-invasive and painless characteristics, wireless capsule endoscopy has become the new gold standard for assessing gastrointestinal disorders. Omissions, however, could occur throughout th... | [
24429
] | Test |
21,139 | 24 | Title: Learning Controllable Adaptive Simulation for Multi-resolution Physics
Abstract: Simulating the time evolution of physical systems is pivotal in many scientific and engineering problems. An open challenge in simulating such systems is their multi-resolution dynamics: a small fraction of the system is extremely d... | [
32547,
32459,
34524,
38451
] | Train |
21,140 | 24 | Title: Beware of Instantaneous Dependence in Reinforcement Learning
Abstract: Playing an important role in Model-Based Reinforcement Learning (MBRL), environment models aim to predict future states based on the past. Existing works usually ignore instantaneous dependence in the state, that is, assuming that the future ... | [] | Train |
21,141 | 30 | Title: Presence of informal language, such as emoticons, hashtags, and slang, impact the performance of sentiment analysis models on social media text?
Abstract: This study aimed to investigate the influence of the presence of informal language, such as emoticons and slang, on the performance of sentiment analysis mode... | [] | Train |
21,142 | 6 | Title: Trust in Shared Automated Vehicles: Study on Two Mobility Platforms
Abstract: The ever-increasing adoption of shared transportation modalities across the United States has the potential to fundamentally change the preferences and usage of different mobilities. It also raises several challenges with respect to th... | [] | Train |
21,143 | 36 | Title: Incentives to Offer Algorithmic Recourse
Abstract: Due to the importance of artificial intelligence (AI) in a variety of high-stakes decisions, such as loan approval, job hiring, and criminal bail, researchers in Explainable AI (XAI) have developed algorithms to provide users with recourse for an unfavorable out... | [] | Test |
21,144 | 27 | Title: Actor-Critic Model Predictive Control
Abstract: An open research question in robotics is how to combine the benefits of model-free reinforcement learning (RL) - known for its strong task performance and flexibility in optimizing general reward formulations - with the robustness and online replanning capabilities... | [
38926
] | Train |
21,145 | 24 | Title: Federated Learning of Gboard Language Models with Differential Privacy
Abstract: We train and deploy language models (LMs) with federated learning (FL) and differential privacy (DP) in Google Keyboard (Gboard). The recent DP-Follow the Regularized Leader (DP-FTRL) algorithm is applied to achieve meaningfully for... | [
20449,
16739,
15495,
27407,
19953,
12468,
25716,
3254,
17240
] | Test |
21,146 | 24 | Title: Federated Learning in IoT: a Survey from a Resource-Constrained Perspective
Abstract: The IoT ecosystem is able to leverage vast amounts of data for intelligent decision-making. Federated Learning (FL), a decentralized machine learning technique, is widely used to collect and train machine learning models from a... | [
24442,
12686
] | Validation |
21,147 | 16 | Title: MALM: Mask Augmentation based Local Matching for Food-Recipe Retrieval
Abstract: Image-to-recipe retrieval is a challenging vision-to-language task of significant practical value. The main challenge of the task lies in the ultra-high redundancy in the long recipe and the large variation reflected in both food it... | [] | Train |
21,148 | 16 | Title: Incremental Dense Reconstruction From Monocular Video With Guided Sparse Feature Volume Fusion
Abstract: Incrementally recovering 3D dense structures from monocular videos is of paramount importance since it enables various robotics and AR applications. Feature volumes have recently been shown to enable efficien... | [] | Test |
21,149 | 28 | Title: Exact Performance Analysis of THz Link Under Transceiver Hardware Impairments
Abstract: Transceiver hardware impairment (THI) is inevitable for high-date rate terahertz (THz) communication. Existing statistical analysis either neglects THI’s effect or provides approximate results when analyzing the performance o... | [] | Train |
21,150 | 30 | Title: Prompt to be Consistent is Better than Self-Consistent? Few-Shot and Zero-Shot Fact Verification with Pre-trained Language Models
Abstract: Few-shot or zero-shot fact verification only relies on a few or no labeled training examples. In this paper, we propose a novel method called ProToCo, to \underline{Pro}mpt ... | [
13700
] | Train |
21,151 | 23 | Title: Mining the Characteristics of Jupyter Notebooks in Data Science Projects
Abstract: Nowadays, numerous industries have exceptional demand for skills in data science, such as data analysis, data mining, and machine learning. The computational notebook (e.g., Jupyter Notebook) is a well-known data science tool adop... | [
24487
] | Test |
21,152 | 24 | Title: Consistency Models
Abstract: Diffusion models have significantly advanced the fields of image, audio, and video generation, but they depend on an iterative sampling process that causes slow generation. To overcome this limitation, we propose consistency models, a new family of models that generate high quality s... | [
4738,
34819,
22921,
9484,
43407,
29456,
37008,
4754,
30229,
38936,
18343,
39340,
30643,
16820,
4791,
42551,
24763,
43836,
27197,
21697,
37697,
19652,
25299,
12889,
7514,
23524,
9317,
38374,
33638,
30312,
43881,
8308,
8564,
32120,
10492,
33150
] | Train |
21,153 | 15 | Title: LightRidge: An End-to-end Agile Design Framework for Diffractive Optical Neural Networks
Abstract: To lower the barrier to diffractive optical neural networks (DONNs) design, exploration, and deployment, we propose LightRidge, the first end-to-end optical ML compilation framework, which consists of (1) precise a... | [] | Train |
21,154 | 10 | Title: Transformer-Based Neural Marked Spatio Temporal Point Process Model for Football Match Events Analysis
Abstract: With recently available football match event data that record the details of football matches, analysts and researchers have a great opportunity to develop new performance metrics, gain insight, and e... | [
24385,
3907
] | Train |
21,155 | 16 | Title: DMKD: Improving Feature-based Knowledge Distillation for Object Detection Via Dual Masking Augmentation
Abstract: Recent mainstream masked distillation methods function by reconstructing selectively masked areas of a student network from the feature map of its teacher counterpart. In these methods, the masked re... | [
41596
] | Validation |
21,156 | 27 | Title: Soft Gripping: Specifying for Trustworthiness
Abstract: Soft robotics is an emerging technology in which engineers create flexible devices for use in a variety of applications. In order to advance the wide adoption of soft robots, ensuring their trustworthiness is essential; if soft robots are not trusted, they ... | [] | Train |
21,157 | 24 | Title: Integer or Floating Point? New Outlooks for Low-Bit Quantization on Large Language Models
Abstract: Efficient deployment of large language models (LLMs) necessitates low-bit quantization to minimize model size and inference cost. While low-bit integer formats (e.g., INT8/INT4) have been the conventional choice, ... | [
44402,
6979,
13700
] | Train |
21,158 | 27 | Title: Robot Navigation in Risky, Crowded Environments: Understanding Human Preferences
Abstract: The effective deployment of robots in risky and crowded environments (RCE) requires the specification of robot plans that are consistent with humans' behaviors. As is well known, humans perceive uncertainty and risk in a b... | [] | Validation |
21,159 | 16 | Title: Interleaving GANs with knowledge graphs to support design creativity for book covers
Abstract: An attractive book cover is important for the success of a book. In this paper, we apply Generative Adversarial Networks (GANs) to the book covers domain, using different methods for training in order to obtain better ... | [] | Test |
21,160 | 34 | Title: An improved kernelization algorithm for Trivially Perfect Editing
Abstract: In the Trivially Perfect Editing problem one is given an undirected graph $G = (V,E)$ and an integer $k$ and seeks to add or delete at most $k$ edges in $G$ to obtain a trivially perfect graph. In a recent work, Dumas, Perez and Todinca ... | [] | Train |
21,161 | 30 | Title: Neural Machine Translation for the Indigenous Languages of the Americas: An Introduction
Abstract: Neural models have drastically advanced state of the art for machine translation (MT) between high-resource languages. Traditionally, these models rely on large amounts of training data, but many language pairs lac... | [
34202,
30532
] | Train |
21,162 | 30 | Title: All Roads Lead to Rome? Exploring the Invariance of Transformers' Representations
Abstract: Transformer models bring propelling advances in various NLP tasks, thus inducing lots of interpretability research on the learned representations of the models. However, we raise a fundamental question regarding the relia... | [
33220
] | Test |
21,163 | 10 | Title: Egocentric Hierarchical Visual Semantics
Abstract: We are interested in aligning how people think about objects and what machines perceive, meaning by this the fact that object recognition, as performed by a machine, should follow a process which resembles that followed by humans when thinking of an object assoc... | [
12633
] | Train |
21,164 | 16 | Title: Artificial-Spiking Hierarchical Networks for Vision-Language Representation Learning
Abstract: With the success of self-supervised learning, multimodal foundation models have rapidly adapted a wide range of downstream tasks driven by vision and language (VL) pretraining. State-of-the-art methods achieve impressi... | [] | Train |
21,165 | 16 | Title: Fine-grained Affordance Annotation for Egocentric Hand-Object Interaction Videos
Abstract: Object affordance is an important concept in hand-object interaction, providing information on action possibilities based on human motor capacity and objects’ physical property thus benefiting tasks such as action anticipa... | [
29427
] | Validation |
21,166 | 30 | Title: An Information-Theoretic Analysis of Self-supervised Discrete Representations of Speech
Abstract: Self-supervised representation learning for speech often involves a quantization step that transforms the acoustic input into discrete units. However, it remains unclear how to characterize the relationship between ... | [
20220
] | Train |
21,167 | 3 | Title: Improving International Climate Policy via Mutually Conditional Binding Commitments
Abstract: This paper proposes enhancements to the RICE-N simulation and multi-agent reinforcement learning framework to improve the realism of international climate policy negotiations. Acknowledging the framework's value, we hig... | [] | Train |
21,168 | 25 | Title: Bridging High-Quality Audio and Video Via Language for Sound Effects Retrieval from Visual Queries
Abstract: Finding the right sound effects (SFX) to match moments in a video is a difficult and time-consuming task, and relies heavily on the quality and completeness of text metadata. Retrieving high-quality (HQ) ... | [
21695
] | Test |
21,169 | 27 | Title: Multi-robot Path Planning with Rapidly-exploring Random Disjointed-Trees
Abstract: Multi-robot path planning is a computational process involving finding paths for each robot from its start to the goal while ensuring collision-free operation. It is widely used in robots and autonomous driving. However, the compu... | [
2863
] | Test |
21,170 | 16 | Title: MARS: An Instance-aware, Modular and Realistic Simulator for Autonomous Driving
Abstract: Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely recognized that realistic sensor simulation will play a critical role in solving remaining corner cases by simulating them. To this end, we pr... | [
34017,
19781,
43720,
13387,
9515,
21771,
16079,
2865,
21846
] | Test |
21,171 | 16 | Title: SLSG: Industrial Image Anomaly Detection by Learning Better Feature Embeddings and One-Class Classification
Abstract: Industrial image anomaly detection under the setting of one-class classification has significant practical value. However, most existing models struggle to extract separable feature representatio... | [] | Validation |
21,172 | 27 | Title: PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas
Abstract: Recent research has demonstrated the potential of reinforcement learning (RL) in enabling effective multi-robot collaboration, particularly in social dilemmas where robots face a trade-off between self-i... | [
22122,
34731
] | Train |
21,173 | 16 | Title: R2-Diff: Denoising by diffusion as a refinement of retrieved motion for image-based motion prediction
Abstract: Image-based motion prediction is one of the essential techniques for robot manipulation. Among the various prediction models, we focus on diffusion models because they have achieved state-of-the-art pe... | [
14136,
8994,
20299
] | Validation |
21,174 | 29 | Title: Splitter Orderings for Probabilistic Bisimulation
Abstract: Model checking has been proposed as a formal verification approach for analyzing computer-based and cyber-physical systems. The state space explosion problem is the main obstacle for applying this approach for sophisticated systems. Bisimulation minimiz... | [
25296
] | Train |
21,175 | 10 | Title: Pure Monte Carlo Counterfactual Regret Minimization
Abstract: Counterfactual Regret Minimization (CFR) and its variants are the best algorithms so far for solving large-scale incomplete information games. Building upon CFR, this paper proposes a new algorithm named Pure CFR (PCFR) for achieving better performanc... | [
22375
] | Validation |
21,176 | 16 | Title: MetaCAM: Ensemble-Based Class Activation Map
Abstract: The need for clear, trustworthy explanations of deep learning model predictions is essential for high-criticality fields, such as medicine and biometric identification. Class Activation Maps (CAMs) are an increasingly popular category of visual explanation m... | [] | Train |
21,177 | 4 | Title: Random (Un)rounding : Vulnerabilities in Discrete Attribute Disclosure in the 2021 Canadian Census
Abstract: The 2021 Canadian census is notable for using a unique form of privacy, random rounding, which independently and probabilistically rounds discrete numerical attribute values. In this work, we explore how ... | [] | Test |
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