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
19,578	16	Title: LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models Abstract: Large Vision-Language Models (LVLMs) have recently played a dominant role in multimodal vision-language learning. Despite the great success, it lacks a holistic evaluation of their efficacy. This paper presents a comprehen...	[ 10624, 13700, 30472, 25226, 41104, 4251, 32796, 22432, 13345, 30243, 36522, 14126, 29999, 15413, 39733, 3003, 8509, 37438, 5700, 9927, 14923, 7633, 36689, 26577, 13408, 10978, 37987, 42983, 1900, 11628, 16878, 13935, 6770, 19066 ]	Validation
19,579	4	Title: An AI-Driven VM Threat Prediction Model for Multi-Risks Analysis-Based Cloud Cybersecurity Abstract: Cloud virtualization technology, ingrained with physical resource sharing, prompts cybersecurity threats on users' virtual machines (VM)s due to the presence of inevitable vulnerabilities on the offsite servers. ...	[ 40421 ]	Train
19,580	10	Title: Transferable Curricula through Difficulty Conditioned Generators Abstract: Advancements in reinforcement learning (RL) have demonstrated superhuman performance in complex tasks such as Starcraft, Go, Chess etc. However, knowledge transfer from Artificial ``Experts" to humans remain a significant challenge. A pro...	[ 38766, 28990 ]	Test
19,581	24	Title: Model-agnostic Measure of Generalization Difficulty Abstract: The measure of a machine learning algorithm is the difficulty of the tasks it can perform, and sufficiently difficult tasks are critical drivers of strong machine learning models. However, quantifying the generalization difficulty of machine learning ...	[]	Train
19,582	24	Title: DCT: Dual Channel Training of Action Embeddings for Reinforcement Learning with Large Discrete Action Spaces Abstract: The ability to learn robust policies while generalizing over large discrete action spaces is an open challenge for intelligent systems, especially in noisy environments that face the curse of di...	[]	Train
19,583	4	Title: Two-in-One: A Model Hijacking Attack Against Text Generation Models Abstract: Machine learning has progressed significantly in various applications ranging from face recognition to text generation. However, its success has been accompanied by different attacks. Recently a new attack has been proposed which raise...	[ 46066, 37499, 21180, 36462 ]	Test
19,584	24	Title: Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook Abstract: For its robust predictive power (compared to pure physics-based models) and sample-efficient training (compared to pure deep learning models), physics-informed deep learning (PIDL), a paradigm hybridizing physics-base...	[ 37600, 23957, 27871 ]	Train
19,585	16	Title: Implicit Diffusion Models for Continuous Super-Resolution Abstract: Image super-resolution (SR) has attracted increasing attention due to its widespread applications. However, current SR methods generally suffer from over-smoothing and artifacts, and most work only with fixed magnifications. This paper introduce...	[ 26145, 17378, 16451, 32395, 45965, 8851, 500, 41695 ]	Train
19,586	24	Title: Dynamics-Aware Loss for Learning with Label Noise Abstract: Label noise poses a serious threat to deep neural networks (DNNs). Employing robust loss functions which reconcile fitting ability with robustness is a simple but effective strategy to handle this problem. However, the widely-used static trade-off betwe...	[]	Train
19,587	28	Title: Analysis of UAV Corridors in Cellular Networks Abstract: In this article, we introduce a new mathematical framework for the analysis and design of UAV corridors in cellular networks, while considering a realistic network deployment, antenna radiation pattern, and propagation channel model. By leveraging quantiza...	[ 32007 ]	Train
19,588	3	Title: Introducing Political Ecology of Creative-Ai Abstract: (150 words) This chapter introduces the perspective of political ecology to the application of artificial intelligence to artistic processes (Creative-Ai). Hence, the environmental and social impact of the development and employment of Creative-Ai are the fo...	[]	Train
19,589	24	Title: G-NM: A Group of Numerical Time Series Prediction Models Abstract: In this study, we focus on the development and implementation of a comprehensive ensemble of numerical time series forecasting models, collectively referred to as the Group of Numerical Time Series Prediction Model (G-NM). This inclusive set comp...	[]	Test
19,590	16	Title: Evaluating 3D Shape Analysis Methods for Robustness to Rotation Invariance Abstract: This paper analyzes the robustness of recent 3D shape descriptors to SO(3) rotations, something that is fundamental to shape modeling. Specifically, we formulate the task of rotated 3D object instance detection. To do so, we con...	[ 19320 ]	Train
19,591	16	Title: RFAConv: Innovating Spatial Attention and Standard Convolutional Operation Abstract: Spatial attention has been widely used to improve the performance of convolutional neural networks. However, it has certain limitations. In this paper, we propose a new perspective on the effectiveness of spatial attention, whic...	[]	Train
19,592	30	Title: OpenPI-C: A Better Benchmark and Stronger Baseline for Open-Vocabulary State Tracking Abstract: Open-vocabulary state tracking is a more practical version of state tracking that aims to track state changes of entities throughout a process without restricting the state space and entity space. OpenPI is to date th...	[]	Train
19,593	30	Title: AGIBench: A Multi-granularity, Multimodal, Human-referenced, Auto-scoring Benchmark for Large Language Models Abstract: Large language models (LLMs) like ChatGPT have revealed amazing intelligence. How to evaluate the question-solving abilities of LLMs and their degrees of intelligence is a hot-spot but challeng...	[ 13510, 1575, 7695, 29430, 9403 ]	Train
19,594	24	Title: Hiding Backdoors within Event Sequence Data via Poisoning Attacks Abstract: The financial industry relies on deep learning models for making important decisions. This adoption brings new danger, as deep black-box models are known to be vulnerable to adversarial attacks. In computer vision, one can shape the outp...	[ 40192, 11273, 13700 ]	Train
19,595	16	Title: AlteredAvatar: Stylizing Dynamic 3D Avatars with Fast Style Adaptation Abstract: This paper presents a method that can quickly adapt dynamic 3D avatars to arbitrary text descriptions of novel styles. Among existing approaches for avatar stylization, direct optimization methods can produce excellent results for a...	[ 2005, 541 ]	Train
19,596	27	Title: Towards Standardized Disturbance Rejection Testing of Legged Robot Locomotion with Linear Impactor: A Preliminary Study, Observations, and Implications Abstract: Dynamic locomotion in legged robots is close to industrial collaboration, but a lack of standardized testing obstructs commercialization. The issues ar...	[ 37014 ]	Validation
19,597	23	Title: A Verification Framework for Component Based Modeling and Simulation : "Putting the pieces together" Abstract: The discipline of component-based modeling and simulation offers promising gains including reduction in development cost, time, and system complexity. This paradigm is very profitable as it promote ...	[]	Validation
19,598	16	Title: VisoGender: A dataset for benchmarking gender bias in image-text pronoun resolution Abstract: We introduce VisoGender, a novel dataset for benchmarking gender bias in vision-language models. We focus on occupation-related gender biases, inspired by Winograd and Winogender schemas, where each image is associated ...	[ 8084 ]	Validation
19,599	16	Title: No Data Augmentation? Alternative Regularizations for Effective Training on Small Datasets Abstract: Solving image classification tasks given small training datasets remains an open challenge for modern computer vision. Aggressive data augmentation and generative models are among the most straightforward approac...	[ 5009, 43423 ]	Train
19,600	30	Title: Data Selection for Fine-tuning Large Language Models Using Transferred Shapley Values Abstract: This paper proposes a sampling chain based method to make Shapley values computationally feasible for data valuation and selection for large language models.	[]	Train
19,601	5	Title: Boosting the Performance of Object Tracking with a Half-Precision Particle Filter on GPU Abstract: High-performance GPU-accelerated particle filter methods are critical for object detection applications, ranging from autonomous driving, robot localization, to time-series prediction. In this work, we investigate ...	[]	Test
19,602	16	Title: Read, look and detect: Bounding box annotation from image-caption pairs Abstract: Various methods have been proposed to detect objects while reducing the cost of data annotation. For instance, weakly supervised object detection (WSOD) methods rely only on image-level annotations during training. Unfortunately, d...	[]	Train
19,603	20	Title: Folding Every Point on a Polygon Boundary to a Point Abstract: We consider a problem in computational origami. Given a piece of paper as a convex polygon P and a point f located within, we fold every point on a boundary of P to f and compute a region that is safe from folding, i.e., the region with no creases. T...	[]	Train
19,604	33	Title: Remarks on Parikh-recognizable omega-languages Abstract: Several variants of Parikh automata on infinite words were recently introduced by Guha et al. [FSTTCS, 2022]. We show that one of these variants coincides with blind counter machine as introduced by Fernau and Stiebe [Fundamenta Informaticae, 2008]. Fernau...	[ 27393, 16468, 39374 ]	Train
19,605	23	Title: Robust Failure Diagnosis of Microservice System through Multimodal Data Abstract: Automatic failure diagnosis is crucial for large microservice systems. Currently, most failure diagnosis methods rely solely on single-modal data (i.e., using either metrics, logs, or traces). In this study, we conduct an empirical...	[ 8677 ]	Train
19,606	24	Title: eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-stationary Data (Student Abstract) Abstract: Conventional temporal causal discovery (CD) methods suffer from high dimensionality, fail to identify lagged causal relationships, and often ignore dynamics in relations. In this study, we present...	[]	Train
19,607	16	Title: AdvBiom: Adversarial Attacks on Biometric Matchers Abstract: With the advent of deep learning models, face recognition systems have achieved impressive recognition rates. The workhorses behind this success are Convolutional Neural Networks (CNNs) and the availability of large training datasets. However, we show ...	[]	Validation
19,608	5	Title: Robust and Listening-Efficient Contention Resolution Abstract: This paper shows how to achieve contention resolution on a shared communication channel using only a small number of channel accesses -- both for listening and sending -- and the resulting algorithm is resistant to adversarial noise. The shared chann...	[]	Test
19,609	24	Title: Hybrid Zonotopes Exactly Represent ReLU Neural Networks Abstract: We show that hybrid zonotopes offer an equivalent representation of feed-forward fully connected neural networks with ReLU activation functions. Our approach demonstrates that the complexity of binary variables is equal to the total number of neur...	[]	Test
19,610	24	Title: SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking Abstract: Generative graph self-supervised learning (SSL) aims to learn node representations by reconstructing the input graph data. However, most existing methods focus on unsupervised learning tasks only and very few work has s...	[ 7552 ]	Test
19,611	27	Title: Group-k consistent measurement set maximization via maximum clique over k-Uniform hypergraphs for robust multi-robot map merging Abstract: This paper unifies the theory of consistent-set maximization for robust outlier detection in a simultaneous localization and mapping framework. We first describe the notion o...	[ 13417 ]	Train
19,612	24	Title: Active Learning of Piecewise Gaussian Process Surrogates Abstract: Active learning of Gaussian process (GP) surrogates has been useful for optimizing experimental designs for physical/computer simulation experiments, and for steering data acquisition schemes in machine learning. In this paper, we develop a metho...	[]	Validation
19,613	16	Title: Image Labels Are All You Need for Coarse Seagrass Segmentation Abstract: Seagrass meadows serve as critical carbon sinks, but estimating the amount of carbon they store requires knowledge of the seagrass species present. Underwater and surface vehicles equipped with machine learning algorithms can help to accura...	[]	Train
19,614	6	Title: Chat2VIS: Generating Data Visualizations via Natural Language Using ChatGPT, Codex and GPT-3 Large Language Models Abstract: The field of data visualisation has long aimed to devise solutions for generating visualisations directly from natural language text. Research in Natural Language Interfaces (NLIs) has con...	[ 12487, 329, 11273, 14007, 15530, 43566, 39823, 26647, 5493, 11190, 13239, 13721, 25821 ]	Test
19,615	23	Title: Redrafting Requirements Modeling Using a Single Multilevel Diagram Abstract: The complexity of software-based systems has increased significantly, especially with regards to capturing requirements along with dependencies among requirements. A conceptual model is a way of thinking about and making sense of the re...	[ 44648 ]	Train
19,616	30	Title: Grammatical gender in Swedish is predictable using recurrent neural networks Abstract: The grammatical gender of Swedish nouns is a mystery. While there are few rules that can indicate the gender with some certainty, it does in general not depend on either meaning or the structure of the word. In this paper we d...	[]	Train
19,617	10	Title: Universal Agent Mixtures and the Geometry of Intelligence Abstract: Inspired by recent progress in multi-agent Reinforcement Learning (RL), in this work we examine the collective intelligent behaviour of theoretical universal agents by introducing a weighted mixture operation. Given a weighted set of agents, the...	[]	Train
19,618	16	Title: RISCLIP: Referring Image Segmentation Framework using CLIP Abstract: Recent advances in computer vision and natural language processing have naturally led to active research in multi-modal tasks, including Referring Image Segmentation (RIS). Recent approaches have advanced the frontier of RIS by impressive margi...	[ 30402, 16103, 23563, 5583, 20435, 13532, 34943 ]	Train
19,619	30	Title: How to Choose How to Choose Your Chatbot: A Massively Multi-System MultiReference Data Set for Dialog Metric Evaluation Abstract: We release MMSMR, a Massively Multi-System MultiReference dataset to enable future work on metrics and evaluation for dialog. Automatic metrics for dialogue evaluation should be robus...	[ 10366 ]	Train
19,620	16	Title: Relightable and Animatable Neural Avatar from Sparse-View Video Abstract: This paper tackles the challenge of creating relightable and animatable neural avatars from sparse-view (or even monocular) videos of dynamic humans under unknown illumination. Compared to studio environments, this setting is more practica...	[ 14792, 29944 ]	Test
19,621	25	Title: ACA-Net: Towards Lightweight Speaker Verification using Asymmetric Cross Attention Abstract: In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetric Cross Attention (ACA) to replace tempo...	[]	Test
19,622	6	Title: Scaling up Action Through Collective Engagement with Environmental Data Abstract: Sustainability has over the past two decades emerged as a key concern in human-computer interaction, with a much critiqued focus on quantification and eco-feedback. This approach fits within a modernist framing of sustainability, t...	[]	Train
19,623	16	Title: C$^3$PS: Context-aware Conditional Cross Pseudo Supervision for Semi-supervised Medical Image Segmentation Abstract: Semi-supervised learning (SSL) methods, which can leverage a large amount of unlabeled data for improved performance, has attracted increasing attention recently. In this paper, we introduce a nov...	[]	Train
19,624	28	Title: Gradient Coding through Iterative Block Leverage Score Sampling Abstract: We generalize the leverage score sampling sketch for $\ell_2$-subspace embeddings, to accommodate sampling subsets of the transformed data, so that the sketching approach is appropriate for distributed settings. This is then used to derive...	[ 36700 ]	Train
19,625	23	Title: Overcoming Challenges in DevOps Education through Teaching Method Abstract: DevOps is a set of practices that deals with coordination between development and operation teams and ensures rapid and reliable new software releases that are essential in industry. DevOps education assumes the vital task of preparing n...	[]	Test
19,626	16	Title: RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-training Abstract: Vision-and-language multi-modal pretraining and fine-tuning have shown great success in visual question answering (VQA). Compared to general domain VQA, the performance of biomedical VQA suffers from limited da...	[ 24053 ]	Validation
19,627	22	Title: Monadic Deep Learning Abstract: The Java and Scala community has built a very successful big data ecosystem. However, most of neural networks running on it are modeled in dynamically typed programming languages. These dynamically typed deep learning frameworks treat neural networks as differentiable expressions ...	[]	Train
19,628	36	Title: Asymptotic Convergence and Performance of Multi-Agent Q-Learning Dynamics Abstract: Achieving convergence of multiple learning agents in general $N$-player games is imperative for the development of safe and reliable machine learning (ML) algorithms and their application to autonomous systems. Yet it is known th...	[ 4355 ]	Train
19,629	34	Title: Budgeted Matroid Maximization: a Parameterized Viewpoint Abstract: We study budgeted variants of well known maximization problems with multiple matroid constraints. Given an $\ell$-matchoid $\cm$ on a ground set $E$, a profit function $p:E \rightarrow \mathbb{R}_{\geq 0}$, a cost function $c:E \rightarrow \mathb...	[ 27755, 3981 ]	Train
19,630	16	Title: OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generation Abstract: Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of large-scale real-scanned 3D databases. To facilitate the development of 3D perception, reconstruction, and...	[ 17700, 25380, 16009, 19532, 20434, 22996 ]	Validation
19,631	24	Title: ExBEHRT: Extended Transformer for Electronic Health Records to Predict Disease Subtypes & Progressions Abstract: nan	[]	Test
19,632	24	Title: Sharp Calibrated Gaussian Processes Abstract: While Gaussian processes are a mainstay for various engineering and scientific applications, the uncertainty estimates don't satisfy frequentist guarantees, and can be miscalibrated in practice. State-of-the-art approaches for designing calibrated models rely on infl...	[]	Validation
19,633	24	Title: Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties Abstract: Development of autonomous cyber system defense strategies and action recommendations in the real-world is challenging, and includes characterizing system state uncertainties and attack-defense dynamics. We prop...	[]	Train
19,634	24	Title: Unexplainable Explanations: Towards Interpreting tSNE and UMAP Embeddings Abstract: It has become standard to explain neural network latent spaces with attraction/repulsion dimensionality reduction (ARDR) methods like tSNE and UMAP. This relies on the premise that structure in the 2D representation is consistent...	[]	Train
19,635	16	Title: A Surface-normal Based Neural Framework for Colonoscopy Reconstruction Abstract: Reconstructing a 3D surface from colonoscopy video is challenging due to illumination and reflectivity variation in the video frame that can cause defective shape predictions. Aiming to overcome this challenge, we utilize the charac...	[]	Validation
19,636	30	Title: Revisit Out-Of-Vocabulary Problem for Slot Filling: A Unified Contrastive Frameword with Multi-level Data Augmentations Abstract: In real dialogue scenarios, the existing slot filling model, which tends to memorize entity patterns, has a significantly reduced generalization facing Out-of-Vocabulary (OOV) problem...	[ 38505, 28892, 4119 ]	Test
19,637	25	Title: DiffV2S: Diffusion-based Video-to-Speech Synthesis with Vision-guided Speaker Embedding Abstract: Recent research has demonstrated impressive results in video-to-speech synthesis which involves reconstructing speech solely from visual input. However, previous works have struggled to accurately synthesize speech ...	[ 28234, 33326 ]	Train
19,638	27	Title: Tracing the Influence of Predecessors on Trajectory Prediction Abstract: In real-world traffic scenarios, agents such as pedestrians and car drivers often observe neighboring agents who exhibit similar behavior as examples and then mimic their actions to some extent in their own behavior. This information can se...	[ 18680, 18283, 41469, 27543 ]	Train
19,639	4	Title: Trustworthy Privacy-Preserving Hierarchical Ensemble and Federated Learning in Healthcare 4.0 With Blockchain Abstract: The advancement of internet and communication technologies has led to the era of Industry 4.0. This shift is followed by healthcare industries creating the term Healthcare 4.0. In Healthcare 4....	[ 16265, 24707 ]	Train
19,640	25	Title: MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training Abstract: Self-supervised learning (SSL) has recently emerged as a promising paradigm for training generalisable models on large-scale data in the fields of vision, text, and speech. Although SSL has been proven effective in speec...	[ 11877, 15880, 21778, 16758, 4759, 4088 ]	Train
19,641	30	Title: Query Structure Modeling for Inductive Logical Reasoning Over Knowledge Graphs Abstract: Logical reasoning over incomplete knowledge graphs to answer complex logical queries is a challenging task. With the emergence of new entities and relations in constantly evolving KGs, inductive logical reasoning over KGs ha...	[]	Test
19,642	24	Title: Machine Learning Model Attribution Challenge Abstract: We present the findings of the Machine Learning Model Attribution Challenge. Fine-tuned machine learning models may derive from other trained models without obvious attribution characteristics. In this challenge, participants identify the publicly-available ...	[ 1917, 38775 ]	Train
19,643	16	Title: SwinLSTM: Improving Spatiotemporal Prediction Accuracy using Swin Transformer and LSTM Abstract: Integrating CNNs and RNNs to capture spatiotemporal dependencies is a prevalent strategy for spatiotemporal prediction tasks. However, the property of CNNs to learn local spatial information decreases their efficienc...	[]	Train
19,644	17	Title: Fast Complementary Dynamics via Skinning Eigenmodes Abstract: We propose a reduced-space elastodynamic solver that is well suited for augmenting rigged character animations with secondary motion. At the core of our method is a novel deformation subspace based on Linear Blend Skinning that overcomes many of the s...	[]	Train
19,645	24	Title: Real-Time Model-Free Deep Reinforcement Learning for Force Control of a Series Elastic Actuator Abstract: Many state-of-the art robotic applications utilize series elastic actuators (SEAs) with closed-loop force control to achieve complex tasks such as walking, lifting, and manipulation. Model-free PID control m...	[]	Train
19,646	23	Title: Interpreting Pretrained Source-code Models using Neuron Redundancy Analyses Abstract: Neural code intelligence models continue to be 'black boxes' to the human programmer. This opacity limits their application towards code intelligence tasks, particularly for applications like vulnerability detection where a mod...	[ 6235, 21759 ]	Train
19,647	16	Title: GET3D-: Learning GET3D from Unconstrained Image Collections Abstract: The demand for efficient 3D model generation techniques has grown exponentially, as manual creation of 3D models is time-consuming and requires specialized expertise. While generative models have shown potential in creating 3D textured shapes ...	[ 34074, 36947 ]	Train
19,648	34	Title: Fast and Efficient Matching Algorithm with Deadline Instances Abstract: Online weighted matching problem is a fundamental problem in machine learning due to its numerous applications. Despite many efforts in this area, existing algorithms are either too slow or don't take $\mathrm{deadline}$ (the longest time a ...	[ 12966, 29867, 13100, 29739, 24299, 39573, 7767 ]	Validation
19,649	24	Title: Learning to Simulate Daily Activities via Modeling Dynamic Human Needs Abstract: Daily activity data that records individuals’ various types of activities in daily life are widely used in many applications such as activity scheduling, activity recommendation, and policymaking. Though with high value, its accessi...	[ 31081 ]	Train
19,650	24	Title: On the Optimality of Misspecified Kernel Ridge Regression Abstract: In the misspecified kernel ridge regression problem, researchers usually assume the underground true function $f_{\rho}^{*} \in [\mathcal{H}]^{s}$, a less-smooth interpolation space of a reproducing kernel Hilbert space (RKHS) $\mathcal{H}$ for ...	[]	Validation
19,651	24	Title: Correcting Model Misspecification via Generative Adversarial Networks Abstract: Machine learning models are often misspecified in the likelihood, which leads to a lack of robustness in the predictions. In this paper, we introduce a framework for correcting likelihood misspecifications in several paradigm agnosti...	[]	Train
19,652	16	Title: Exploring Sparse MoE in GANs for Text-conditioned Image Synthesis Abstract: Due to the difficulty in scaling up, generative adversarial networks (GANs) seem to be falling from grace on the task of text-conditioned image synthesis. Sparsely-activated mixture-of-experts (MoE) has recently been demonstrated as a va...	[ 21152, 30402, 21264, 24624, 20435, 36947, 46197, 28532 ]	Test
19,653	8	Title: Flow Correlator: A Flow Table Cache Management Strategy Abstract: Switching, routing, and security functions are the backbone of packet processing networks. Fast and efficient processing of packets requires maintaining the state of a large number of transient network connections. In particular, modern stateful f...	[]	Train
19,654	6	Title: Generate labeled training data using Prompt Programming and GPT-3. An example of Big Five Personality Classification Abstract: We generated 25000 conversations labeled with Big Five Personality traits using prompt programming at GPT-3. Then we train Big Five classification models with these data and evaluate the...	[]	Train
19,655	24	Title: Causal Information Splitting: Engineering Proxy Features for Robustness to Distribution Shifts Abstract: Statistical prediction models are often trained on data from different probability distributions than their eventual use cases. One approach to proactively prepare for these shifts harnesses the intuition tha...	[]	Test
19,656	24	Title: Can Membership Inferencing be Refuted? Abstract: Membership inference (MI) attack is currently the most popular test for measuring privacy leakage in machine learning models. Given a machine learning model, a data point and some auxiliary information, the goal of an MI attack is to determine whether the data poi...	[]	Test
19,657	24	Title: Scope Loss for Imbalanced Classification and RL Exploration Abstract: We demonstrate equivalence between the reinforcement learning problem and the supervised classification problem. We consequently equate the exploration exploitation trade-off in reinforcement learning to the dataset imbalance problem in superv...	[]	Train
19,658	23	Title: LTM: Scalable and Black-box Similarity-based Test Suite Minimization based on Language Models Abstract: Test suites tend to grow when software evolves, making it often infeasible to execute all test cases with the allocated testing budgets, especially for large software systems. Therefore, test suite minimizatio...	[]	Train
19,659	5	Title: Towards Sybil Resilience in Decentralized Learning Abstract: Federated learning is a privacy-enforcing machine learning technology but suffers from limited scalability. This limitation mostly originates from the internet connection and memory capacity of the central parameter server, and the complexity of the mo...	[ 12050 ]	Train
19,660	34	Title: Weitzman's Rule for Pandora's Box with Correlations Abstract: Pandora’s Box is a central problem in decision making under uncertainty that can model various real life scenarios. In this problem we are given n boxes, each with a ﬁxed opening cost, and an unknown value drawn from a known distribution, only reveale...	[ 40548 ]	Test
19,661	16	Title: Is Generative Modeling-based Stylization Necessary for Domain Adaptation in Regression Tasks? Abstract: Unsupervised domain adaptation (UDA) aims to bridge the gap between source and target domains in the absence of target domain labels using two main techniques: input-level alignment (such as generative modelin...	[]	Validation
19,662	24	Title: Model-based Offline Reinforcement Learning with Local Misspecification Abstract: We present a model-based offline reinforcement learning policy performance lower bound that explicitly captures dynamics model misspecification and distribution mismatch and we propose an empirical algorithm for optimal offline poli...	[ 42858 ]	Train
19,663	24	Title: Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks Abstract: A Markov network characterizes the conditional independence structure, or Markov property, among a set of random variables. Existing work focuses on specific families of distributions (e.g., exponential families) and/...	[]	Train
19,664	24	Title: Catapult Dynamics and Phase Transitions in Quadratic Nets Abstract: Neural networks trained with gradient descent can undergo non-trivial phase transitions as a function of the learning rate. In (Lewkowycz et al., 2020) it was discovered that wide neural nets can exhibit a catapult phase for super-critical learn...	[]	Train
19,665	6	Title: IoT-based Wearables: A comprehensive Survey Abstract: A substantial amount of growth is being achieved by businesses through IoT-based services. The emergent of small electronic devices capable of computing, which are commonly known as wearables in IoT domain has proven to have huge impact in people's life. Thes...	[]	Train
19,666	26	Title: A study on information disorders on social networks during the Chilean social outbreak and COVID-19 pandemic Abstract: Information disorders on social media can have a significant impact on citizens’ participation in democratic processes. To better understand the spread of false and inaccurate information online...	[ 39680 ]	Train
19,667	6	Title: The GENEA Challenge 2023: A large scale evaluation of gesture generation models in monadic and dyadic settings Abstract: This paper reports on the GENEA Challenge 2023, in which participating teams built speech-driven gesture-generation systems using the same speech and motion dataset, followed by a joint evalua...	[ 41699, 33512, 36214, 17241, 27642 ]	Train
19,668	26	Title: Efficient Centrality Maximization with Rademacher Averages Abstract: The identification of the set of k most central nodes of a graph, or centrality maximization, is a key task in network analysis, with various applications ranging from finding communities in social and biological networks to understanding which...	[]	Validation
19,669	16	Title: Vista-Morph: Unsupervised Image Registration of Visible-Thermal Facial Pairs Abstract: For a variety of biometric cross-spectral tasks, Visible-Thermal (VT) facial pairs are used. However, due to a lack of calibration in the lab, photographic capture between two different sensors leads to severely misaligned pai...	[ 6731, 36941 ]	Train
19,670	30	Title: System-Initiated Transitions from Chit-Chat to Task-Oriented Dialogues with Transition Info Extractor and Transition Sentence Generator Abstract: In this work, we study dialogue scenarios that start from chit-chat but eventually switch to task-related services, and investigate how a unified dialogue model, which...	[ 22198 ]	Train
19,671	30	Title: Large Language Models are not Fair Evaluators Abstract: In this paper, we uncover a systematic bias in the evaluation paradigm of adopting large language models~(LLMs), e.g., GPT-4, as a referee to score and compare the quality of responses generated by candidate models. We find that the quality ranking of candi...	[ 5891, 17417, 6797, 14609, 13844, 25751, 32796, 8608, 13345, 31012, 12709, 7339, 7982, 7344, 41010, 21300, 9014, 13495, 6328, 29753, 12602, 9403, 20794, 34103, 2622, 32184, 6977, 36545, 33220, 41029, 21190, 40440, 38857, 12628, 24440, 38102, 136...	Test
19,672	16	Title: A Critical Look at the Current Usage of Foundation Model for Dense Recognition Task Abstract: In recent years large model trained on huge amount of cross-modality data, which is usually be termed as foundation model, achieves conspicuous accomplishment in many fields, such as image recognition and generation. Th...	[ 37254, 3015, 36168, 8234, 5583, 23545, 34074, 4220, 46047 ]	Train
19,673	13	Title: Implementing Immune Repertoire Models Using Weighted Finite State Machines Abstract: The adaptive immune system's T and B cells can be viewed as large populations of simple, diverse classifiers. Artificial immune systems (AIS) $\unicode{x2013}$ algorithmic models of T or B cell repertoires $\unicode{x2013}$ are ...	[]	Validation
19,674	16	Title: Towards Globally Consistent Stochastic Human Motion Prediction via Motion Diffusion Abstract: Stochastic human motion prediction aims to predict multiple possible upcoming pose sequences based on past human motion trajectories. Prior works focused heavily on generating diverse motion samples, leading to inconsis...	[ 3440, 38181 ]	Train
19,675	16	Title: Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation Abstract: Object detection and multiple object tracking (MOT) are essential components of self-driving systems. Accurate detection and uncertainty quantification are both critical for onboard modules, such as perception, prediction, and p...	[ 1155, 740, 44574 ]	Train
19,676	1	Title: UMMAFormer: A Universal Multimodal-adaptive Transformer Framework for Temporal Forgery Localization Abstract: The emergence of artificial intelligence-generated content (AIGC) has raised concerns about the authenticity of multimedia content in various fields. However, existing research for forgery content detect...	[]	Train
19,677	16	Title: Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes Abstract: 3D scene understanding has gained significant attention due to its wide range of applications. However, existing methods for 3D scene understanding are limited to specific downstream tasks, which hinders their pra...	[ 10624, 14656, 31776, 37987, 13700, 37765, 37799, 24715, 41104, 30745, 18267 ]	Test

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.