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AVEX: What Matters for Animal Vocalization Encoding

arXiv:2508.11845v3 Announce Type: replace-cross Abstract: Bioacoustics, the study of sounds produced by living organisms, plays a vital role in conservation, biodiversity monitoring, and behavioral st

Bad Seeing or Bad Thinking? Rewarding Perception for Vision-Language Reasoning

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DGX agent

arXiv:2605.14054v1 Announce Type: new Abstract: Achieving robust perception-reasoning synergy is a central goal for advanced Vision-Language Models (VLMs). Recent advancements have pursued this goal v

agentsarxiv-cs-ai

15 May 2026

BCI-Based Assessment of Ocular Response Time Using Dynamic Time Warping Leveraging an RDWT-Driven Deep Neural Framework

arXiv:2605.14883v1 Announce Type: cross Abstract: Mild traumatic brain injury (mTBI) is a prevalent condition that remains difficult to diagnose in its early stages. Oculomotor dysfunction is a well-e

researcharxiv-cs-lg

Tutorials

bde: A Python Package for Bayesian Deep Ensembles via MILE

arXiv:2605.14146v1 Announce Type: new Abstract: bde is a user-friendly Python package for Bayesian Deep Ensembles with a particular focus on tabular data. Built on an efficient JAX implementation of t

tutorialsarxiv-cs-lg

Hardware

BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE

arXiv:2605.14438v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures enhance the efficiency of large language models by activating only a subset of experts per token. However, standa

hardwarearxiv-cs-ai

Before the Body Moves: Learning Anticipatory Joint Intent for Language-Conditioned Humanoid Control

arXiv:2605.14417v1 Announce Type: cross Abstract: Natural language is an intuitive interface for humanoid robots, yet streaming whole-body control requires control representations that are executable

safetyarxiv-cs-cv

Behavior Cloning for Active Perception with Low-Resolution Egocentric Vision

arXiv:2605.14106v1 Announce Type: new Abstract: We investigate whether behavior cloning is sufficient to produce active perception in a structured object-finding task. A low-cost robot arm equipped wi

researcharxiv-cs-ro

Behavioral Data-Driven Optimal Trajectory Generation for Rotary Cranes

arXiv:2605.14944v1 Announce Type: new Abstract: With the growth of the construction industry and the global shortage of skilled labor, the automation of crane control has become increasingly important

safetyarxiv-cs-ro

Bellman Value Decomposition for Task Logic in Safe Optimal Control

arXiv:2602.19532v2 Announce Type: replace Abstract: Real-world tasks involve nuanced combinations of goal and safety specifications. In high dimensions, the challenge is exacerbated: formal automata b

safetyarxiv-cs-ro

Beyond AI as Assistants: Toward Autonomous Discovery in Cosmology

arXiv:2605.14791v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) agents are pushing AI beyond tools toward autonomous scientific discovery. We discuss two complementar

Beyond Binary: Reframing GUI Critique as Continuous Semantic Alignment

arXiv:2605.14311v1 Announce Type: cross Abstract: Test-Time Scaling (TTS), which samples multiple candidate actions and ranks them via a Critic Model, has emerged as a promising paradigm for generalis

Beyond Cosine Similarity: Zero-Initialized Residual Complex Projection for Aspect-Based Sentiment Analysis

arXiv:2603.28205v2 Announce Type: replace Abstract: Aspect-Based Sentiment Analysis (ABSA) faces critical challenges due to representation entanglement and false-negative collisions in real-valued emb

researcharxiv-cs-cl

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems

arXiv:2605.14892v1 Announce Type: new Abstract: LLM-based autonomous agents have demonstrated strong capabilities in reasoning, planning, and tool use, yet remain limited when tasks require sustained

agentsarxiv-cs-ai

Beyond Instance-Level Self-Supervision in 3D Multi-Modal Medical Imaging

arXiv:2605.14654v1 Announce Type: new Abstract: Self-supervised pre-training methods in medical imaging typically treat each individual as an isolated instance, learning representations through augmen

safetyarxiv-cs-cv

Beyond Mode-Seeking RL: Trajectory-Balance Post-Training for Diffusion Language Models

model-releasesarxiv-cs-cl

arXiv:2605.13935v1 Announce Type: cross Abstract: Diffusion language models are a promising alternative to autoregressive models, yet post-training methods for them largely adapt reward-maximizing obj

Beyond the Final Answer: Evaluating the Reasoning Trajectories of Tool-Augmented Agents

arXiv:2510.02837v2 Announce Type: replace Abstract: Although recent tool-augmented benchmarks involve complex requests, evaluation remains limited to answer matching, neglecting critical trajectory as

agentsarxiv-cs-ai

Beyond What to Select: A Plug-and-play Oscillatory Data-Volume Scheduling for Efficient Model Training

arXiv:2605.14773v1 Announce Type: cross Abstract: Data selection accelerates training by identifying representative training data while preserving model performance. However, existing methods mainly f

BiFedKD: Bidirectional Federated Knowledge Distillation Framework for Non-IID and Long-Tailed ECG Monitoring

arXiv:2605.14886v1 Announce Type: new Abstract: Electrocardiogram (ECG) monitoring in Internet of Medical Things (IoMT) networks is constrained by strict data-sharing regulations and privacy concerns.

BioHuman: Learning Biomechanical Human Representations from Video

model-releasesarxiv-cs-cv

arXiv:2605.14772v1 Announce Type: new Abstract: Understanding human motion beyond surface kinematics is crucial for motion analysis, rehabilitation, and injury risk assessment. However, progress in th

BiSpikCLM: A Spiking Language Model integrating Softmax-Free Spiking Attention and Spike-Aware Alignment Distillation

arXiv:2605.13859v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) offer promising energy-efficient alternatives to large language models (LLMs) due to their event-driven nature and ultr

safetyarxiv-cs-ai

BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2506.05762v5 Announce Type: replace Abstract: Recent advances in offline Reinforcement Learning (RL) have proven that effective policy learning can benefit from imposing conservative constraints

BOOKMARKS: Efficient Active Storyline Memory for Role-playing

arXiv:2605.14169v1 Announce Type: new Abstract: Memory systems are critical for role-playing agents (RPAs) to maintain long-horizon consistency. However, existing RPA memory methods (e.g., profiling)

researcharxiv-cs-cl

BOOST: A Data-Driven Framework for the Automated Joint Selection of Kernel and Acquisition Functions in Bayesian Optimization

arXiv:2508.02332v3 Announce Type: replace Abstract: The performance of Bayesian optimization (BO), a highly sample-efficient method for expensive black-box problems, is critically governed by the sele

agentsarxiv-cs-lg

Boosting LLM Reasoning via Human-Inspired Reward Shaping

arXiv:2602.04265v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for enhancing reasoning in Large Language Models (LL

Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance

arXiv:2605.15012v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has achieved great success in developing Large Language Models (LLMs) with chain-of-thought roll

safetyarxiv-cs-ai

Break-the-Beat! Controllable MIDI-to-Drum Audio Synthesis

arXiv:2605.14555v1 Announce Type: cross Abstract: Current methods for creating drum loop audio in digital music production, such as using one-shot samples or resampling, often demand non-trivial effor

safetyarxiv-cs-ai

Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners

model-releasesarxiv-cs-cv

arXiv:2605.14709v1 Announce Type: new Abstract: Recent unified models integrate multimodal understanding and generation within a single framework. However, an 'understanding-generation gap' persists,

Breaking Global Self-Attention Bottlenecks in Transformer-based Spiking Neural Networks with Local Structure-Aware Self-Attention

arXiv:2605.13887v1 Announce Type: cross Abstract: Transformer-based Spiking Neural Networks (SNNs) integrate SNNs with global self-attention and have demonstrated impressive performance. However, exis

Local Ai

Breaking the Reasoning Horizon in Entity Alignment Foundation Models

arXiv:2601.21174v2 Announce Type: replace Abstract: Entity alignment (EA) is critical for knowledge graph (KG) fusion. Existing EA models lack transferability and are incapable of aligning unseen KGs

local-aiarxiv-cs-lg

Bridging Brain and Semantics: A Hierarchical Framework for Semantically Enhanced fMRI-to-Video Reconstruction

arXiv:2605.14569v1 Announce Type: new Abstract: Reconstructing dynamic visual experiences as videos from functional magnetic resonance imaging (fMRI) is pivotal for advancing the understanding of neur

researcharxiv-cs-cv

Applications

Bridging Legal Interpretation and Formal Logic: Faithfulness, Assumption, and the Future of AI Legal Reasoning

arXiv:2605.14049v1 Announce Type: new Abstract: The growing adoption of large language models in legal practice brings both significant promise and serious risk. Legal professionals stand to benefit f

applicationsarxiv-cs-ai

Local Ai

Bridging the Rural Healthcare Gap: A Cascaded Edge-Cloud Architecture for Automated Retinal Screening

arXiv:2605.14108v1 Announce Type: cross Abstract: Diabetic Retinopathy (DR) is one of the leading causes of preventable blindness, yet rural regions often lack the specialists and infrastructure neede

local-aiarxiv-cs-ai

CA2: Code-Aware Agent for Automated Game Testing

arXiv:2605.13918v1 Announce Type: cross Abstract: Automated game testing is important for verifying game functionality, but it remains a costly and time-consuming process. Manual testing often misses

agentsarxiv-cs-lg

Applications

CAKE: Confidence in Assignments via K-partition Ensembles

arXiv:2602.18435v2 Announce Type: replace Abstract: Clustering is widely used for unsupervised structure discovery, yet it offers limited insight into how reliable each individual assignment is. Diagn

applicationsarxiv-cs-lg

Applications

CalibAnyView: Beyond Single-View Camera Calibration in the Wild

arXiv:2605.14615v1 Announce Type: new Abstract: Camera calibration is a fundamental prerequisite for reliable geometric perception, yet classical approaches rely on controlled acquisition setups that

applicationsarxiv-cs-cv

CaMeRL: Collision-Aware and Memory-Enhanced Reinforcement Learning for UAV Navigation in Multi-Scale Obstacle Environments

arXiv:2605.14810v1 Announce Type: new Abstract: In obstacle avoidance navigation of unmanned aerial vehicles (UAVs), variations in obstacle scale have received strangely less attention than obstacle n

researcharxiv-cs-ro

Tutorials

Can Stationary Distributions of Scale-Invariant Neural Networks Be Described by the Thermodynamics of an Ideal Gas?

arXiv:2511.07308v2 Announce Type: replace Abstract: Understanding the training dynamics of deep neural networks remains a major open problem, with physics-inspired approaches offering promising insigh

tutorialsarxiv-cs-lg

Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation

model-releasesarxiv-cs-cv

arXiv:2605.14799v1 Announce Type: new Abstract: In recent years, computer vision has witnessed remarkable progress, fueled by the development of innovative architectures such as Convolutional Neural N

Capacitive Touchscreens at Risk: Recovering Handwritten Trajectory on Smartphone via Electromagnetic Emanations

arXiv:2512.11484v1 Announce Type: cross Abstract: This paper reveals and exploits a critical security vulnerability: the electromagnetic (EM) side channel of capacitive touchscreens leaks sufficient i

Case-Based Calibration of Adaptive Reasoning and Execution for LLM Tool Use

arXiv:2605.15041v1 Announce Type: new Abstract: Tool use extends large language models beyond parametric knowledge, but reliable execution requires balancing appropriate reasoning depth with strict st

agentsarxiv-cs-ai

Cattle Trade: A Multi-Agent Benchmark for LLM Bluffing, Bidding, and Bargaining

arXiv:2605.14537v1 Announce Type: new Abstract: We introduce extsc{Cattle Trade, a multi-agent benchmark for evaluating large language models (LLMs) as agents in strategic reasoning under imperfect in

Causal Forcing++: Scalable Few-Step Autoregressive Diffusion Distillation for Real-Time Interactive Video Generation

arXiv:2605.15141v1 Announce Type: new Abstract: Real-time interactive video generation requires low-latency, streaming, and controllable rollout. Existing autoregressive (AR) diffusion distillation me

researcharxiv-cs-cv

Causal Foundation Models with Continuous Treatments

arXiv:2605.15133v1 Announce Type: new Abstract: Causal inference, estimating causal effects from observational data, is a fundamental tool in many disciplines. Of particular importance across a variet

researcharxiv-cs-lg

Causal Multi-Task Demand Learning

arXiv:2602.09969v2 Announce Type: replace Abstract: We study a canonical multi-task demand-learning problem motivated by retail pricing, where a firm seeks to estimate heterogeneous linear price-respo

researcharxiv-cs-lg

Tutorials

Causal Time Series Generation via Diffusion Models

arXiv:2509.20846v3 Announce Type: replace Abstract: Time series generation (TSG) synthesizes realistic sequences and has achieved remarkable success. Among TSG, conditional models generate sequences g

tutorialsarxiv-cs-lg

CausalReasoningBenchmark: A Real-World Benchmark for Disentangled Evaluation of Causal Identification and Estimation

arXiv:2602.20571v2 Announce Type: replace Abstract: Many benchmarks for automated causal inference evaluate a system's performance based on a single numerical output, such as an Average Treatment Effe

CC-Pan: Channel-wise Compression based Diffusion for Efficient Pan-Sharpening

arXiv:2602.04473v2 Announce Type: replace Abstract: Recently, diffusion models have brought novel insights to pan-sharpening and notably boosted fusion precision. However, most existing models perform

researcharxiv-cs-cv

Chain-of-Procedure: Hierarchical Visual-Language Reasoning for Procedural QA

model-releasesarxiv-cs-cl

arXiv:2605.14928v1 Announce Type: new Abstract: Recent advances in vision-language models (VLMs) have achieved impressive results on standard image-text tasks, yet their potential for visual procedure