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
21,678	24	Title: A Bio-Inspired Chaos Sensor Model Based on the Perceptron Neural Network: Machine Learning Concept and Application for Computational Neuro-Science Abstract: The study presents a bio-inspired chaos sensor model based on the perceptron neural network for the estimation of entropy of spike train in neurodynamic sys...	[ 36230 ]	Train
21,679	16	Title: SF-TMN: SlowFast Temporal Modeling Network for Surgical Phase Recognition Abstract: Automatic surgical phase recognition is one of the key technologies to support Video-Based Assessment (VBA) systems for surgical education. Utilizing temporal information is crucial for surgical phase recognition, hence various r...	[ 30106, 17547, 3158 ]	Test
21,680	10	Title: Physical Deep Reinforcement Learning: Safety and Unknown Unknowns Abstract: In this paper, we propose the Phy-DRL: a physics-model-regulated deep reinforcement learning framework for safety-critical autonomous systems. The Phy-DRL is unique in three innovations: i) proactive unknown-unknowns training, ii) conjun...	[ 17198 ]	Train
21,681	16	Title: Federated Ensemble YOLOv5 - A Better Generalized Object Detection Algorithm Abstract: Federated learning (FL) has gained significant traction as a privacy-preserving algorithm, but the underlying resemblances of federated learning algorithms like Federated averaging (FedAvg) or Federated SGD (Fed SGD) to ensembl...	[ 12532 ]	Train
21,682	16	Title: Floaters No More: Radiance Field Gradient Scaling for Improved Near-Camera Training Abstract: NeRF acquisition typically requires careful choice of near planes for the different cameras or suffers from background collapse, creating floating artifacts on the edges of the captured scene. The key insight of this wo...	[ 29000, 7068 ]	Test
21,683	16	Title: Preserving Modality Structure Improves Multi-Modal Learning Abstract: Self-supervised learning on large-scale multi-modal datasets allows learning semantically meaningful embeddings in a joint multi-modal representation space without relying on human annotations. These joint embeddings enable zero-shot cross-mod...	[]	Train
21,684	24	Title: Aligning Agent Policy with Externalities: Reward Design via Bilevel RL Abstract: In reinforcement learning (RL), a reward function is often assumed at the outset of a policy optimization procedure. Learning in such a fixed reward paradigm in RL can neglect important policy optimization considerations, such as st...	[ 8464, 37252, 1716, 9573 ]	Test
21,685	10	Title: PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Abstract: In recent years, Game AI research has made important breakthroughs using Reinforcement Learning (RL). Despite this, RL for modern tabletop games has gained little to no attention, even when they offer a range of unique cha...	[]	Test
21,686	23	Title: The Effect of Stereotypes on Perceived Competence of Indigenous Software Practitioners: A Professional Photo Abstract: Context: Potential employers can readily find job candidates' photos through various online sources such as former employers' websites or professional and social networks. The alignment or 'fit'...	[]	Train
21,687	24	Title: V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection Abstract: Machine learning (ML) has revolutionized transportation systems, enabling autonomous driving and smart traffic services. Federated learning (FL) overcomes privacy constraints by training M...	[ 1155, 17612, 10265, 8412, 44574 ]	Train
21,688	16	Title: CD-CTFM: A Lightweight CNN-Transformer Network for Remote Sensing Cloud Detection Fusing Multiscale Features Abstract: Clouds in remote sensing images inevitably affect information extraction, which hinder the following analysis of satellite images. Hence, cloud detection is a necessary preprocessing procedure. ...	[]	Validation
21,689	16	Title: Region-wise matching for image inpainting based on adaptive weighted low-rank decomposition Abstract: Digital image inpainting is an interpolation problem, inferring the content in the missing (unknown) region to agree with the known region data such that the interpolated result fulfills some prior knowledge. Lo...	[]	Train
21,690	16	Title: Density Invariant Contrast Maximization for Neuromorphic Earth Observations Abstract: Contrast maximization (CMax) techniques are widely used in event-based vision systems to estimate the motion parameters of the camera and generate high-contrast images. However, these techniques are noise-intolerance and suffer...	[]	Train
21,691	34	Title: An Approximation Algorithm for Ancestral Maximum-Likelihood and Phylogeography Inference Problems under Time Reversible Markov Evolutionary Models Abstract: The ancestral maximum-likelihood and phylogeography problems are two fundamental problems involving evolutionary studies. The ancestral maximum-likelihood p...	[]	Train
21,692	28	Title: Exploring the Interplay of Interference and Queues in Unlicensed Spectrum Bands for UAV Networks Abstract: In this paper, we present an analytical framework to explore the interplay of signal interference and transmission queue management, and their impacts on the performance of unmanned aerial vehicles (UAVs) w...	[]	Test
21,693	23	Title: The TeamPlay Project: Analysing and Optimising Time, Energy, and Security for Cyber-Physical Systems Abstract: Non-functional properties, such as energy, time, and security (ETS) are becoming increasingly important in Cyber-Physical Systems (CPS) programming. This article describes TeamPlay, a research project f...	[ 39739 ]	Test
21,694	30	Title: Exploring Attention Mechanisms for Multimodal Emotion Recognition in an Emergency Call Center Corpus Abstract: The emotion detection technology to enhance human decision-making is an important research issue for real-world applications, but real-life emotion datasets are relatively rare and small. The experiment...	[ 6763, 9693 ]	Train
21,695	16	Title: Language-Guided Music Recommendation for Video via Prompt Analogies Abstract: We propose a method to recommend music for an input video while allowing a user to guide music selection with free-form natural language. A key challenge of this problem setting is that existing music video datasets provide the needed ...	[ 21168, 33800 ]	Validation
21,696	16	Title: Shifted-windows transformers for the detection of cerebral aneurysms in microsurgery Abstract: nan	[]	Train
21,697	16	Title: Diffusion Sampling with Momentum for Mitigating Divergence Artifacts Abstract: Despite the remarkable success of diffusion models in image generation, slow sampling remains a persistent issue. To accelerate the sampling process, prior studies have reformulated diffusion sampling as an ODE/SDE and introduced high...	[ 21152, 37299, 11982 ]	Test
21,698	24	Title: Data-Copying in Generative Models: A Formal Framework Abstract: There has been some recent interest in detecting and addressing memorization of training data by deep neural networks. A formal framework for memorization in generative models, called"data-copying,"was proposed by Meehan et. al. (2020). We build upo...	[]	Train
21,699	24	Title: Interactive Decision Tree Creation and Enhancement with Complete Visualization for Explainable Modeling Abstract: To increase the interpretability and prediction accuracy of the Machine Learning (ML) models, visualization of ML models is a key part of the ML process. Decision Trees (DTs) are essential in machine...	[ 7017 ]	Validation
21,700	30	Title: Differentiable Entailment for Parameter Efficient Few Shot Learning Abstract: Few-shot learning allows pre-trained language models to adapt to downstream tasks while using a limited number of training examples. However, practical applications are limited when all model parameters must be optimized. In this work ...	[]	Validation
21,701	6	Title: Causally Linking Health Application Data and Personal Information Management Tools Abstract: The proliferation of consumer health devices such as smart watches, sleep monitors, smart scales, etc, in many countries, has not only led to growing interest in health monitoring, but also to the development of a countl...	[]	Train
21,702	10	Title: LLM as A Robotic Brain: Unifying Egocentric Memory and Control Abstract: Embodied AI focuses on the study and development of intelligent systems that possess a physical or virtual embodiment (i.e. robots) and are able to dynamically interact with their environment. Memory and control are the two essential parts ...	[ 1952, 10624, 22115, 295, 10897, 42355, 8084, 45685, 34361, 13564 ]	Train
21,703	16	Title: Entropy-based Guidance of Deep Neural Networks for Accelerated Convergence and Improved Performance Abstract: Neural networks have dramatically increased our capacity to learn from large, high-dimensional datasets across innumerable disciplines. However, their decisions are not easily interpretable, their comput...	[ 25525 ]	Train
21,704	10	Title: Dear XAI Community, We Need to Talk! Fundamental Misconceptions in Current XAI Research Abstract: Despite progress in the field, significant parts of current XAI research are still not on solid conceptual, ethical, or methodological grounds. Unfortunately, these unfounded parts are not on the decline but continu...	[ 39720 ]	Train
21,705	28	Title: Information-Theoretic Privacy-Preserving Schemes Based On Perfect Privacy Abstract: Consider a pair of random variables $(X,Y)$ distributed according to a given joint distribution $p_{XY}$. A curator wishes to maximally disclose information about $Y$, while limiting the information leakage incurred on $X$. Adopt...	[ 39548 ]	Test
21,706	30	Title: ZYN: Zero-Shot Reward Models with Yes-No Questions Abstract: In this work, we address the problem of directing the text generations of a LLM towards a desired behavior, aligning the generated text with the preferences of the human operator. We propose using another language model as a critic, reward model in a z...	[ 10944, 40610, 12957, 21739, 846, 22098, 33172, 39451, 24316, 17789, 29375 ]	Train
21,707	24	Title: Identifying the Key Attributes in an Unlabeled Event Log for Automated Process Discovery Abstract: —Process mining discovers and analyzes a process model from historical event logs. The prior art methods use the attributes of case-id, activity, and timestamp hidden in an event log as clues to discover a process ...	[]	Test
21,708	5	Title: Baechi: Fast Device Placement of Machine Learning Graphs Abstract: Machine Learning graphs (or models) can be challenging or impossible to train when either devices have limited memory, or models are large. To split the model across devices, learning-based approaches are still popular. While these result in mode...	[]	Test
21,709	37	Title: Towards Learned Predictability of Storage Systems Abstract: With the rapid development of cloud computing and big data technologies, storage systems have become a fundamental building block of datacenters, incorporating hardware innovations such as flash solid state drives and non-volatile memories, as well as s...	[]	Train
21,710	16	Title: Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms Abstract: Real-time video surveillance, through CCTV camera systems has become essential for ensuring public safety which is a priority today. Although CCTV cameras...	[]	Test
21,711	30	Title: Learning Answer Generation using Supervision from Automatic Question Answering Evaluators Abstract: Recent studies show that sentence-level extractive QA, i.e., based on Answer Sentence Selection (AS2), is outperformed by Generation-based QA (GenQA) models, which generate answers using the top-k answer sentences...	[ 10023 ]	Test
21,712	34	Title: Provably-Efficient and Internally-Deterministic Parallel Union-Find Abstract: Determining the degree of inherent parallelism in classical sequential algorithms and leveraging it for fast parallel execution is a key topic in parallel computing, and detailed analyses are known for a wide range of classical algorit...	[]	Test
21,713	16	Title: Long-Distance Gesture Recognition using Dynamic Neural Networks Abstract: Gestures form an important medium of communication between humans and machines. An overwhelming majority of existing gesture recognition methods are tailored to a scenario where humans and machines are located very close to each other. Thi...	[]	Train
21,714	16	Title: AGIQA-3K: An Open Database for AI-Generated Image Quality Assessment Abstract: With the rapid advancements of the text-to-image generative model, AI-generated images (AGIs) have been widely applied to entertainment, education, social media, etc. However, considering the large quality variance among different AGI...	[ 37152, 6145, 2502, 15591, 2247, 35273, 35977, 25368 ]	Test
21,715	24	Title: Feature propagation as self-supervision signals on graphs Abstract: Self-supervised learning is gaining considerable attention as a solution to avoid the requirement of extensive annotations in representation learning on graphs. Current algorithms are based on contrastive learning, which is computation an memory...	[]	Test
21,716	24	Title: Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity Abstract: Byzantine machine learning (ML) aims to ensure the resilience of distributed learning algorithms to misbehaving (or Byzantine) machines. Although this problem received significant attention, prior works often assume the data held b...	[ 8728, 13777, 7556 ]	Train
21,717	16	Title: Bringing Telepresence to Every Desk Abstract: In this paper, we work to bring telepresence to every desktop. Unlike commercial systems, personal 3D video conferencing systems must render high-quality videos while remaining financially and computationally viable for the average consumer. To this end, we introduce...	[]	Train
21,718	30	Title: Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization Abstract: Prompt tuning is one of the successful approaches for parameter-efficient tuning of pre-trained language models. Despite being arguably the most parameter-efficient (tuned soft prompts constitute<0.1% of total parameters),...	[ 13442, 33854 ]	Train
21,719	24	Title: Tackling Diverse Minorities in Imbalanced Classification Abstract: Imbalanced datasets are commonly observed in various real-world applications, presenting significant challenges in training classifiers. When working with large datasets, the imbalanced issue can be further exacerbated, making it exceptionally di...	[ 41436, 14524, 7918, 7351 ]	Test
21,720	6	Title: EFL Students' Attitudes and Contradictions in a Machine-in-the-loop Activity System Abstract: This study applies Activity Theory and investigates the attitudes and contradictions of 67 English as a foreign language (EFL) students from four Hong Kong secondary schools towards machine-in-the-loop writing, where ar...	[]	Train
21,721	24	Title: Generative Adversarial Networks Unlearning Abstract: As machine learning continues to develop, and data misuse scandals become more prevalent, individuals are becoming increasingly concerned about their personal information and are advocating for the right to remove their data. Machine unlearning has emerged as ...	[ 7354 ]	Train
21,722	5	Title: Miriam: Exploiting Elastic Kernels for Real-time Multi-DNN Inference on Edge GPU Abstract: Many applications such as autonomous driving and augmented reality, require the concurrent running of multiple deep neural networks (DNN) that poses different levels of real-time performance requirements. However, coordina...	[]	Train
21,723	30	Title: CTC-based Non-autoregressive Speech Translation Abstract: Combining end-to-end speech translation (ST) and non-autoregressive (NAR) generation is promising in language and speech processing for their advantages of less error propagation and low latency.In this paper, we investigate the potential of connectionist...	[]	Train
21,724	30	Title: Machine Psychology: Investigating Emergent Capabilities and Behavior in Large Language Models Using Psychological Methods Abstract: Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Due to rapid technological advances and their extr...	[ 7936, 30087, 39177, 37516, 2833, 10900, 21401, 11045, 16556, 40876, 36528, 25924, 13510, 30668, 28242, 21733, 27880, 5355, 1401, 634 ]	Train
21,725	16	Title: Sparse resultant based minimal solvers in computer vision and their connection with the action matrix Abstract: Many computer vision applications require robust and efficient estimation of camera geometry from a minimal number of input data measurements, i.e., solving minimal problems in a RANSAC framework. Mini...	[]	Train
21,726	6	Title: Gatherplot: A Non-Overlapping Scatterplot Abstract: Scatterplots are a common tool for exploring multidimensional datasets, especially in the form of scatterplot matrices (SPLOMs). However, scatterplots suffer from overplotting when categorical variables are mapped to one or two axes, or the same continuous vari...	[]	Train
21,727	16	Title: Proposal-Based Multiple Instance Learning for Weakly-Supervised Temporal Action Localization Abstract: Weakly-supervised temporal action localization aims to localize and recognize actions in untrimmed videos with only video-level category labels during training. Without instance-level annotations, most existing...	[]	Validation
21,728	24	Title: Learning From Biased Soft Labels Abstract: Knowledge distillation has been widely adopted in a variety of tasks and has achieved remarkable successes. Since its inception, many researchers have been intrigued by the dark knowledge hidden in the outputs of the teacher model. Recently, a study has demonstrated tha...	[]	Validation
21,729	30	Title: A Deep Dive into the Disparity of Word Error Rates Across Thousands of NPTEL MOOC Videos Abstract: Automatic speech recognition (ASR) systems are designed to transcribe spoken language into written text and find utility in a variety of applications including voice assistants and transcription services. However, ...	[]	Test
21,730	30	Title: Collective Knowledge Graph Completion with Mutual Knowledge Distillation Abstract: Knowledge graph completion (KGC), the task of predicting missing information based on the existing relational data inside a knowledge graph (KG), has drawn significant attention in recent years. However, the predictive power of KG...	[]	Test
21,731	24	Title: Identification of Negative Transfers in Multitask Learning Using Surrogate Models Abstract: Multitask learning is widely used in practice to train a low-resource target task by augmenting it with multiple related source tasks. Yet, naively combining all the source tasks with a target task does not always improve...	[ 36963, 36398 ]	Train
21,732	27	Title: Online Learning Based Mobile Robot Controller Adaptation for Slip Reduction Abstract: Slip is a very common phenomena present in wheeled mobile robotic systems. It has undesirable consequences such as wasting energy and impeding system stability. To tackle the challenge of mobile robot trajectory tracking under ...	[]	Train
21,733	30	Title: Meta-in-context learning in large language models Abstract: Large language models have shown tremendous performance in a variety of tasks. In-context learning -- the ability to improve at a task after being provided with a number of demonstrations -- is seen as one of the main contributors to their success. In t...	[ 2465, 23171, 21724, 25924 ]	Train
21,734	30	Title: Tri-level Joint Natural Language Understanding for Multi-turn Conversational Datasets Abstract: Natural language understanding typically maps single utterances to a dual level semantic frame, sentence level intent and slot labels at the word level. The best performing models force explicit interaction between in...	[]	Train
21,735	24	Title: Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification Abstract: It is critical that machine learning (ML) model predictions be trustworthy for high-throughput catalyst discovery approaches. Uncertainty quantification (UQ) methods allow esti...	[]	Train
21,736	30	Title: What makes a language easy to deep-learn? Abstract: Neural networks drive the success of natural language processing. A fundamental property of natural languages is their compositional structure, allowing us to describe new meanings systematically. However, neural networks notoriously struggle with systematic ge...	[]	Train
21,737	28	Title: Grouping Method for mmWave Massive MIMO System: Exploitation of Angular Multiplexing Gain Abstract: A future millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) system may serve hundreds or thousands of users at the same time; thus, research on multiple access technology is particularly im...	[]	Test
21,738	28	Title: Computation of Reliability Statistics for Finite Samples of Success-Failure Experiments Abstract: Computational method for statistical measures of reliability, confidence, and assurance are available for infinite population size. If the population size is finite and small compared to the number of samples tested...	[]	Train
21,739	30	Title: Phoenix: Democratizing ChatGPT across Languages Abstract: This paper presents our efforts to democratize ChatGPT across language. We release a large language model"Phoenix", achieving competitive performance among open-source English and Chinese models while excelling in languages with limited resources (coverin...	[ 13345, 867, 13700, 35621, 4902, 10598, 21706, 39639, 27537, 45138, 34963, 2102, 41782, 634, 25853, 43930 ]	Train
21,740	4	Title: Are Current CCPA Compliant Banners Conveying User's Desired Opt-Out Decisions? An Empirical Study of Cookie Consent Banners Abstract: The California Consumer Privacy Act (CCPA) secures the right to Opt-Out for consumers in California. However, websites may implement complex consent mechanisms that potentially do...	[]	Train
21,741	15	Title: PALS: Distributed Gradient Clocking on Chip Abstract: Consider an arbitrary network of communicating modules on a chip, each requiring a local signal telling it when to execute a computational step. There are three common solutions to generating such a local clock signal: (i) by deriving it from a single, centra...	[]	Train
21,742	10	Title: Sport Task: Fine Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2022 Abstract: Sports video analysis is a widespread research topic. Its applications are very diverse, like events detection during a match, video summary, or fine-grained movement analysis of athletes...	[ 26695 ]	Train
21,743	24	Title: Divide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems Abstract: Federated Learning (FL) is a privacy-preserving distributed machine learning approach geared towards applications in edge devices. However, the problem of designing custom neural architectures in federated environments...	[]	Test
21,744	27	Title: Globally Guided Trajectory Planning in Dynamic Environments Abstract: Navigating mobile robots through environments shared with humans is challenging. From the perspective of the robot, humans are dynamic obstacles that must be avoided. These obstacles make the collision-free space nonconvex, which leads to two ...	[]	Validation
21,745	27	Title: CHSEL: Producing Diverse Plausible Pose Estimates from Contact and Free Space Data Abstract: This paper proposes a novel method for estimating the set of plausible poses of a rigid object from a set of points with volumetric information, such as whether each point is in free space or on the surface of the object...	[]	Train
21,746	30	Title: Chatbot Application to Support Smart Agriculture in Thailand Abstract: A chatbot is a software developed to help reply to text or voice conversations automatically and quickly in real time. In the agriculture sector, the existing smart agriculture systems just use data from sensing and internet of things (IoT) t...	[]	Train
21,747	24	Title: Intelligent gradient amplification for deep neural networks Abstract: Deep learning models offer superior performance compared to other machine learning techniques for a variety of tasks and domains, but pose their own challenges. In particular, deep learning models require larger training times as the depth of ...	[]	Train
21,748	16	Title: Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation Abstract: Deep neural networks have made huge progress in the last few decades. However, as the real-world data often exhibits a long-tailed distribution, vanilla deep models tend to be heavily biased toward the majority ...	[ 36810, 33523 ]	Train
21,749	28	Title: Codes and Orbit Covers of Finite Abelian Groups Abstract: It is well known that the discrete analogue of a lattice is a linear code which is a vector subspace of Hamming space $\mathbb{F}^n$. The set $\mathbb{F}$ is a finite field and $n \in \mathbb{Z}_{>0}$. Our attempt is to construct a class of lattices such ...	[]	Test
21,750	10	Title: Dynamic fairness-aware recommendation through multi-agent social choice Abstract: Algorithmic fairness in the context of personalized recommendation presents significantly different challenges to those commonly encountered in classification tasks. Researchers studying classification have generally considered fai...	[]	Train
21,751	20	Title: The Lawn Mowing Problem: From Algebra to Algorithms Abstract: For a given polygonal region $P$, the Lawn Mowing Problem (LMP) asks for a shortest tour $T$ that gets within Euclidean distance 1/2 of every point in $P$; this is equivalent to computing a shortest tour for a unit-diameter cutter $C$ that covers all ...	[]	Train
21,752	24	Title: Multivariate Time-Series Anomaly Detection with Contaminated Data: Application to Physiological Signals Abstract: Mainstream unsupervised anomaly detection algorithms often excel in academic datasets, yet their real-world performance is restricted due to the controlled experimental conditions involving clean tra...	[ 2969 ]	Test
21,753	24	Title: The Responsibility Problem in Neural Networks with Unordered Targets Abstract: We discuss the discontinuities that arise when mapping unordered objects to neural network outputs of fixed permutation, referred to as the responsibility problem. Prior work has proved the existence of the issue by identifying a sing...	[]	Train
21,754	16	Title: Object Detection performance variation on compressed satellite image datasets with iquaflow Abstract: A lot of work has been done to reach the best possible performance of predictive models on images. There are fewer studies about the resilience of these models when they are trained on image datasets that suffer...	[]	Train
21,755	16	Title: Designing Deep Networks for Scene Recognition Abstract: Most deep learning backbones are evaluated on ImageNet. Using scenery images as an example, we conducted extensive experiments to demonstrate the widely accepted principles in network design may result in dramatic performance differences when the data is al...	[]	Train
21,756	11	Title: On Computing Universal Plans for Partially Observable Multi-Agent Path Finding Abstract: Multi-agent routing problems have drawn significant attention nowadays due to their broad industrial applications in, e.g., warehouse robots, logistics automation, and traffic control. Conventionally, they are modelled as cl...	[]	Validation
21,757	16	Title: DANI-Net: Uncalibrated Photometric Stereo by Differentiable Shadow Handling, Anisotropic Reflectance Modeling, and Neural Inverse Rendering Abstract: Uncalibrated photometric stereo (UPS) is challenging due to the inherent ambiguity brought by the unknown light. Although the ambiguity is alleviated on non-Lamber...	[]	Train
21,758	16	Title: SC-VAE: Sparse Coding-based Variational Autoencoder Abstract: Learning rich data representations from unlabeled data is a key challenge towards applying deep learning algorithms in downstream supervised tasks. Several variants of variational autoencoders have been proposed to learn compact data representaitons b...	[]	Test
21,759	23	Title: An Empirical Comparison of Pre-Trained Models of Source Code Abstract: While a large number of pre-trained models of source code have been successfully developed and applied to a variety of software engineering (SE) tasks in recent years, our understanding of these pre-trained models is arguably fairly limited. ...	[ 34243, 46052, 8456, 24329, 14285, 26997, 7611, 34493, 19646 ]	Train
21,760	24	Title: Learning Stochastic Dynamical Systems as an Implicit Regularization with Graph Neural Networks Abstract: Stochastic Gumbel graph networks are proposed to learn high-dimensional time series, where the observed dimensions are often spatially correlated. To that end, the observed randomness and spatial-correlations...	[]	Train
21,761	30	Title: Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors Abstract: Recent work has shown that fine-tuning large language models (LLMs) on large-scale instruction-following datasets substantially improves their performance on a wide range of NLP tasks, especially in the zero-shot ...	[ 12622, 15598 ]	Train
21,762	25	Title: Hierarchical Network with Decoupled Knowledge Distillation for Speech Emotion Recognition Abstract: The goal of Speech Emotion Recognition (SER) is to enable computers to recognize the emotion category of a given utterance in the same way that humans do. The accuracy of SER is strongly dependent on the validity ...	[]	Train
21,763	10	Title: Towards end-to-end ASP computation Abstract: We propose an end-to-end approach for answer set programming (ASP) and linear algebraically compute stable models satisfying given constraints. The idea is to implement Lin-Zhao's theorem \cite{Lin04} together with constraints directly in vector spaces as numerical mi...	[]	Test
21,764	9	Title: Pseudorandom Generators for Sliding-Window Algorithms Abstract: A sliding-window algorithm of window size $t$ is an algorithm whose current operation depends solely on the last $t$ symbols read. We construct pseudorandom generators (PRGs) for low-space randomized sliding-window algorithms that have access to a b...	[]	Train
21,765	16	Title: LION: Implicit Vision Prompt Tuning Abstract: Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs. Recently, vision prompt learning has provided an economic solution to this problem without fine-tuning the whole large-scale m...	[ 37851, 26089, 13805, 3227, 2525 ]	Train
21,766	27	Title: EMV-LIO: An Efficient Multiple Vision aided LiDAR-Inertial Odometry Abstract: To deal with the degeneration caused by the incomplete constraints of single sensor, multi-sensor fusion strategies especially in LiDAR-vision-inertial fusion area have attracted much interest from both the industry and the research co...	[ 10953 ]	Train
21,767	24	Title: Learning signatures of decision making from many individuals playing the same game Abstract: Human behavior is incredibly complex and the factors that drive decision making-from instinct, to strategy, to biases between individuals-often vary over multiple timescales. In this paper, we design a predictive framewo...	[]	Train
21,768	34	Title: A Simple and Efficient Parallel Laplacian Solver Abstract: A symmetric matrix is called a Laplacian if it has nonpositive off-diagonal entries and zero row sums. Since the seminal work of Spielman and Teng (2004) on solving Laplacian linear systems in nearly linear time, several algorithms have been designed for...	[]	Train
21,769	24	Title: Accelerating Molecular Graph Neural Networks via Knowledge Distillation Abstract: Recent advances in graph neural networks (GNNs) have allowed molecular simulations with accuracy on par with conventional gold-standard methods at a fraction of the computational cost. Nonetheless, as the field has been progressing...	[ 16953 ]	Train
21,770	16	Title: HashCC: Lightweight Method to Improve the Quality of the Camera-less NeRF Scene Generation Abstract: Neural Radiance Fields has become a prominent method of scene generation via view synthesis. A critical requirement for the original algorithm to learn meaningful scene representation is camera pose information f...	[]	Train
21,771	16	Title: K-Planes: Explicit Radiance Fields in Space, Time, and Appearance Abstract: We introduce k-planes, a white-box model for radiance fields in arbitrary dimensions. Our model uses planes to represent a d-dimensional scene, providing a seamless way to go from static (d = 3) to dynamic (d= 4) scenes. This planar fact...	[ 44288, 261, 2950, 11016, 16521, 33036, 30095, 42645, 38959, 21170, 27575, 10810, 15035, 8641, 41282, 21443, 12357, 15944, 18632, 30158, 9565, 3680, 15458, 37352, 1002, 3438 ]	Train
21,772	16	Title: Semi-Supervised Learning in the Few-Shot Zero-Shot Scenario Abstract: Semi-Supervised Learning (SSL) leverages both labeled and unlabeled data to improve model performance. Traditional SSL methods assume that labeled and unlabeled data share the same label space. However, in real-world applications, especially w...	[]	Train
21,773	28	Title: Distributed Computing of Functions of Structured Sources with Helper Side Information Abstract: In this work, we consider the problem of distributed computing of functions of structured sources, focusing on the classical setting of two correlated sources and one user that seeks the outcome of the function while ...	[ 39287 ]	Train
21,774	27	Title: Learning Goal-based Movement via Motivational-based Models in Cognitive Mobile Robots Abstract: Humans have needs motivating their behavior according to intensity and context. However, we also create preferences associated with each action's perceived pleasure, which is susceptible to changes over time. This mak...	[]	Validation
21,775	37	Title: AisLSM: Revolutionizing the Compaction with Asynchronous I/Os for LSM-tree Abstract: The log-structured merge tree (LSM-tree) is widely employed to build key-value (KV) stores. LSM-tree organizes multiple levels in memory and on disk. The compaction of LSM-tree, which is used to redeploy KV pairs between on-disk...	[]	Train
21,776	16	Title: TransCAR: Transformer-based Camera-And-Radar Fusion for 3D Object Detection Abstract: Despite radar's popularity in the automotive industry, for fusion-based 3D object detection, most existing works focus on LiDAR and camera fusion. In this paper, we propose TransCAR, a Transformer-based Camera-And-Radar fusion ...	[ 45767, 28456, 7815, 40403, 40571 ]	Test
21,777	27	Title: End-to-end Lidar-Driven Reinforcement Learning for Autonomous Racing Abstract: Reinforcement Learning (RL) has emerged as a transformative approach in the domains of automation and robotics, offering powerful solutions to complex problems that conventional methods struggle to address. In scenarios where the prob...	[]	Validation

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