node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
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|---|---|---|---|---|
27,178 | 16 | Title: Tackling Face Verification Edge Cases: In-Depth Analysis and Human-Machine Fusion Approach
Abstract: Nowadays, face recognition systems surpass human performance on several datasets. However, there are still edge cases that the machine can’t correctly classify. This paper investigates the effect of a combination... | [] | Train |
27,179 | 36 | Title: Multi-unit Auction over a Social Network
Abstract: Diffusion auction is an emerging business model where a seller aims to incentivise buyers in a social network to diffuse the auction information thereby attracting potential buyers. We focus on designing mechanisms for multi-unit diffusion auctions. Despite seve... | [] | Validation |
27,180 | 24 | Title: Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length
Abstract: Multivariate Hawkes processes (MHPs) are versatile probabilistic tools used to model various real-life phenomena: earthquakes, operations on stock markets, neuronal activity, virus propagation and many others. In this p... | [] | Train |
27,181 | 16 | Title: Patterns of Vehicle Lights: Addressing Complexities in Curation and Annotation of Camera-Based Vehicle Light Datasets and Metrics
Abstract: This paper explores the representation of vehicle lights in computer vision and its implications for various tasks in the field of autonomous driving. Different specificatio... | [
5336
] | Test |
27,182 | 10 | Title: Teacher-Student Knowledge Distillation for Radar Perception on Embedded Accelerators
Abstract: Many radar signal processing methodologies are being developed for critical road safety perception tasks. Unfortunately, these signal processing algorithms are often poorly suited to run on embedded hardware accelerato... | [] | Train |
27,183 | 23 | Title: Provengo: A Tool Suite for Scenario Driven Model-Based Testing
Abstract: We present Provengo, a comprehensive suite of tools designed to facilitate the implementation of Scenario-Driven Model-Based Testing (SDMBT), an innovative approach that utilizes scenarios to construct a model encompassing the user's perspe... | [] | Train |
27,184 | 16 | Title: Unified Multi-Modal Latent Diffusion for Joint Subject and Text Conditional Image Generation
Abstract: Language-guided image generation has achieved great success nowadays by using diffusion models. However, texts can be less detailed to describe highly-specific subjects such as a particular dog or a certain car... | [
4545,
37126,
42695,
36265,
7597,
16846,
20687,
33621,
3031,
30936,
39324,
18205
] | Train |
27,185 | 3 | Title: Learning gain differences between ChatGPT and human tutor generated algebra hints
Abstract: Large Language Models (LLMs), such as ChatGPT, are quickly advancing AI to the frontiers of practical consumer use and leading industries to re-evaluate how they allocate resources for content production. Authoring of ope... | [
10624,
40036,
34916,
13254,
24552,
11273,
18250,
30026,
21487,
11476,
20185
] | Train |
27,186 | 10 | Title: International Governance of Civilian AI: A Jurisdictional Certification Approach
Abstract: This report describes trade-offs in the design of international governance arrangements for civilian artificial intelligence (AI) and presents one approach in detail. This approach represents the extension of a standards, ... | [
38338,
10660,
33220,
7015,
9262,
5071,
39322,
18065,
40953,
32410,
1917
] | Test |
27,187 | 30 | Title: UOR: Universal Backdoor Attacks on Pre-trained Language Models
Abstract: Backdoors implanted in pre-trained language models (PLMs) can be transferred to various downstream tasks, which exposes a severe security threat. However, most existing backdoor attacks against PLMs are un-targeted and task-specific. Few ta... | [
7739,
34076,
10749
] | Test |
27,188 | 27 | Title: Towards Modeling and Influencing the Dynamics of Human Learning
Abstract: Humans have internal models of robots (like their physical capabilities), the world (like what will happen next), and their tasks (like a preferred goal). However, human internal models are not always perfect: for example, it is easy to un... | [
28802,
45923,
14141
] | Train |
27,189 | 16 | Title: IBAFormer: Intra-batch Attention Transformer for Domain Generalized Semantic Segmentation
Abstract: Domain generalized semantic segmentation (DGSS) is a critical yet challenging task, where the model is trained only on source data without access to any target data. Despite the proposal of numerous DGSS strategie... | [
41773,
5878
] | Train |
27,190 | 24 | Title: Provable Benefit of Mixup for Finding Optimal Decision Boundaries
Abstract: We investigate how pair-wise data augmentation techniques like Mixup affect the sample complexity of finding optimal decision boundaries in a binary linear classification problem. For a family of data distributions with a separability co... | [] | Test |
27,191 | 4 | Title: Security Threat Mitigation for Smart Contracts: A Comprehensive Survey
Abstract: The blockchain technology, initially created for cryptocurrency, has been re-purposed for recording state transitions of smart contracts—decentralized applications that can be invoked through external transactions. Smart contracts g... | [
26959
] | Train |
27,192 | 16 | Title: Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection
Abstract: Camouflaged objects that blend into natural scenes pose significant challenges for deep-learning models to detect and synthesize. While camouflaged object detection is a crucial task in computer vision with diverse real-world ap... | [] | Train |
27,193 | 2 | Title: SCL(FOL) Revisited
Abstract: This paper presents an up-to-date and refined version of the SCL calculus for first-order logic without equality. The refinement mainly consists of the following two parts: First, we incorporate a stronger notion of regularity into SCL(FOL). Our regularity definition is adapted from ... | [
24190
] | Train |
27,194 | 24 | Title: FedMEKT: Distillation-based Embedding Knowledge Transfer for Multimodal Federated Learning
Abstract: Federated learning (FL) enables a decentralized machine learning paradigm for multiple clients to collaboratively train a generalized global model without sharing their private data. Most existing works simply pr... | [
21857
] | Test |
27,195 | 13 | Title: Training Full Spike Neural Networks via Auxiliary Accumulation Pathway
Abstract: Due to the binary spike signals making converting the traditional high-power multiply-accumulation (MAC) into a low-power accumulation (AC) available, the brain-inspired Spiking Neural Networks (SNNs) are gaining more and more atten... | [
39185,
45557,
18150
] | Train |
27,196 | 34 | Title: Automated Tail Bound Analysis for Probabilistic Recurrence Relations
Abstract: Probabilistic recurrence relations (PRRs) are a standard formalism for describing the runtime of a randomized algorithm. Given a PRR and a time limit $\kappa$, we consider the classical concept of tail probability $\Pr[T \ge \kappa]$,... | [] | Train |
27,197 | 16 | Title: Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
Abstract: Diffusion models have recently emerged as powerful generative priors for solving inverse problems. However, training diffusion models in the pixel space are both data intensive and computationally demanding, which restricts... | [
21152,
46135,
24494,
20759
] | Train |
27,198 | 24 | Title: M22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion
Abstract: In federated learning (FL), the communication constraint between the remote learners and the Parameter Server (PS) is a crucial bottleneck. For this reason, model updates must be compressed so as to minimize the... | [] | Train |
27,199 | 24 | Title: Multimodal Temporal Fusion Transformers Are Good Product Demand Forecasters
Abstract: Multimodal demand forecasting aims at predicting product demand utilizing visual, textual, and contextual information. This paper proposes a method for multimodal product demand forecasting using convolutional, graph-based, and... | [] | Validation |
27,200 | 16 | Title: AAN: Attributes-Aware Network for Temporal Action Detection
Abstract: The challenge of long-term video understanding remains constrained by the efficient extraction of object semantics and the modelling of their relationships for downstream tasks. Although the CLIP visual features exhibit discriminative properti... | [] | Test |
27,201 | 30 | Title: Learning to Imagine: Visually-Augmented Natural Language Generation
Abstract: People often imagine relevant scenes to aid in the writing process. In this work, we aim to utilize visual information for composition in the same manner as humans. We propose a method, LIVE, that makes pre-trained language models (PLM... | [
40192
] | Train |
27,202 | 27 | Title: Embedded light-weight approach for safe landing in populated areas
Abstract: Landing safety is a challenge heavily engaging the research community recently, due to the increasing interest in applications availed by aerial vehicles. In this paper, we propose a landing safety pipeline based on state of the art obj... | [] | Train |
27,203 | 16 | Title: Computational Long Exposure Mobile Photography
Abstract: Long exposure photography produces stunning imagery, representing moving elements in a scene with motion-blur. It is generally employed in two modalities, producing either a foreground or a background blur effect. Foreground blur images are traditionally c... | [] | Test |
27,204 | 32 | Title: An Incremental Singular Value Decomposition Approach for Large-Scale Spatially Parallel & Distributed but Temporally Serial Data - Applied to Technical Flows
Abstract: The paper presents a strategy to construct an incremental Singular Value Decomposition (SVD) for time-evolving, spatially 3D discrete data sets. ... | [] | Validation |
27,205 | 6 | Title: Learnersourcing in the Age of AI: Student, Educator and Machine Partnerships for Content Creation
Abstract: nan | [
36778,
3314,
18547,
37450
] | Validation |
27,206 | 30 | Title: Incorporating Human Translator Style into English-Turkish Literary Machine Translation
Abstract: Although machine translation systems are mostly designed to serve in the general domain, there is a growing tendency to adapt these systems to other domains like literary translation. In this paper, we focus on Engli... | [] | Validation |
27,207 | 36 | Title: Single Sample Prophet Inequality for Uniform Matroids of Rank 2
Abstract: We study the prophet inequality when the gambler has an access only to a single sample from each distribution. Rubinstein, Wang and Weinberg showed that an optimal guarantee of 1/2 can be achieved when the underlying matroid has rank 1, i.... | [
8788
] | Validation |
27,208 | 30 | Title: Bipol: Multi-axes Evaluation of Bias with Explainability in Benchmark Datasets
Abstract: We investigate five English NLP benchmark datasets (on the superGLUE leaderboard) and two Swedish datasets for bias, along multiple axes. The datasets are the following: Boolean Question (Boolq), CommitmentBank (CB), Winogra... | [
26797
] | Train |
27,209 | 16 | Title: Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning
Abstract: Few-shot class-incremental learning (FSCIL) has been a challenging problem as only a few training samples are accessible for each novel class in the new sessions. Finetuning the backbone or adjusting the class... | [
20738,
31523,
41381,
39380,
42869,
22614,
14618,
19259,
42878,
10495
] | Train |
27,210 | 24 | Title: Recursive Algorithmic Reasoning
Abstract: Learning models that execute algorithms can enable us to address a key problem in deep learning: generalizing to out-of-distribution data. However, neural networks are currently unable to execute recursive algorithms because they do not have arbitrarily large memory to s... | [
37532,
41734
] | Test |
27,211 | 16 | Title: DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV Perception
Abstract: Closing the domain gap between training and deployment and incorporating multiple sensor modalities are two challenging yet critical topics for self-driving. Existing work only focuses on single one of the above topics, over... | [] | Train |
27,212 | 30 | Title: Efficiently Measuring the Cognitive Ability of LLMs: An Adaptive Testing Perspective
Abstract: Large language models (LLMs), like ChatGPT, have shown some human-like cognitive abilities. For comparing these abilities of different models, several benchmarks (i.e. sets of standard test questions) from different fi... | [
12128,
4996,
965,
1575,
8942,
36751,
12602
] | Test |
27,213 | 30 | Title: Trading Syntax Trees for Wordpieces: Target-oriented Opinion Words Extraction with Wordpieces and Aspect Enhancement
Abstract: State-of-the-art target-oriented opinion word extraction (TOWE) models typically use BERT-based text encoders that operate on the word level, along with graph convolutional networks (GCN... | [
8727
] | Train |
27,214 | 16 | Title: Design and Implementation of A Soccer Ball Detection System with Multiple Cameras
Abstract: The detection of small and medium-sized objects in three dimensions has always been a frontier exploration problem. This technology has a very wide application in sports analysis, games, virtual reality, human animation a... | [] | Train |
27,215 | 16 | Title: CLIP Multi-modal Hashing: A new baseline CLIPMH
Abstract: The multi-modal hashing method is widely used in multimedia retrieval. It can fuse multi-source data to generate binary hash code. However, the current multi-modal methods have the problem of low retrieval accuracy. The reason is that the individual backb... | [
5082
] | Train |
27,216 | 10 | Title: Machine Learning for SAT: Restricted Heuristics and New Graph Representations
Abstract: Boolean satisfiability (SAT) is a fundamental NP-complete problem with many applications, including automated planning and scheduling. To solve large instances, SAT solvers have to rely on heuristics, e.g., choosing a branchi... | [] | Train |
27,217 | 5 | Title: The best multicore-parallelization refactoring you've never heard of
Abstract: In this short paper, we explore a new way to refactor a simple but tricky-to-parallelize tree-traversal algorithm to harness multicore parallelism. Crucially, the refactoring draws from some classic techniques from programming-languag... | [] | Train |
27,218 | 24 | Title: Automated Polynomial Filter Learning for Graph Neural Networks
Abstract: Polynomial graph filters have been widely used as guiding principles in the design of Graph Neural Networks (GNNs). Recently, the adaptive learning of the polynomial graph filters has demonstrated promising performance for modeling graph si... | [] | Test |
27,219 | 27 | Title: RadarLCD: Learnable Radar-based Loop Closure Detection Pipeline
Abstract: Loop Closure Detection (LCD) is an essential task in robotics and computer vision, serving as a fundamental component for various applications across diverse domains. These applications encompass object recognition, image retrieval, and vi... | [
45944
] | Train |
27,220 | 23 | Title: Applying Machine Learning Analysis for Software Quality Test
Abstract: One of the biggest expense in software development is the maintenance. Therefore, it's critical to comprehend what triggers maintenance and if it may be predicted. Numerous research outputs have demonstrated that specific methods of assessing... | [
17083
] | Train |
27,221 | 25 | Title: Single Channel Speech Enhancement Using U-Net Spiking Neural Networks
Abstract: Speech enhancement (SE) is crucial for reliable communication devices or robust speech recognition systems. Although conventional artificial neural networks (ANN) have demonstrated remarkable performance in SE, they require significa... | [
17211,
28215
] | Validation |
27,222 | 8 | Title: Artificial intelligence based load balancing in SDN: A comprehensive survey
Abstract: nan | [] | Validation |
27,223 | 16 | Title: Triple-stream Deep Metric Learning of Great Ape Behavioural Actions
Abstract: We propose the first metric learning system for the recognition of great ape behavioural actions. Our proposed triple stream embedding architecture works on camera trap videos taken directly in the wild and demonstrates that the utilis... | [
30241,
1165
] | Train |
27,224 | 24 | Title: Deep projection networks for learning time-homogeneous dynamical systems
Abstract: We consider the general class of time-homogeneous dynamical systems, both discrete and continuous, and study the problem of learning a meaningful representation of the state from observed data. This is instrumental for the task of... | [] | Test |
27,225 | 30 | Title: Non-Autoregressive Math Word Problem Solver with Unified Tree Structure
Abstract: Existing MWP solvers employ sequence or binary tree to present the solution expression and decode it from given problem description. However, such structures fail to handle the identical variants derived via mathematical manipulati... | [] | Train |
27,226 | 16 | Title: Localisation of Mammographic masses by Greedy Backtracking of Activations in the Stacked Auto-Encoders
Abstract: Mammographic image analysis requires accurate localisation of salient mammographic masses. In mammographic computer-aided diagnosis, mass or Region of Interest (ROI) is often marked by physicians and ... | [] | Train |
27,227 | 24 | Title: Guiding Energy-based Models via Contrastive Latent Variables
Abstract: An energy-based model (EBM) is a popular generative framework that offers both explicit density and architectural flexibility, but training them is difficult since it is often unstable and time-consuming. In recent years, various training tec... | [] | Train |
27,228 | 30 | Title: Can AI Chatbots Pass the Fundamentals of Engineering (FE) and Principles and Practice of Engineering (PE) Structural Exams?
Abstract: The engineering community has recently witnessed the emergence of chatbot technology with the release of OpenAI ChatGPT-4 and Google Bard. While these chatbots have been reported ... | [] | Train |
27,229 | 30 | Title: Accurate Knowledge Distillation with n-best Reranking
Abstract: We propose extending the Sequence-level Knowledge Distillation (Kim and Rush, 2016) with n-best reranking to consider not only the top-1 hypotheses but also the top n-best hypotheses of teacher models. Our approach leverages a diverse set of models,... | [] | Validation |
27,230 | 16 | Title: Advancing Referring Expression Segmentation Beyond Single Image
Abstract: Referring Expression Segmentation (RES) is a widely explored multi-modal task, which endeavors to segment the pre-existing object within a single image with a given linguistic expression. However, in broader real-world scenarios, it is not... | [
27860,
34943
] | Train |
27,231 | 16 | Title: Learning Cross-modality Information Bottleneck Representation for Heterogeneous Person Re-Identification
Abstract: Visible-Infrared person re-identification (VI-ReID) is an important and challenging task in intelligent video surveillance. Existing methods mainly focus on learning a shared feature space to reduce... | [] | Test |
27,232 | 10 | Title: A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?
Abstract: As ChatGPT goes viral, generative AI (AIGC, a.k.a AI-generated content) has made headlines everywhere because of its ability to analyze and create text, images, and beyond. With such overwhelming media coverage, it ... | [
8577,
15618,
20993,
28932,
18705,
41491,
25368,
28570,
42267,
6942,
39340,
9775,
38575,
42032,
1337,
35263,
17349,
3782,
12487,
26825,
5584,
11476,
24149,
16728,
12888,
27480,
37211,
45659,
32352,
24549,
37225,
5499,
21375
] | Train |
27,233 | 31 | Title: Explain Like I am BM25: Interpreting a Dense Model's Ranked-List with a Sparse Approximation
Abstract: Neural retrieval models (NRMs) have been shown to outperform their statistical counterparts owing to their ability to capture semantic meaning via dense document representations. These models, however, suffer f... | [
34563
] | Train |
27,234 | 31 | Title: Invariant Collaborative Filtering to Popularity Distribution Shift
Abstract: Collaborative Filtering (CF) models, despite their great success, suffer from severe performance drops due to popularity distribution shifts, where these changes are ubiquitous and inevitable in real-world scenarios. Unfortunately, most... | [
1765
] | Validation |
27,235 | 10 | Title: The Case Against Explainability
Abstract: As artificial intelligence (AI) becomes more prevalent there is a growing demand from regulators to accompany decisions made by such systems with explanations. However, a persistent gap exists between the need to execute a meaningful right to explanation vs. the ability ... | [
20794,
13510
] | Validation |
27,236 | 24 | Title: PPG-based Heart Rate Estimation with Efficient Sensor Sampling and Learning Models
Abstract: Recent studies showed that Photoplethysmography (PPG) sensors embedded in wearable devices can estimate heart rate (HR) with high accuracy. However, despite of prior research efforts, applying PPG sensor based HR estimat... | [
38076
] | Train |
27,237 | 16 | Title: Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation
Abstract: The ability to deploy robots that can operate safely in diverse environments is crucial for developing embodied intelligent agents. As a community, we have made tremendous progress in within-domain LiDAR semantic seg... | [
28173
] | Train |
27,238 | 30 | Title: Can LLMs facilitate interpretation of pre-trained language models?
Abstract: Work done to uncover the knowledge encoded within pre-trained language models, rely on annotated corpora or human-in-the-loop methods. However, these approaches are limited in terms of scalability and the scope of interpretation. We pro... | [
39642,
43930
] | Train |
27,239 | 10 | Title: Optimizing Group Utility in Itinerary Planning: A Strategic and Crowd-Aware Approach
Abstract: Itinerary recommendation is a complex sequence prediction problem with numerous real-world applications. This task becomes even more challenging when considering the optimization of multiple user queuing times and crow... | [] | Train |
27,240 | 28 | Title: Robust Indexing for the Sliced Channel: Almost Optimal Codes for Substitutions and Deletions
Abstract: Encoding data as a set of unordered strings is receiving great attention as it captures one of the basic features of DNA storage systems. However, the challenge of constructing optimal redundancy codes for this... | [] | Validation |
27,241 | 30 | Title: Alloprof: a new French question-answer education dataset and its use in an information retrieval case study
Abstract: Teachers and students are increasingly relying on online learning resources to supplement the ones provided in school. This increase in the breadth and depth of available resources is a great thi... | [] | Train |
27,242 | 16 | Title: Uni-Removal: A Semi-Supervised Framework for Simultaneously Addressing Multiple Degradations in Real-World Images
Abstract: Removing multiple degradations, such as haze, rain, and blur, from real-world images poses a challenging and illposed problem. Recently, unified models that can handle different degradation... | [] | Test |
27,243 | 24 | Title: Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents
Abstract: The optimized certainty equivalent (OCE) is a family of risk measures that cover important examples such as entropic risk, conditional value-at-risk and mean-variance models. In this paper, we propose a new episo... | [
22384,
12159
] | Test |
27,244 | 24 | Title: Offline Learning of Closed-Loop Deep Brain Stimulation Controllers for Parkinson Disease Treatment
Abstract: Deep brain stimulation (DBS) has shown great promise toward treating motor symptoms caused by Parkinson's disease (PD), by delivering electrical pulses to the Basal Ganglia (BG) region of the brain. Howev... | [
34452,
7543
] | Train |
27,245 | 24 | Title: Finding the right XAI method - A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science
Abstract: Explainable artificial intelligence (XAI) methods shed light on the predictions of deep neural networks (DNNs). Several different approaches exist and have partly already been successfully... | [
30962,
40271
] | Train |
27,246 | 23 | Title: Can a Chatbot Support Exploratory Software Testing? Preliminary Results
Abstract: Tests executed by human testers are still widespread in practice and fill the gap left by limitations of automated approaches. Among the human-centered approaches, exploratory testing is the de facto approach in agile teams. Althou... | [] | Train |
27,247 | 16 | Title: Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection
Abstract: Unsupervised domain adaptation (UDA) plays a crucial role in object detection when adapting a source-trained detector to a target domain without annotated data. In this paper, we propose a novel and e... | [
15696
] | Train |
27,248 | 30 | Title: Aligning Large Language Models through Synthetic Feedback
Abstract: Aligning large language models (LLMs) to human values has become increasingly important as it enables sophisticated steering of LLMs, e.g., making them follow given instructions while keeping them less toxic. However, it requires a significant a... | [
13345,
45923,
40330,
25772,
4111,
14609,
4658,
10163,
9012,
17076,
26673,
36179,
29375
] | Train |
27,249 | 6 | Title: Automated Conversion of Music Videos into Lyric Videos
Abstract: Musicians and fans often produce lyric videos, a form of music videos that showcase the song's lyrics, for their favorite songs. However, making such videos can be challenging and time-consuming as the lyrics need to be added in synchrony and visua... | [] | Train |
27,250 | 10 | Title: Defining and Explorting the Intelligence Space
Abstract: Intelligence is a difficult concept to define, despite many attempts at doing so. Rather than trying to settle on a single definition, this article introduces a broad perspective on what intelligence is, by laying out a cascade of definitions that induces ... | [
16556,
13510
] | Train |
27,251 | 16 | Title: Neural Preset for Color Style Transfer
Abstract: In this paper, we present a Neural Preset technique to address the limitations of existing color style transfer methods, including visual artifacts, vast memory requirement, and slow style switching speed. Our method is based on two core designs. First, we propose... | [
10170
] | Test |
27,252 | 16 | Title: SEPAL: Spatial Gene Expression Prediction from Local Graphs
Abstract: Spatial transcriptomics is an emerging technology that aligns histopathology images with spatially resolved gene expression profiling. It holds the potential for understanding many diseases but faces significant bottlenecks such as specialized... | [] | Train |
27,253 | 10 | Title: Faster Approximate Dynamic Programming by Freezing Slow States
Abstract: We consider infinite horizon Markov decision processes (MDPs) with fast-slow structure, meaning that certain parts of the state space move “fast” (and in a sense, are more influential) while other parts transition more “slowly.” Such struct... | [] | Validation |
27,254 | 30 | Title: An Empirical Study and Improvement for Speech Emotion Recognition
Abstract: Multimodal speech emotion recognition aims to detect speakers' emotions from audio and text. Prior works mainly focus on exploiting advanced networks to model and fuse different modality information to facilitate performance, while negle... | [] | Train |
27,255 | 16 | Title: TEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis
Abstract: The gradual nature of a diffusion process that synthesizes samples in small increments constitutes a key ingredient of Denoising Diffusion Probabilistic Models (DDPM), which have presented unprecedented quality in image synthesis and b... | [
38181,
15030
] | Train |
27,256 | 24 | Title: Discovering Graph Generation Algorithms
Abstract: We provide a novel approach to construct generative models for graphs. Instead of using the traditional probabilistic models or deep generative models, we propose to instead find an algorithm that generates the data. We achieve this using evolutionary search and ... | [] | Test |
27,257 | 24 | Title: Diffusion Models for Time Series Applications: A Survey
Abstract: Diffusion models, a family of generative models based on deep learning, have become increasingly prominent in cutting-edge machine learning research. With a distinguished performance in generating samples that resemble the observed data, diffusion... | [
1603,
20004,
45828,
42339,
34247,
15529,
42957,
17941
] | Test |
27,258 | 28 | Title: Joint User Scheduling and Precoding for XL-MIMO Systems with Imperfect CSI
Abstract: We propose an algorithm for joint precoding and user selection in multiple-input multiple-output systems with extremely-large aperture arrays, assuming realistic channel conditions and imperfect channel estimates. The use of lon... | [] | Test |
27,259 | 23 | Title: Excel as a Turing-complete Functional Programming Environment
Abstract: Since the calculation engine of Excel was the subject of a major upgrade to accommodate Dynamic Arrays in 2018 there has been a series of seismic changes to the art of building spreadsheet solutions. This paper will show the ad-hoc end user ... | [] | Train |
27,260 | 23 | Title: Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing
Abstract: Machine learning (ML) systems have achieved remarkable performance across a wide area of applications. However, they frequently exhibit unfair behaviors in sensitive application domains (e.g., employm... | [
34712,
44201,
1879
] | Test |
27,261 | 27 | Title: Rapid grasping of fabric using bionic soft grippers with elastic instability
Abstract: Abstract — Robot grasping is subject to an inherent tradeoff: Grippers with a large span typically take a longer time to close, and fast grippers usually cover a small span. However, many practical applications of soft gripp... | [] | Test |
27,262 | 8 | Title: Deterministic End-to-End Transmission to Optimize the Network Efficiency and Quality of Service: A Paradigm Shift in 6G
Abstract: Toward end-to-end mobile service provision with optimized network efficiency and quality of service, tremendous efforts have been devoted in upgrading mobile applications, transport a... | [] | Train |
27,263 | 16 | Title: BoPR: Body-aware Part Regressor for Human Shape and Pose Estimation
Abstract: This paper presents a novel approach for estimating human body shape and pose from monocular images that effectively addresses the challenges of occlusions and depth ambiguity. Our proposed method BoPR, the Body-aware Part Regressor, f... | [] | Train |
27,264 | 16 | Title: Instant Continual Learning of Neural Radiance Fields
Abstract: Neural radiance fields (NeRFs) have emerged as an effective method for novel-view synthesis and 3D scene reconstruction. However, conventional training methods require access to all training views during scene optimization. This assumption may be pro... | [
19781
] | Train |
27,265 | 24 | Title: Diverse Offline Imitation via Fenchel Duality
Abstract: There has been significant recent progress in the area of unsupervised skill discovery, with various works proposing mutual information based objectives, as a source of intrinsic motivation. Prior works predominantly focused on designing algorithms that req... | [
8230,
1694
] | Train |
27,266 | 39 | Title: Shortest Path with Positive Disjunctive Constraints - a Parameterized Perspective
Abstract: We study the SHORTEST PATH problem with positive disjunctive constraints from the perspective of parameterized complexity. For positive disjunctive constraints, there are certain pair of edges such that any feasible solut... | [] | Train |
27,267 | 16 | Title: PathLDM: Text conditioned Latent Diffusion Model for Histopathology
Abstract: To achieve high-quality results, diffusion models must be trained on large datasets. This can be notably prohibitive for models in specialized domains, such as computational pathology. Conditioning on labeled data is known to help in d... | [
43641,
27305,
5852
] | Train |
27,268 | 24 | Title: Graphtester: Exploring Theoretical Boundaries of GNNs on Graph Datasets
Abstract: Graph Neural Networks (GNNs) have emerged as a powerful tool for learning from graph-structured data. However, even state-of-the-art architectures have limitations on what structures they can distinguish, imposing theoretical limit... | [
44836
] | Test |
27,269 | 24 | Title: Distribution Grid Line Outage Identification with Unknown Pattern and Performance Guarantee
Abstract: Line outage identification in distribution grids is essential for sustainable grid operation. In this work, we propose a practical yet robust detection approach that utilizes only readily available voltage magni... | [] | Train |
27,270 | 16 | Title: FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow
Abstract: This paper introduces a novel transformer-based network architecture, FlowFormer, along with the Masked Cost Volume AutoEncoding (MCVA) for pretraining it to tackle the problem of optical flow estimation. Fl... | [] | Test |
27,271 | 30 | Title: Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference
Abstract: Large Language Models (LLMs) have sparked significant interest in their generative capabilities, leading to the development of various commercial applications. The high cost of using the models drives application b... | [
24440,
33220,
3804,
24238
] | Test |
27,272 | 10 | Title: Cybernetic Environment: A Historical Reflection on System, Design, and Machine Intelligence
Abstract: Taking on a historical lens, this paper traces the development of cybernetics and systems thinking back to the 1950s, when a group of interdisciplinary scholars converged to create a new theoretical model based ... | [
39686
] | Train |
27,273 | 16 | Title: Open Set Action Recognition via Multi-Label Evidential Learning
Abstract: Existing methods for open set action recognition focus on novelty detection that assumes video clips show a single action, which is unrealistic in the real world. We propose a new method for open set action recognition and novelty detectio... | [
19710
] | Test |
27,274 | 24 | Title: Maestro: Uncovering Low-Rank Structures via Trainable Decomposition
Abstract: Deep Neural Networks (DNNs) have been a large driver and enabler for AI breakthroughs in recent years. These models have been getting larger in their attempt to become more accurate and tackle new upcoming use-cases, including AR/VR an... | [
24582
] | Test |
27,275 | 23 | Title: The Effect of Perceptual Load on Performance within IDE in People with ADHD Symptoms
Abstract: nan | [
19475
] | Validation |
27,276 | 27 | Title: Designing a Magnetic Micro-Robot for Transporting Filamentous Microcargo
Abstract: In recent years, the medical industry has witnessed a growing interest in minimally invasive procedures, with magnetic microrobots emerging as a promising approach. These micro-robots possess the ability to navigate through variou... | [] | Train |
27,277 | 24 | Title: Tailoring Machine Learning for Process Mining
Abstract: Machine learning models are routinely integrated into process mining pipelines to carry out tasks like data transformation, noise reduction, anomaly detection, classification, and prediction. Often, the design of such models is based on some ad-hoc assumpti... | [
34285
] | Validation |
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