Split (1)

train · 203k rows

node_id int64 0 76.9k	label int64 0 39	text stringlengths 13 124k	neighbors listlengths 0 3.32k	mask stringclasses 4 values
20,378	24	Title: AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving Abstract: Object detection with on-board sensors (e.g., lidar, radar, and camera) is crucial to autonomous driving (AD), and these sensors complement each other in modalities. While crowdsensing may potentially exploit these...	[ 45616, 41826 ]	Validation
20,379	24	Title: SneakyPrompt: Evaluating Robustness of Text-to-image Generative Models' Safety Filters Abstract: Text-to-image generative models such as Stable Diffusion and DALL$\cdot$E 2 have attracted much attention since their publication due to their wide application in the real world. One challenging problem of text-to-im...	[ 45104, 41395, 3548 ]	Validation
20,380	11	Title: Dynamics-Based Algorithm-Level Privacy Preservation for Push-Sum Average Consensus Abstract: Average consensus is essential for multi-agent systems to achieve specific functions and is widely used in network control, information fusion, etc. In conventional average consensus algorithms, all agents reach an agree...	[]	Validation
20,381	27	Title: Real-life Implementation of Internet of Robotic Things Using 5 DoF Heterogeneous Robotic Arm Abstract: Establishing a communication bridge by transferring data driven from different embedded sensors via internet or reconcilable network protocols between enormous number of distinctively addressable objects or "th...	[]	Test
20,382	28	Title: Segmented GRAND: Combining Sub-patterns in Near-ML Order Abstract: The recently introduced maximum-likelihood (ML) decoding scheme called guessing random additive noise decoding (GRAND) has demonstrated a remarkably low time complexity in high signal-to-noise ratio (SNR) regimes. However, the complexity is not a...	[]	Train
20,383	16	Title: CDA: Contrastive-adversarial Domain Adaptation Abstract: Recent advances in domain adaptation reveal that adversarial learning on deep neural networks can learn domain invariant features to reduce the shift between source and target domains. While such adversarial approaches achieve domain-level alignment, they ...	[]	Train
20,384	24	Title: Interpreting and generalizing deep learning in physics-based problems with functional linear models Abstract: Although deep learning has achieved remarkable success in various scientific machine learning applications, its black-box nature poses concerns regarding interpretability and generalization capabilities ...	[ 21243, 25030 ]	Train
20,385	30	Title: ClusTop: An unsupervised and integrated text clustering and topic extraction framework Abstract: Text clustering and topic extraction are two important tasks in text mining. Usually, these two tasks are performed separately. For topic extraction to facilitate clustering, we can first project texts into a topic s...	[]	Train
20,386	16	Title: UniverSeg: Universal Medical Image Segmentation Abstract: While deep learning models have become the predominant method for medical image segmentation, they are typically not capable of generalizing to unseen segmentation tasks involving new anatomies, image modalities, or labels. Given a new segmentation task, ...	[ 27817, 22713, 8155, 40894 ]	Train
20,387	24	Title: A Curriculum View of Robust Loss Functions Abstract: Robust loss functions are designed to combat the adverse impacts of label noise, whose robustness is typically supported by theoretical bounds agnostic to the training dynamics. However, these bounds may fail to characterize the empirical performance as it rem...	[]	Validation
20,388	24	Title: Stability Analysis Framework for Particle-based Distance GANs with Wasserstein Gradient Flow Abstract: In this paper, we investigate the training process of generative networks that use a type of probability density distance named particle-based distance as the objective function, e.g. MMD GAN, Cram\'er GAN, EIE...	[ 31784 ]	Train
20,389	24	Title: Spectral Cross-Domain Neural Network with Soft-adaptive Threshold Spectral Enhancement Abstract: —Electrocardiography (ECG) signals can be consid- ered as multi-variable time-series. The state-of-the-art ECG data classiﬁcation approaches, based on either feature engineering or deep learning techniques, treat sep...	[]	Train
20,390	23	Title: A novel failure indexing approach with run-time values of program variables Abstract: Failures with different root causes can disturb multi-fault localization significantly, therefore, dividing failures into distinct groups according to the responsible faults is highly important. In such a failure indexing task,...	[]	Train
20,391	16	Title: Real-time Multi-Object Tracking Based on Bi-directional Matching Abstract: In recent years, anchor-free object detection models combined with matching algorithms are used to achieve real-time muti-object tracking and also ensure high tracking accuracy. However, there are still great challenges in multi-object tr...	[]	Train
20,392	16	Title: Robust Contrastive Language-Image Pretraining against Adversarial Attacks Abstract: Contrastive vision-language representation learning has achieved state-of-the-art performance for zero-shot classification, by learning from millions of image-caption pairs crawled from the internet. However, the massive data tha...	[]	Train
20,393	24	Title: Boosting with Tempered Exponential Measures Abstract: One of the most popular ML algorithms, AdaBoost, can be derived from the dual of a relative entropy minimization problem subject to the fact that the positive weights on the examples sum to one. Essentially, harder examples receive higher probabilities. We ge...	[ 16587 ]	Train
20,394	16	Title: Jersey Number Recognition using Keyframe Identification from Low-Resolution Broadcast Videos Abstract: Player identification is a crucial component in vision-driven soccer analytics, enabling various downstream tasks such as player assessment, in-game analysis, and broadcast production. However, automatically de...	[]	Train
20,395	28	Title: The Model Inversion Eavesdropping Attack in Semantic Communication Systems Abstract: In recent years, semantic communication has been a popular research topic for its superiority in communication efficiency. As semantic communication relies on deep learning to extract meaning from raw messages, it is vulnerable ...	[]	Train
20,396	4	Title: OpenSCV: An Open Hierarchical Taxonomy for Smart Contract Vulnerabilities Abstract: Smart contracts are nowadays at the core of most blockchain systems, as they specify and allow an agreement between entities that wish to perform a transaction. As any computer program, smart contracts are subject to the presence...	[]	Validation
20,397	10	Title: HAT-GAE: Self-Supervised Graph Auto-encoders with Hierarchical Adaptive Masking and Trainable Corruption Abstract: Self-supervised auto-encoders have emerged as a successful framework for representation learning in computer vision and natural language processing in recent years, However, their application to gra...	[]	Train
20,398	10	Title: LLM-assisted Knowledge Graph Engineering: Experiments with ChatGPT Abstract: Knowledge Graphs (KG) provide us with a structured, flexible, transparent, cross-system, and collaborative way of organizing our knowledge and data across various domains in society and industrial as well as scientific disciplines. KGs ...	[ 28256, 37417, 37043, 13510 ]	Train
20,399	16	Title: FHA-Kitchens: A Novel Dataset for Fine-Grained Hand Action Recognition in Kitchen Scenes Abstract: A typical task in the field of video understanding is hand action recognition, which has a wide range of applications. Existing works either mainly focus on full-body actions, or the defined action categories are r...	[]	Train
20,400	16	Title: Learning Invariance From Generated Variance for Unsupervised Person Re-Identification Abstract: This work focuses on unsupervised representation learning in person re-identification (ReID). Recent self-supervised contrastive learning methods learn invariance by maximizing the representation similarity between tw...	[ 827 ]	Train
20,401	25	Title: FSD: An Initial Chinese Dataset for Fake Song Detection Abstract: Singing voice synthesis and singing voice conversion have significantly advanced, revolutionizing musical experiences. However, the rise of"Deepfake Songs"generated by these technologies raises concerns about authenticity. Unlike Audio DeepFake De...	[ 11288, 23916 ]	Train
20,402	30	Title: Unlocking Context Constraints of LLMs: Enhancing Context Efficiency of LLMs with Self-Information-Based Content Filtering Abstract: Large language models (LLMs) have received significant attention by achieving remarkable performance across various tasks. However, their fixed context length poses challenges when ...	[ 21494, 34491, 13700, 13510 ]	Train
20,403	24	Title: Pathway: a fast and flexible unified stream data processing framework for analytical and Machine Learning applications Abstract: We present Pathway, a new unified data processing framework that can run workloads on both bounded and unbounded data streams. The framework was created with the original motivation of...	[]	Train
20,404	5	Title: P4SGD: Programmable Switch Enhanced Model-Parallel Training on Generalized Linear Models on Distributed FPGAs Abstract: Generalized linear models (GLMs) are a widely utilized family of machine learning models in real-world applications. As data size increases, it is essential to perform efficient distributed tra...	[]	Test
20,405	16	Title: Uncertainty Estimation using the Local Lipschitz for Deep Learning Image Reconstruction Models Abstract: The use of supervised deep neural network approaches has been investigated to solve inverse problems in all domains, especially radiology where imaging technologies are at the heart of diagnostics. However, i...	[]	Validation
20,406	30	Title: Language Models are Causal Knowledge Extractors for Zero-shot Video Question Answering Abstract: Causal Video Question Answering (CVidQA) queries not only association or temporal relations but also causal relations in a video. Existing question synthesis methods pretrained question generation (QG) systems on rea...	[ 6061 ]	Train
20,407	5	Title: GACER: Granularity-Aware ConcurrEncy Regulation for Multi-Tenant Deep Learning Abstract: As deep learning continues to advance and is applied to increasingly complex scenarios, the demand for concurrent deployment of multiple neural network models has arisen. This demand, commonly referred to as multi-tenant com...	[]	Train
20,408	1	Title: Confidence-based Event-centric Online Video Question Answering on a Newly Constructed ATBS Dataset Abstract: Deep neural networks facilitate video question answering (VideoQA), but the real-world applications on video streams such as CCTV and live cast place higher demands on the solver. To address the challenge...	[]	Train
20,409	24	Title: Federated Large Language Model: A Position Paper Abstract: Large scale language models (LLM) have received significant attention and found diverse applications across various domains, but their development encounters challenges in real-world scenarios. These challenges arise due to the scarcity of public domain ...	[ 40192, 12027, 23502 ]	Train
20,410	30	Title: Lexical Retrieval Hypothesis in Multimodal Context Abstract: Multimodal corpora have become an essential language resource for language science and grounded natural language processing (NLP) systems due to the growing need to understand and interpret human communication across various channels. In this paper, we...	[]	Train
20,411	30	Title: Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding Abstract: This paper presents"Predictive Pipelined Decoding (PPD),"an approach that speeds up greedy decoding in Large Language Models (LLMs) while maintaining the exact same output as the original decoding. Unlike conventional str...	[ 15488, 22978, 13700, 31256, 40413 ]	Train
20,412	16	Title: PointCLIMB: An Exemplar-Free Point Cloud Class Incremental Benchmark Abstract: Point clouds offer comprehensive and precise data regarding the contour and configuration of objects. Employing such geometric and topological 3D information of objects in class incremental learning can aid endless application in 3D-c...	[]	Train
20,413	16	Title: Contrastive Learning Based Recursive Dynamic Multi-Scale Network for Image Deraining Abstract: Rain streaks significantly decrease the visibility of captured images and are also a stumbling block that restricts the performance of subsequent computer vision applications. The existing deep learning-based image der...	[ 10492, 1903 ]	Train
20,414	38	Title: Peer Prediction for Peer Review: Designing a Marketplace for Ideas Abstract: The paper describes a potential platform to facilitate academic peer review with emphasis on early-stage research. This platform aims to make peer review more accurate and timely by rewarding reviewers on the basis of peer prediction al...	[]	Train
20,415	16	Title: MammoDG: Generalisable Deep Learning Breaks the Limits of Cross-Domain Multi-Center Breast Cancer Screening Abstract: Breast cancer is a major cause of cancer death among women, emphasising the importance of early detection for improved treatment outcomes and quality of life. Mammography, the primary diagnostic ...	[]	Validation
20,416	30	Title: Shuffle & Divide: Contrastive Learning for Long Text Abstract: We propose a self-supervised learning method for long text documents based on contrastive learning. A key to our method is Shuffle and Divide (SaD), a simple text augmentation algorithm that sets up a pretext task required for contrastive updates to ...	[]	Train
20,417	28	Title: Vision-Assisted mmWave Beam Management for Next-Generation Wireless Systems: Concepts, Solutions and Open Challenges Abstract: Beamforming techniques have been widely used in the millimeter wave (mmWave) bands to mitigate the path loss of mmWave radio links as the narrow straight beams by directionally concentra...	[]	Test
20,418	10	Title: Review of Parameter Tuning Methods for Nature-Inspired Algorithms Abstract: nan	[]	Train
20,419	6	Title: Introducing Vibration for use in Interaction Designs to support Human Performance: A Pilot Study Abstract: While vibration is a well-used output signal in HCI as part of haptic interaction, vibration outside HCI is used in many other modes to support human performance, from rehabilitation to cognition. In this l...	[]	Train
20,420	23	Title: A Case Study on AI Engineering Practices: Developing an Autonomous Stock Trading System Abstract: Today, many systems use artificial intelligence (AI) to solve complex problems. While this often increases system effectiveness, developing a production-ready AI-based system is a difficult task. Thus, solid AI engi...	[]	Train
20,421	16	Title: LEO: Generative Latent Image Animator for Human Video Synthesis Abstract: Spatio-temporal coherency is a major challenge in synthesizing high quality videos, particularly in synthesizing human videos that contain rich global and local deformations. To resolve this challenge, previous approaches have resorted to ...	[ 34074 ]	Train
20,422	34	Title: Capacity-Preserving Subgraphs of Directed Flow Networks Abstract: We introduce and discuss the Minimum Capacity-Preserving Subgraph (MCPS) problem: given a directed graph and a retention ratio $\alpha \in (0,1)$, find the smallest subgraph that, for each pair of vertices $(u,v)$, preserves at least a fraction $\...	[]	Train
20,423	16	Title: Butterfly: Multiple Reference Frames Feature Propagation Mechanism for Neural Video Compression Abstract: Using more reference frames can significantly improve the compression efficiency in neural video compression. However, in low-latency scenarios, most existing neural video compression frameworks usually use ...	[]	Validation
20,424	6	Title: Multimodal Earable Sensing for Human Energy Expenditure Estimation Abstract: Energy Expenditure Estimation (EEE) is vital for maintaining weight, managing chronic diseases, achieving fitness goals, and improving overall health and well-being. Gold standard measurements for energy expenditure are expensive and ti...	[]	Train
20,425	30	Title: M-SENSE: Modeling Narrative Structure in Short Personal Narratives Using Protagonist's Mental Representations Abstract: Narrative is a ubiquitous component of human communication. Understanding its structure plays a critical role in a wide variety of applications, ranging from simple comparative analyses to enha...	[]	Train
20,426	16	Title: Conditional Score Guidance for Text-Driven Image-to-Image Translation Abstract: We present a novel algorithm for text-driven image-to-image translation based on a pretrained text-to-image diffusion model. Our method aims to generate a target image by selectively editing the regions of interest in a source image,...	[ 20960, 16103 ]	Train
20,427	4	Title: An Adaptive Ensemble Framework for Addressing Concept Drift in IoT Data Streams Abstract: In the modern era of digital transformation, the evolution of the fifth-generation (5G) wireless network has played a pivotal role in revolutionizing communication technology and accelerating the growth of smart technology ...	[]	Test
20,428	15	Title: Accelerating Graph Analytics on a Reconfigurable Architecture with a Data-Indirect Prefetcher Abstract: The irregular nature of memory accesses of graph workloads makes their performance poor on modern computing platforms. On manycore reconfigurable architectures (MRAs), in particular, even state-of-the-art grap...	[]	Test
20,429	24	Title: DADO - Low-Cost Selection Strategies for Deep Active Design Optimization Abstract: In this experience report, we apply deep active learning to the field of design optimization to reduce the number of computationally expensive numerical simulations. We are interested in optimizing the design of structural compone...	[]	Train
20,430	16	Title: Producing a Standard Dataset of Speed Climbing Training Videos Using Deep Learning Techniques Abstract: This dissertation presents a methodology for recording speed climbing training sessions with multiple cameras and annotating the videos with relevant data, including body position, hand and foot placement, and...	[]	Train
20,431	24	Title: BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware Abstract: Efficient large-scale neural network training and inference on commodity CPU hardware is of immense practical significance in democratizing deep learning (DL) cap...	[]	Test
20,432	31	Title: Prompt Learning for News Recommendation Abstract: Some recent news recommendation (NR) methods introduce a Pre-trained Language Model (PLM) to encode news representation by following the vanilla pre-train and fine-tune paradigm with carefully-designed recommendation-specific neural networks and objective functio...	[ 21252, 33800, 14282, 16179, 5974, 9917 ]	Train
20,433	24	Title: A Privacy-Preserving Federated Learning Approach for Kernel methods Abstract: It is challenging to implement Kernel methods, if the data sources are distributed and cannot be joined at a trusted third party for privacy reasons. It is even more challenging, if the use case rules out privacy-preserving approaches ...	[]	Test
20,434	16	Title: Color-NeuS: Reconstructing Neural Implicit Surfaces with Color Abstract: The reconstruction of object surfaces from multi-view images or monocular video is a fundamental issue in computer vision. However, much of the recent research concentrates on reconstructing geometry through implicit or explicit methods. In...	[ 14168, 8795, 39012, 19630 ]	Test
20,435	24	Title: StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis Abstract: Text-to-image synthesis has recently seen significant progress thanks to large pretrained language models, large-scale training data, and the introduction of scalable model families such as diffusion and autoregressive...	[ 36741, 18697, 11405, 21264, 44177, 41874, 33939, 12565, 36640, 19618, 17449, 7850, 18731, 37290, 24622, 19378, 34873, 26809, 40253, 29245, 30402, 19652, 36168, 29389, 10062, 3918, 27612, 28004, 36844, 45933, 43771, 1148 ]	Test
20,436	24	Title: FastAMI - a Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics Abstract: Clustering is at the very core of machine learning, and its applications proliferate with the increasing availability of data. However, as datasets grow, comparing clusterings with an adjustment for chance be...	[]	Train
20,437	16	Title: LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning Abstract: We present a novel vision-language prompt learning approach for few-shot out-of-distribution (OOD) detection. Few-shot OOD detection aims to detect OOD images from classes that are unseen during training using only a few labeled in-dist...	[ 18386, 1930, 25310 ]	Validation
20,438	16	Title: DARTS: Double Attention Reference-based Transformer for Super-resolution Abstract: We present DARTS, a transformer model for reference-based image super-resolution. DARTS learns joint representations of two image distributions to enhance the content of low-resolution input images through matching correspondences...	[]	Train
20,439	24	Title: Learning Directed Graphical Models with Optimal Transport Abstract: Estimating the parameters of a probabilistic directed graphical model from incomplete data remains a long-standing challenge. This is because, in the presence of latent variables, both the likelihood function and posterior distribution are intra...	[ 26389 ]	Train
20,440	4	Title: SoK: The Ghost Trilemma Abstract: Trolls, bots, and sybils distort online discourse and compromise the security of networked platforms. User identity is central to the vectors of attack and manipulation employed in these contexts. However it has long seemed that, try as it might, the security community has been ...	[]	Train
20,441	24	Title: The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation Abstract: Theoretical guarantees in reinforcement learning (RL) are known to suffer multiplicative blow-up factors with respect to the misspecification error of function approximation. Yet, the nature of such \emph{approximati...	[]	Test
20,442	16	Title: Evading Forensic Classifiers with Attribute-Conditioned Adversarial Faces Abstract: The ability of generative models to produce highly realistic synthetic face images has raised security and ethical concerns. As a first line of defense against such fake faces, deep learning based forensic classifiers have been d...	[]	Train
20,443	24	Title: Predicting Early Dropouts of an Active and Healthy Ageing App Abstract: In this work, we present a machine learning approach for predicting early dropouts of an active and healthy ageing app. The presented algorithms have been submitted to the IFMBE Scientific Challenge 2022, part of IUPESM WC 2022. We have proc...	[ 20307 ]	Validation
20,444	7	Title: Failure Probability Estimation and Detection of Failure Surfaces via Adaptive Sequential Decomposition of the Design Domain Abstract: nan	[]	Test
20,445	30	Title: BAN-PL: a Novel Polish Dataset of Banned Harmful and Offensive Content from Wykop.pl web service Abstract: Advances in automated detection of offensive language online, including hate speech and cyberbullying, require improved access to publicly available datasets comprising social media content. In this paper, ...	[]	Train
20,446	24	Title: Blockchain-based decentralized voting system security Perspective: Safe and secure for digital voting system Abstract: This research study focuses primarily on Block-Chain-based voting systems, which facilitate participation in and administration of voting for voters, candidates, and officials. Because we used B...	[]	Test
20,447	6	Title: Peer Surveillance in Online Communities Abstract: Online communities are not safe spaces for user privacy. Even though existing research focuses on creating and improving various content moderation strategies and privacy preserving technologies, platforms hosting online communities support features allowing user...	[]	Train
20,448	16	Title: Deep state-space modeling for explainable representation, analysis, and generation of professional human poses Abstract: The analysis of human movements has been extensively studied due to its wide variety of practical applications, such as human-robot interaction, human learning applications, or clinical diagno...	[ 27991 ]	Train
20,449	24	Title: How to Protect Copyright Data in Optimization of Large Language Models? Abstract: Large language models (LLMs) and generative AI have played a transformative role in computer research and applications. Controversy has arisen as to whether these models output copyrighted data, which can occur if the data the mode...	[ 40196, 16781, 1298, 39573, 21145, 9381, 13100, 20911, 16949, 4663, 24635, 5447, 17354, 13388, 22476, 7643, 12898, 40301, 2291, 7159, 11128, 43641, 8190 ]	Train
20,450	15	Title: Enhancement in Reliability for Multi-core system consisting of One Instruction Cores Abstract: Rapid CMOS device size reduction resulted in billions of transistors on a chip have led to integration of many cores leading to many challenges such as increased power dissipation, thermal dissipation, occurrence of tr...	[]	Train
20,451	16	Title: BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion Abstract: Recent text-to-image diffusion models have demonstrated an astonishing capacity to generate high-quality images. However, researchers mainly studied the way of synthesizing images with only text prompts. While some works have...	[ 6242, 2211, 43867, 41146, 31913, 3690, 7723, 45933, 28279, 34074, 3067, 28382 ]	Train
20,452	16	Title: Efficient Deduplication and Leakage Detection in Large Scale Image Datasets with a focus on the CrowdAI Mapping Challenge Dataset Abstract: Recent advancements in deep learning and computer vision have led to widespread use of deep neural networks to extract building footprints from remote-sensing imagery. The s...	[]	Test
20,453	10	Title: Behavioral Cloning via Search in Embedded Demonstration Dataset Abstract: Behavioural cloning uses a dataset of demonstrations to learn a behavioural policy. To overcome various learning and policy adaptation problems, we propose to use latent space to index a demonstration dataset, instantly access similar rele...	[ 4643, 13965, 44759 ]	Train
20,454	2	Title: Partially Typed Multiparty Sessions Abstract: A multiparty session formalises a set of concurrent communicating participants. We propose a type system for multiparty sessions where some communications between participants can be ignored. This allows us to type some sessions with global types representing interes...	[]	Validation
20,455	24	Title: Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting Abstract: Diffusion models have achieved state-of-the-art performance in generative modeling tasks across various domains. Prior works on time series diffusion models have primarily focused on developing conditio...	[ 11982 ]	Validation
20,456	16	Title: Turning Waste into Wealth: Leveraging Low-Quality Samples for Enhancing Continuous Conditional Generative Adversarial Networks Abstract: Continuous Conditional Generative Adversarial Networks (CcGANs) enable generative modeling conditional on continuous scalar variables (termed regression labels). However, they ...	[ 41505 ]	Train
20,457	23	Title: Toward a Mapping of Capability and Skill Models using Asset Administration Shells and Ontologies Abstract: In order to react efficiently to changes in production, resources and their functions must be integrated into plants in accordance with the plug and produce principle. In this context, research on so-called...	[]	Validation
20,458	10	Title: Probabilistic Uncertainty-Aware Risk Spot Detector for Naturalistic Driving Abstract: Risk assessment is a central element for the development and validation of autonomous vehicles. It comprises a combination of occurrence probability and severity of future critical events. Time headway (TH) as well as time-to-c...	[ 37347, 39431, 16203, 36380, 35262 ]	Train
20,459	16	Title: Exploring Multi-Modal Contextual Knowledge for Open-Vocabulary Object Detection Abstract: In this paper, we for the first time explore helpful multi-modal contextual knowledge to understand novel categories for open-vocabulary object detection (OVD). The multi-modal contextual knowledge stands for the joint rela...	[]	Validation
20,460	24	Title: Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes Abstract: Pool-based active learning (AL) is a promising technology for increasing data-efficiency of machine learning models. However, surveys show that performance of recent AL methods is very sensitive to the choice of data...	[]	Train
20,461	33	Title: History-deterministic Vector Addition Systems Abstract: We consider history-determinism, a restricted form of non-determinism, for Vector Addition Systems with States (VASS) when used as acceptors to recognise languages of finite words. History-determinism requires that the non-deterministic choices can be resol...	[ 12570, 29637 ]	Train
20,462	31	Title: Understanding Differential Search Index for Text Retrieval Abstract: The Differentiable Search Index (DSI) is a novel information retrieval (IR) framework that utilizes a differentiable function to generate a sorted list of document identifiers in response to a given query. However, due to the black-box nature o...	[ 7380 ]	Test
20,463	16	Title: Curvature regularization for Non-line-of-sight Imaging from Under-sampled Data Abstract: Non-line-of-sight (NLOS) imaging aims to reconstruct the three-dimensional hidden scenes from the data measured in the line-of-sight, which uses photon time-of-flight information encoded in light after multiple diffuse refle...	[]	Train
20,464	30	Title: An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning Abstract: Catastrophic forgetting (CF) is a phenomenon that occurs in machine learning when a model forgets previously learned information as it learns new information. As large language models (LLMs) have shown e...	[ 13700, 14501, 20575 ]	Train
20,465	30	Title: Hexatagging: Projective Dependency Parsing as Tagging Abstract: We introduce a novel dependency parser, the hexatagger, that constructs dependency trees by tagging the words in a sentence with elements from a finite set of possible tags. In contrast to many approaches to dependency parsing, our approach is fully...	[]	Train
20,466	4	Title: Differentially Private Algorithms for Synthetic Power System Datasets Abstract: While power systems research relies on the availability of real-world network datasets, data owners (e.g., system operators) are hesitant to share data due to privacy risks. To control these risks, we develop privacy-preserving algor...	[]	Test
20,467	30	Title: FPTQ: Fine-grained Post-Training Quantization for Large Language Models Abstract: In the era of large-scale language models, the substantial parameter size poses significant challenges for deployment. Being a prevalent compression technique, quantization has emerged as the mainstream practice to tackle this issu...	[ 6979, 13700, 5649, 1234, 12851, 44402, 13525, 16662, 41244, 21849, 43452 ]	Test
20,468	10	Title: Both eyes open: Vigilant Incentives help Regulatory Markets improve AI Safety Abstract: In the context of rapid discoveries by leaders in AI, governments must consider how to design regulation that matches the increasing pace of new AI capabilities. Regulatory Markets for AI is a proposal designed with adaptabil...	[]	Validation
20,469	16	Title: How To Not Train Your Dragon: Training-free Embodied Object Goal Navigation with Semantic Frontiers Abstract: Object goal navigation is an important problem in Embodied AI that involves guiding the agent to navigate to an instance of the object category in an unknown environment -- typically an indoor scene. Unf...	[ 26830 ]	Train
20,470	16	Title: Image generation with shortest path diffusion Abstract: The field of image generation has made significant progress thanks to the introduction of Diffusion Models, which learn to progressively reverse a given image corruption. Recently, a few studies introduced alternative ways of corrupting images in Diffusion ...	[]	Validation
20,471	28	Title: Robust Beamforming Design for RIS-Aided Cell-Free Systems With CSI Uncertainties and Capacity-Limited Backhaul Abstract: In this paper, we consider the robust beamforming design in a reconfigurable intelligent surface (RIS)-aided cell-free (CF) system considering the channel state information (CSI) uncertainties...	[ 42507 ]	Train
20,472	24	Title: Bidirectional Looking with A Novel Double Exponential Moving Average to Adaptive and Non-adaptive Momentum Optimizers Abstract: Optimizer is an essential component for the success of deep learning, which guides the neural network to update the parameters according to the loss on the training set. SGD and Adam ar...	[]	Validation
20,473	24	Title: Input Perturbation Reduces Exposure Bias in Diffusion Models Abstract: Denoising Diffusion Probabilistic Models have shown an impressive generation quality, although their long sampling chain leads to high computational costs. In this paper, we observe that a long sampling chain also leads to an error accumulati...	[ 20624, 9059 ]	Train
20,474	16	Title: BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout Abstract: Using synthesized images to boost the performance of perception models is a long-standing research challenge in computer vision. It becomes more eminent in visual-centric autonomous driving ...	[ 25160, 2921, 44585, 18731, 11820, 16557, 41146, 15983, 1717, 17526, 20949, 22616, 34074, 41439 ]	Test
20,475	24	Title: Convergence Guarantees of Overparametrized Wide Deep Inverse Prior Abstract: Neural networks have become a prominent approach to solve inverse problems in recent years. Amongst the different existing methods, the Deep Image/Inverse Priors (DIPs) technique is an unsupervised approach that optimizes a highly overp...	[]	Validation
20,476	16	Title: MicroSegNet: A Deep Learning Approach for Prostate Segmentation on Micro-Ultrasound Images Abstract: Micro-ultrasound (micro-US) is a novel 29-MHz ultrasound technique that provides 3-4 times higher resolution than traditional ultrasound, delivering comparable accuracy for diagnosing prostate cancer to MRI but a...	[]	Train
20,477	8	Title: Wi-Fi Multi-Link Operation: An Experimental Study of Latency and Throughput Abstract: In this article, we investigate the real-world capability of the multi-link operation (MLO) framework -- one of the key MAC-layer features included in the IEEE 802.11be amendment -- by using a large dataset containing 5 GHz spe...	[ 17233, 16769 ]	Test

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