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
36,478	27	Title: Visual Contact Pressure Estimation for Grippers in the Wild Abstract: Sensing contact pressure applied by a gripper is useful for autonomous and teleoperated robotic manipulation, but adding tactile sensing to a gripper's surface can be difficult or impractical. If a gripper visibly deforms when forces are appli...	[]	Validation
36,479	33	Title: Timed Partial Order Inference Algorithm Abstract: In this work, we propose the model of timed partial orders (TPOs) for specifying workflow schedules, especially for modeling manufacturing processes. TPOs integrate partial orders over events in a workflow, specifying ``happens-before'' relations, with timing con...	[]	Test
36,480	24	Title: FACT: Federated Adversarial Cross Training Abstract: Federated Learning (FL) facilitates distributed model development to aggregate multiple confidential data sources. The information transfer among clients can be compromised by distributional differences, i.e., by non-i.i.d. data. A particularly challenging sce...	[]	Test
36,481	7	Title: An Anisotropic hp-Adaptation Framework for Ultraweak Discontinuous Petrov-Galerkin Formulations Abstract: In this article, we present a three-dimensional anisotropic $hp$-mesh refinement strategy for ultraweak discontinuous Petrov--Galerkin (DPG) formulations with optimal test functions. The refinement strategy ...	[]	Test
36,482	25	Title: U-DiT TTS: U-Diffusion Vision Transformer for Text-to-Speech Abstract: Deep learning has led to considerable advances in text-to-speech synthesis. Most recently, the adoption of Score-based Generative Models (SGMs), also known as Diffusion Probabilistic Models (DPMs), has gained traction due to their ability to ...	[ 4481, 21778, 8308 ]	Train
36,483	24	Title: Stochastic Interpolants: A Unifying Framework for Flows and Diffusions Abstract: A class of generative models that unifies flow-based and diffusion-based methods is introduced. These models extend the framework proposed in Albergo&Vanden-Eijnden (2023), enabling the use of a broad class of continuous-time stocha...	[ 27715, 32933, 25482, 35083, 43697, 14036, 14421, 6229, 10872, 219 ]	Test
36,484	22	Title: Staged Specifications for Automated Verification of Higher-Order Imperative Programs Abstract: Higher-order functions and imperative references are language features supported by many mainstream languages. Their combination enables the ability to package references to code blocks with the captured state from the...	[]	Test
36,485	16	Title: FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization Abstract: The recent amalgamation of transformer and convolutional designs has led to steady improvements in accuracy and efficiency of the models. In this work, we introduce FastViT, a hybrid vision transformer architecture that obtai...	[ 25400, 20026, 7365, 34693 ]	Validation
36,486	5	Title: The Impact of Space-Filling Curves on Data Movement in Parallel Systems Abstract: Modern computer systems are characterized by deep memory hierarchies, composed of main memory, multiple layers of cache, and other specialized types of memory. In parallel and distributed systems, additional memory layers are added...	[ 19306 ]	Train
36,487	24	Title: Deep Injective Prior for Inverse Scattering Abstract: In electromagnetic inverse scattering, the goal is to reconstruct object permittivity using scattered waves. While deep learning has shown promise as an alternative to iterative solvers, it is primarily used in supervised frameworks which are sensitive to dis...	[]	Train
36,488	24	Title: Full High-Dimensional Intelligible Learning In 2-D Lossless Visualization Space Abstract: This study explores a new methodology for machine learning classification tasks in 2-dimensional visualization space (2-D ML) using Visual knowledge Discovery in lossless General Line Coordinates. It is shown that this is a...	[ 40127 ]	Test
36,489	16	Title: Quality-aware Pretrained Models for Blind Image Quality Assessment Abstract: Blind image quality assessment (BIQA) aims to auto-matically evaluate the perceived quality of a single image, whose performance has been improved by deep learning-based methods in recent years. However, the paucity of labeled data some...	[ 22810, 35844, 33934 ]	Train
36,490	14	Title: Exact and optimal quadratization of nonlinear finite-dimensional non-autonomous dynamical systems Abstract: Quadratization of polynomial and nonpolynomial systems of ordinary differential equations is advantageous in a variety of disciplines, such as systems theory, fluid mechanics, chemical reaction modeling an...	[]	Validation
36,491	16	Title: Kinematic Data-Based Action Segmentation for Surgical Applications Abstract: Action segmentation is a challenging task in high-level process analysis, typically performed on video or kinematic data obtained from various sensors. In the context of surgical procedures, action segmentation is critical for workflow ...	[ 39110 ]	Train
36,492	30	Title: Fine Tuning with Abnormal Examples Abstract: Given the prevalence of crowd sourced labor in creating Natural Language processing datasets, these aforementioned sets have become increasingly large. For instance, the SQUAD dataset currently sits at over 80,000 records. However, because the English language is rath...	[]	Train
36,493	16	Title: DBARF: Deep Bundle-Adjusting Generalizable Neural Radiance Fields Abstract: Recent works such as BARF and GARF can bundle adjust camera poses with neural radiance fields (NeRF) which is based on coordinate-MLPs. Despite the impressive results, these methods cannot be applied to Generalizable NeRFs (GeNeRFs) whic...	[ 3225, 39452, 16735, 6575 ]	Validation
36,494	30	Title: Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing Abstract: The task of text-to-SQL parsing, which aims at converting natural language questions into executable SQL queries, has garnered increasing attention in recent years. One of the major challenges in text-to-SQL par...	[ 867, 24901, 11757, 1233, 19250, 22578, 26393, 23832, 20313 ]	Test
36,495	16	Title: Identifying Interpretable Subspaces in Image Representations Abstract: We propose Automatic Feature Explanation using Contrasting Concepts (FALCON), an interpretability framework to explain features of image representations. For a target feature, FALCON captions its highly activating cropped images using a large...	[ 10624 ]	Train
36,496	24	Title: Viewing the process of generating counterfactuals as a source of knowledge - Application to the Naive Bayes classifier Abstract: There are now many comprehension algorithms for understanding the decisions of a machine learning algorithm. Among these are those based on the generation of counterfactual examples. T...	[]	Train
36,497	30	Title: Sequence-Based Extractive Summarisation for Scientific Articles Abstract: This paper presents the results of research on supervised extractive text summarisation for scientific articles. We show that a simple sequential tagging model based only on the text within a document achieves high results against a simple...	[ 21006, 30166, 18294, 16060, 40158 ]	Test
36,498	30	Title: Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts Abstract: Many cognitive approaches to well-being, such as recognizing and reframing unhelpful thoughts, have received considerable empirical support over the past decades, yet still lack truly widespread adoption in self-help format. A barri...	[]	Train
36,499	4	Title: Effective Ambiguity Attack Against Passport-based DNN Intellectual Property Protection Schemes through Fully Connected Layer Substitution Abstract: Since training a deep neural network (DNN) is costly, the well-trained deep models can be regarded as valuable intellectual property (IP) assets. The IP protection a...	[ 41616 ]	Test
36,500	24	Title: Exploring the Benefits of Differentially Private Pre-training and Parameter-Efficient Fine-tuning for Table Transformers Abstract: For machine learning with tabular data, Table Transformer (TabTransformer) is a state-of-the-art neural network model, while Differential Privacy (DP) is an essential component to en...	[ 16432 ]	Test
36,501	4	Title: Decentralized Threshold Signatures with Dynamically Private Accountability Abstract: Threshold signatures are a fundamental cryptographic primitive used in many practical applications. As proposed by Boneh and Komlo (CRYPTO'22), TAPS is a threshold signature that is a hybrid of privacy and accountability. It ena...	[]	Train
36,502	3	Title: Spatial, Social and Data Gaps in On-Demand Mobility Services: Towards a Supply-Oriented MaaS Abstract: After a decade of on-demand mobility services that change spatial behaviors in metropolitan areas, the Shared Autonomous Vehicle (SAV) service is expected to increase traffic congestion and unequal access to tr...	[]	Test
36,503	4	Title: Counterfeit Chip Detection using Scattering Parameter Analysis Abstract: The increase in the number of counterfeit and recycled microelectronic chips in recent years has created significant security and safety concerns in various applications. Hence, detecting such counterfeit chips in electronic systems is crit...	[ 32168 ]	Train
36,504	3	Title: Are ChatGPT and Other Similar Systems the Modern Lernaean Hydras of AI? Abstract: The rise of Generative Artificial Intelligence systems (``AI systems'') has created unprecedented social engagement. AI code generation systems provide responses (output) to questions or requests by accessing the vast library of op...	[]	Train
36,505	28	Title: ELF Codes: Concatenated Codes with an Expurgating Linear Function as the Outer Code Abstract: An expurgating linear function (ELF) is a linear outer code that disallows the low-weight codewords of the inner code. ELFs can be designed either to maximize the minimum distance or to minimize the codeword error rate ...	[ 14277 ]	Test
36,506	16	Title: Automatic Photo Orientation Detection with Convolutional Neural Networks Abstract: We apply convolutional neural networks (CNN) to the problem of image orientation detection in the context of determining the correct orientation (from 0, 90, 180, and 270 degrees) of a consumer photo. The problem is especially imp...	[ 10687 ]	Test
36,507	28	Title: Component Training of Turbo Autoencoders Abstract: Isolated training with Gaussian priors (TGP) of the component autoencoders of turbo-autoencoder architectures enables faster, more consistent training and better generalization to arbitrary decoding iterations than training based on deep unfolding. We propose fi...	[]	Validation
36,508	24	Title: Diffusion models with location-scale noise Abstract: Diffusion Models (DMs) are powerful generative models that add Gaussian noise to the data and learn to remove it. We wanted to determine which noise distribution (Gaussian or non-Gaussian) led to better generated data in DMs. Since DMs do not work by design wi...	[]	Train
36,509	24	Title: Data-Driven Allocation of Preventive Care With Application to Diabetes Mellitus Type II Abstract: Problem Definition. Increasing costs of healthcare highlight the importance of effective disease prevention. However, decision models for allocating preventive care are lacking. Methodology/Results. In this paper, w...	[ 40443 ]	Test
36,510	23	Title: One Adapter for All Programming Languages? Adapter Tuning for Code Search and Summarization Abstract: As pre-trained models automate many code intel-ligence tasks, a widely used paradigm is to fine-tune a model on the task dataset for each programming language. A recent study reported that multilingual fine-tuni...	[ 1761, 12706 ]	Validation
36,511	38	Title: FAIR Begins at home: Implementing FAIR via the Community Data Driven Insights Abstract: Arguments for the FAIR principles have mostly been based on appeals to values. However, the work of onboarding diverse researchers to make efficient and effective implementations of FAIR requires different appeals. In our rec...	[]	Train
36,512	6	Title: "It Felt Like Having a Second Mind": Investigating Human-AI Co-creativity in Prewriting with Large Language Models Abstract: Prewriting is the process of discovering and developing ideas before a first draft, which requires divergent thinking and often implies unstructured strategies such as diagramming, outlini...	[]	Train
36,513	24	Title: Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks Abstract: Multi-armed bandits are extensively used to model sequential decision-making, making them ubiquitous in many real-life applications such as online recommender systems and wireless networking. We consider a m...	[ 3153, 20730 ]	Train
36,514	4	Title: BarrierBypass: Out-of-Sight Clean Voice Command Injection Attacks through Physical Barriers Abstract: The growing adoption of voice-enabled devices (e.g., smart speakers), particularly in smart home environments, has introduced many security vulnerabilities that pose significant threats to users' privacy and saf...	[]	Test
36,515	24	Title: Confidence-Based Feature Imputation for Graphs with Partially Known Features Abstract: This paper investigates a missing feature imputation problem for graph learning tasks. Several methods have previously addressed learning tasks on graphs with missing features. However, in cases of high rates of missing featur...	[]	Validation
36,516	30	Title: Towards Multilingual Automatic Dialogue Evaluation Abstract: The main limiting factor in the development of robust multilingual dialogue evaluation metrics is the lack of multilingual data and the limited availability of open sourced multilingual dialogue systems. In this work, we propose a workaround for this l...	[]	Train
36,517	10	Title: Nemo: First Glimpse of a New Rule Engine Abstract: This system demonstration presents Nemo, a new logic programming engine with a focus on reliability and performance. Nemo is built for data-centric analytic computations, modelled in a fully declarative Datalog dialect. Its scalability for these tasks matches or...	[ 559 ]	Validation
36,518	30	Title: Comparison between parameter-efficient techniques and full fine-tuning: A case study on multilingual news article classification Abstract: Adapters and Low-Rank Adaptation (LoRA) are parameter-efficient fine-tuning techniques designed to make the training of language models more efficient. Previous results demon...	[ 44482, 6765, 8949, 5815, 505 ]	Train
36,519	30	Title: Sentiment Analysis on YouTube Smart Phone Unboxing Video Reviews in Sri Lanka Abstract: Product-related reviews are based on users’ experiences that are mostly shared on videos in YouTube. It is the second most popular website globally in 2021. People prefer to watch videos on recently released products prior to...	[]	Test
36,520	16	Title: Video-Specific Query-Key Attention Modeling for Weakly-Supervised Temporal Action Localization Abstract: Weakly-supervised temporal action localization aims to identify and localize the action instances in the untrimmed videos with only video-level action labels. When humans watch videos, we can adapt our abstra...	[]	Test
36,521	16	Title: SAGE-NDVI: A Stereotype-Breaking Evaluation Metric for Remote Sensing Image Dehazing Using Satellite-to-Ground NDVI Knowledge Abstract: Image dehazing is a meaningful low-level computer vision task and can be applied to a variety of contexts. In our industrial deployment scenario based on remote sensing (RS) ima...	[]	Train
36,522	16	Title: Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images Abstract: Weird, unusual, and uncanny images pique the curiosity of observers because they challenge commonsense. For example, an image released during the 2022 world cup depicts the famous soccer stars Lionel Me...	[ 10624, 30243, 33220, 37987, 25226, 11628, 15278, 41104, 43641, 19578, 37979, 27454 ]	Train
36,523	16	Title: Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection Abstract: This paper aims for high-performance offline LiDAR-based 3D object detection. We first observe that experienced human annotators annotate objects from a track-centric perspective. They first label the obj...	[ 30113, 40674, 12581, 8615, 36174, 4980, 34804, 45087 ]	Validation
36,524	16	Title: Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics Abstract: Text-to-image generation models represent the next step of evolution in image synthesis, offering a natural way to achieve flexible yet fine-grained control over the result. One emerging area of research is the ...	[ 24763, 10788, 16015 ]	Train
36,525	30	Title: Fountain - an intelligent contextual assistant combining knowledge representation and language models for manufacturing risk identification Abstract: Deviations from the approved design or processes during mass production can lead to unforeseen risks. However, these changes are sometimes necessary due to changes...	[]	Validation
36,526	16	Title: On the Biometric Capacity of Generative Face Models Abstract: There has been tremendous progress in generating realistic faces with high fidelity over the past few years. Despite this progress, a crucial question remains unanswered:"Given a generative face model, how many unique identities can it generate?"In ot...	[]	Train
36,527	16	Title: Towards Better Gradient Consistency for Neural Signed Distance Functions via Level Set Alignment Abstract: Neural signed distance functions (SDFs) have shown remarkable capability in representing geometry with details. However, without signed distance supervision, it is still a challenge to infer SDFs from point...	[ 17217, 8004, 40717, 14255 ]	Train
36,528	30	Title: Theory of Mind Might Have Spontaneously Emerged in Large Language Models Abstract: We explore the intriguing possibility that theory of mind (ToM), or the uniquely human ability to impute unobservable mental states to others, might have spontaneously emerged in large language models (LLMs). We designed 40 false-...	[ 40192, 39170, 20228, 40966, 6535, 44173, 5522, 37522, 30356, 45847, 21401, 7585, 9892, 2475, 10923, 16429, 4270, 42287, 8115, 19252, 13882, 23236, 16837, 33220, 12487, 45127, 43593, 5707, 17099, 23371, 30668, 8536, 21724, 39778, 10981, 26981, 2...	Train
36,529	16	Title: Mutual Query Network for Multi-Modal Product Image Segmentation Abstract: Product image segmentation is vital in e-commerce. Most existing methods extract the product image foreground only based on the visual modality, making it difficult to distinguish irrelevant products. As product titles contain abundant app...	[]	Train
36,530	16	Title: Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train Abstract: Foundation models have exhibited remarkable success in various applications, such as disease diagnosis and text report generation. To date, a foundation model for endoscopic video analysis is still lacking. In this ...	[]	Test
36,531	23	Title: Analysis of Software Engineering Practices in General Software and Machine Learning Startups Abstract: Context: On top of the inherent challenges startup software companies face applying proper software engineering practices, the non-deterministic nature of machine learning techniques makes it even more difficul...	[ 42363, 5018, 14267, 36975 ]	Train
36,532	16	Title: Hyperspectral Target Detection Based on Low-Rank Background Subspace Learning and Graph Laplacian Regularization Abstract: Hyperspectral target detection is good at finding dim and small objects based on spectral characteristics. However, existing representation-based methods are hindered by the problem of the u...	[]	Validation
36,533	37	Title: BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs Abstract: Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge graphs can easily represent heterogeneous types of information, and many algorithms and tools exist f...	[]	Train
36,534	23	Title: Debugging Flaky Tests using Spectrum-based Fault Localization Abstract: Non-deterministically behaving (i.e., flaky) tests hamper regression testing as they destroy trust and waste computational and human resources. Eradicating flakiness in test suites is therefore an important goal, but automated debugging tool...	[]	Train
36,535	24	Title: Sample Complexity of Kernel-Based Q-Learning Abstract: Modern reinforcement learning (RL) often faces an enormous state-action space. Existing analytical results are typically for settings with a small number of state-actions, or simple models such as linearly modeled Q-functions. To derive statistically efficie...	[]	Test
36,536	32	Title: SYCL compute kernels for ExaHyPE Abstract: We discuss three SYCL realisations of a simple Finite Volume scheme over multiple Cartesian patches. The realisation flavours differ in the way how they map the compute steps onto loops and tasks: We compare an implementation which is exclusively using a cascade of for-...	[]	Train
36,537	24	Title: Unified Molecular Modeling via Modality Blending Abstract: Self-supervised molecular representation learning is critical for molecule-based tasks such as AI-assisted drug discovery. Recent studies consider leveraging both 2D and 3D information for representation learning, with straightforward alignment strategie...	[ 21857, 38858, 40133 ]	Train
36,538	13	Title: RAMAN: A Re-configurable and Sparse tinyML Accelerator for Inference on Edge Abstract: Deep Neural Network (DNN) based inference at the edge is challenging as these compute and data-intensive algorithms need to be implemented at low cost and low power while meeting the latency constraints of the target applicati...	[]	Train
36,539	20	Title: Robust Estimation of Surface Curvature Information from Point Cloud Data Abstract: This paper surveys and evaluates some popular state of the art methods for algorithmic curvature and normal estimation. In addition to surveying existing methods we also propose a new method for robust curvature estimation and eva...	[]	Train
36,540	24	Title: Multiplicative update rules for accelerating deep learning training and increasing robustness Abstract: Even nowadays, where Deep Learning (DL) has achieved state-of-the-art performance in a wide range of research domains, accelerating training and building robust DL models remains a challenging task. To this en...	[]	Test
36,541	2	Title: Algebraic Semantics of Datalog with Equality Abstract: We discuss the syntax and semantics of relational Horn logic (RHL) and partial Horn logic (PHL). RHL is an extension of the Datalog programming language that allows introducing and equating variables in conclusions. PHL is a syntactic extension of RHL by par...	[ 4248, 21479 ]	Validation
36,542	24	Title: Boosting Neural Networks to Decompile Optimized Binaries Abstract: Decompilation aims to transform a low-level program language (LPL) (eg., binary file) into its functionally-equivalent high-level program language (HPL) (e.g., C/C++). It is a core technology in software security, especially in vulnerability disc...	[]	Train
36,543	30	Title: Resources and Few-shot Learners for In-context Learning in Slavic Languages Abstract: Despite the rapid recent progress in creating accurate and compact in-context learners, most recent work focuses on in-context learning (ICL) for tasks in English. However, the ability to interact with users of languages outsid...	[ 23447 ]	Train
36,544	25	Title: The Biased Journey of MSD_AUDIO.ZIP Abstract: The equitable distribution of academic data is crucial for ensuring equal research opportunities, and ultimately further progress. Yet, due to the complexity of using the API for audio data that corresponds to the Million Song Dataset along with its misreporting (bef...	[]	Test
36,545	30	Title: Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data? Abstract: Despite the power of Large Language Models (LLMs) like GPT-4, they still struggle with tasks that require generating complex, structured outputs. In this study, we assess the capability of Current LLMs in generati...	[ 12128, 17889, 32097, 45018, 14920, 26091, 45582, 37809, 19671, 8794 ]	Validation
36,546	16	Title: EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices Abstract: Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually resource-constrained, edge deep neural networks (DNNs) have fewer weights and shallower architectures than ge...	[ 13204, 13759 ]	Test
36,547	30	Title: Zero-shot Clinical Entity Recognition using ChatGPT Abstract: In this study, we investigated the potential of ChatGPT, a large language model developed by OpenAI, for the clinical named entity recognition task defined in the 2010 i2b2 challenge, in a zero-shot setting with two different prompt strategies. We com...	[ 35234, 30787, 35883, 38575, 10224, 26357, 16598, 23127, 23512, 10681, 30775, 35580, 8286 ]	Validation
36,548	16	Title: Explaining Deep Models Through Forgettable Learning Dynamics Abstract: Even though deep neural networks have shown tremendous success in countless applications, explaining model behaviour or predictions is an open research problem. In this paper, we address this issue by employing a simple yet effective method b...	[ 16288, 18225, 2366 ]	Train
36,549	27	Title: Selective Communication for Cooperative Perception in End-to-End Autonomous Driving Abstract: The reliability of current autonomous driving systems is often jeopardized in situations when the vehicle's field-of-view is limited by nearby occluding objects. To mitigate this problem, vehicle-to-vehicle communicatio...	[ 10265, 44574 ]	Test
36,550	4	Title: Towards Autonomous Cyber Operation Agents: Exploring the Red Case Abstract: Recently, reinforcement and deep reinforcement learning (RL/DRL) have been applied to develop autonomous agents for cyber network operations(CyOps), where the agents are trained in a representative environment using RL and particularly D...	[ 31305, 44678, 24462 ]	Train
36,551	16	Title: MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds Abstract: 3D semantic segmentation on multi-scan large-scale point clouds plays an important role in autonomous systems. Unlike the single-scan-based semantic segmentation task, this task requires distinguishing th...	[ 23617, 19716 ]	Train
36,552	25	Title: Multi-perspective Information Fusion Res2Net with RandomSpecmix for Fake Speech Detection Abstract: In this paper, we propose the multi-perspective information fusion (MPIF) Res2Net with random Specmix for fake speech detection (FSD). The main purpose of this system is to improve the model's ability to learn pre...	[ 21813 ]	Train
36,553	16	Title: Self-Supervised Multi-Object Tracking From Consistency Across Timescales Abstract: Self-supervised multi-object trackers have the potential to leverage the vast amounts of raw data recorded worldwide. However, they still fall short in re-identification accuracy compared to their supervised counterparts. We hypot...	[ 30347 ]	Test
36,554	23	Title: On Using Information Retrieval to Recommend Machine Learning Good Practices for Software Engineers Abstract: Machine learning (ML) is nowadays widely used for different purposes and in several disciplines. From self-driving cars to automated medical diagnosis, machine learning models extensively support users' d...	[ 22334, 13700, 8238, 22775 ]	Test
36,555	27	Title: An Explicit Method for Fast Monocular Depth Recovery in Corridor Environments Abstract: Monocular cameras are extensively employed in indoor robotics, but their performance is limited in visual odometry, depth estimation, and related applications due to the absence of scale information.Depth estimation refers to...	[]	Train
36,556	30	Title: Continual Learning with Dirichlet Generative-based Rehearsal Abstract: Recent advancements in data-driven task-oriented dialogue systems (ToDs) struggle with incremental learning due to computational constraints and time-consuming issues. Continual Learning (CL) attempts to solve this by avoiding intensive pre-t...	[ 7264 ]	Test
36,557	24	Title: SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models Abstract: The pre-training and fine-tuning paradigm has contributed to a number of breakthroughs in Natural Language Processing (NLP). Instead of directly training on a downstream task, language models are first pre-trained on large datase...	[ 16960, 21481 ]	Validation
36,558	24	Title: Transfer learning for process design with reinforcement learning Abstract: Process design is a creative task that is currently performed manually by engineers. Artificial intelligence provides new potential to facilitate process design. Specifically, reinforcement learning (RL) has shown some success in automati...	[ 19846 ]	Test
36,559	16	Title: AffineGlue: Joint Matching and Robust Estimation Abstract: We propose AffineGlue, a method for joint two-view feature matching and robust estimation that reduces the combinatorial complexity of the problem by employing single-point minimal solvers. AffineGlue selects potential matches from one-to-many correspond...	[]	Test
36,560	24	Title: Implicit bias of SGD in L2-regularized linear DNNs: One-way jumps from high to low rank Abstract: The $L_{2}$-regularized loss of Deep Linear Networks (DLNs) with more than one hidden layers has multiple local minima, corresponding to matrices with different ranks. In tasks such as matrix completion, the goal is...	[ 45210, 44743 ]	Test
36,561	24	Title: Improved sampling via learned diffusions Abstract: Recently, a series of papers proposed deep learning-based approaches to sample from unnormalized target densities using controlled diffusion processes. In this work, we identify these approaches as special cases of the Schr\"odinger bridge problem, seeking the m...	[ 14401 ]	Train
36,562	24	Title: Temporal Gradient Inversion Attacks with Robust Optimization Abstract: Federated Learning (FL) has emerged as a promising approach for collaborative model training without sharing private data. However, privacy concerns regarding information exchanged during FL have received significant research attention. Gradi...	[ 23682 ]	Test
36,563	10	Title: MetaGPT: Meta Programming for Multi-Agent Collaborative Framework Abstract: Recently, remarkable progress has been made in automated task-solving through the use of multi-agent driven by large language models (LLMs). However, existing LLM-based multi-agent works primarily focus on solving simple dialogue tasks, ...	[ 770, 16912, 5522, 14740, 30624, 9379, 16556, 24238, 8892, 33477, 2506, 34637, 15952, 18007, 3162, 39773, 2549, 1528, 634 ]	Validation
36,564	24	Title: An Empirical Study on Google Research Football Multi-agent Scenarios Abstract: Few multi-agent reinforcement learning (MARL) research on Google Research Football (GRF) focus on the 11v11 multi-agent full-game scenario and to the best of our knowledge, no open benchmark on this scenario has been released to the p...	[]	Test
36,565	30	Title: Decoding Emotions: A comprehensive Multilingual Study of Speech Models for Speech Emotion Recognition Abstract: Recent advancements in transformer-based speech representation models have greatly transformed speech processing. However, there has been limited research conducted on evaluating these models for speec...	[ 10203 ]	Test
36,566	16	Title: Prompt Ensemble Self-training for Open-Vocabulary Domain Adaptation Abstract: Traditional domain adaptation assumes the same vocabulary across source and target domains, which often struggles with limited transfer flexibility and efficiency while handling target domains with different vocabularies. Inspired by r...	[]	Test
36,567	26	Title: Why Rumors Spread Fast in Social Networks, and How to Stop It Abstract: We study a rumor spreading model where individuals are connected via a network structure. Initially, only a small subset of the individuals are spreading a rumor. Each individual who is connected to a spreader, starts spreading the rumor wit...	[]	Validation
36,568	22	Title: Modularity and Separate Compilation in Logic Programming Abstract: The ability to compose code in a modular fashion is important to the construction of large programs. In the logic programming setting, it is desirable that such capabilities be realized through logic-based devices. We describe an approach for doi...	[]	Test
36,569	24	Title: G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks Abstract: It has become a popular paradigm to transfer the knowledge of large-scale pre-trained models to various downstream tasks via fine-tuning the entire model parameters. However, with the growth of model...	[ 38747, 13700, 32176, 2801, 31158, 32635, 23805, 37919 ]	Train
36,570	16	Title: DAOT: Domain-Agnostically Aligned Optimal Transport for Domain-Adaptive Crowd Counting Abstract: Domain adaptation is commonly employed in crowd counting to bridge the domain gaps between different datasets. However, existing domain adaptation methods tend to focus on inter-dataset differences while overlooking ...	[]	Train
36,571	23	Title: Improving students' code correctness and test completeness by informal specifications Abstract: The quality of software produced by students is often poor. How to teach students to develop good quality software has long been a topic in computer science education and research. We must conclude that we still do no...	[]	Validation
36,572	2	Title: Computational philosophy of science Abstract: Philosophy of science attempts to describe all parts of the scientific process in a general way in order to facilitate the description, execution and improvements of this process. So far, all proposed philosophies have only covered existing processes and disciplines ...	[]	Validation
36,573	3	Title: An Empirical Analysis of Racial Categories in the Algorithmic Fairness Literature Abstract: Recent work in algorithmic fairness has highlighted the challenge of defining racial categories for the purposes of anti-discrimination. These challenges are not new but have previously fallen to the state, which enacts r...	[]	Train
36,574	20	Title: Scenic Routes over Points in 2D Space Abstract: Consider a 2D coordinate space with a set of red and a set of blue points. We define a scenic point as a point that is equidistant to a red point and a blue point. The set of contiguous scenic points form a scenic path. The perpendicular bisectors to the line joini...	[ 1908 ]	Train
36,575	16	Title: Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection Abstract: Out-of-distribution (OOD) detection can be used in deep learning-based applications to reject outlier samples from being unreliably classified by deep neural networks. Learning to classify between OOD and in-distributi...	[]	Train
36,576	24	Title: COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search Abstract: The sparse Mixture-of-Experts (Sparse-MoE) framework efficiently scales up model capacity in various domains, such as natural language processing and vision. Sparse-MoEs select a subset of the "experts" (thus, only a...	[]	Test
36,577	16	Title: CrossKD: Cross-Head Knowledge Distillation for Dense Object Detection Abstract: Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation, which ...	[ 35773 ]	Validation

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