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VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents

model-releasesarxiv-cs-cl

arXiv:2605.30256v1 Announce Type: cross Abstract: Natural human conversation is full-duplex and audio-visual: people simultaneously speak and listen while continuously interpreting and producing nonve

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Hardware

VideoMLA: Low-Rank Latent KV Cache for Minute-Scale Autoregressive Video Diffusion

DGX agent

arXiv:2605.30351v1 Announce Type: cross Abstract: Long-rollout causal video diffusion has converged on a fixed-size sliding-window KV cache, with recent progress innovating within this layout by chang

hardwarearxiv-cs-ai

29 May 2026

Agents

VikingMem: A Memory Base Management System for Stateful LLM-based Applications

arXiv:2605.29640v1 Announce Type: new Abstract: Large Language Models have revolutionized interactive applications; however, their finite context windows pose a critical data management challenge for

agentsarxiv-cs-ai

Visual Spatial Learning: Single-Field Spatial Interpolation Using Convolutional Neural Networks

arXiv:2605.30167v1 Announce Type: cross Abstract: Predicting a complete spatially correlated field from sparse observations is a fundamental challenge in spatial statistics and environmental modelling

researcharxiv-cs-cv

Agents

VisualThink-VLA: Visual Intermediate Reasoning for Effective and Low-Latency Vision-Language-Action Policies

arXiv:2605.30011v1 Announce Type: cross Abstract: Recent work has begun to equip vision-language-action (VLA) policies with explicit intermediate reasoning. In embodied control, however, textual chain

agentsarxiv-cs-ai

VitalAgent: A Tool-Augmented Agent for Reactive and Proactive Physiological Monitoring over Wearable Health Data

arXiv:2605.29483v1 Announce Type: new Abstract: Wearable devices enable continuous monitoring of physiological signals such as ECG and PPG, but existing mHealth systems are largely limited to task-spe

Applications

VLA-Pro: Cross-Task Procedural Memory Transfer for Vision-Language-Action Models

arXiv:2605.29562v1 Announce Type: cross Abstract: Vision-Language-Action~(VLA) models have shown strong potential for general-purpose robotic manipulation, yet they still struggle to generalize to uns

applicationsarxiv-cs-ai

VLA-Trace: Diagnosing Vision-Language-Action Models through Representation and Behavior Tracing

arXiv:2605.30117v1 Announce Type: new Abstract: Understanding how Vision-Language-Action (VLA) models transform multimodal knowledge into embodied control remains an open challenge. We present VLA-Tra

VLAConf: Calibrated Task-Success Confidence for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2605.29605v1 Announce Type: new Abstract: Confidence estimation for Vision-Language-Action (VLA) models is essential for robots to perform manipulation tasks in the open world, providing crucial

VPG: Visual Prefix Guidance for Autoregressive Image and Video Generation

model-releasesarxiv-cs-cv

arXiv:2605.30317v1 Announce Type: new Abstract: Autoregressive image and video generators are trained with teacher-forced histories but must sample from their own generated prefixes at inference time,

Wait! There's a Way Out: A Decision Mechanism for Forecasting Conversational Derailment

arXiv:2605.29243v1 Announce Type: cross Abstract: Forecasting conversational derailment is the task of predicting, as the conversation unfolds, whether it will eventually derail into personal attacks.

WASHH: An Anchor-Aware Whale-Guided Selection Hyper-Heuristic for Continuous Optimization and SVC Configuration

arXiv:2605.28844v1 Announce Type: cross Abstract: Learning-assisted algorithm design often has to make reliable search decisions under small evaluation budgets, where committing to a single metaheuris

Wasserstein Contraction of Coordinate Ascent Variational Inference

arXiv:2605.30253v1 Announce Type: cross Abstract: We study the contraction in Wasserstein distance of the coordinate ascent variational inference algorithm. This is shown to hold under a transport-inf

researcharxiv-cs-lg

WaterSearch: A Quality-Aware Search-based Watermarking Framework for Large Language Models

arXiv:2512.00837v2 Announce Type: replace Abstract: Watermarking acts as a critical safeguard in text generated by Large Language Models (LLMs). By embedding identifiable signals into model outputs, w

Weakly Supervised Detection and Temporal Localization of Whale Calls in Long-Duration Bioacoustic Data

arXiv:2502.20838v3 Announce Type: replace-cross Abstract: Passive acoustic monitoring (PAM) systems generate continuous recordings spanning months, yet automated bioacoustic analysis of whale calls re

What are They Thinking? Delineation, Probing and Tracking of Concepts in LLMs

arXiv:2605.28823v1 Announce Type: new Abstract: As the influence of LLMs expands, it is imperative to gain insight into their decisions. One way to do that is to develop probes that detect the presenc

What drives performance in molecular MPNNs? An operator-level factorial benchmark

arXiv:2605.30195v1 Announce Type: cross Abstract: Message-passing neural networks (MPNNs) are widely used for molecular property prediction, but their deployment as monolithic architectures makes it d

What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies

arXiv:2603.02082v2 Announce Type: replace Abstract: Children's acquisition of filler-gap dependencies has been argued by some to depend on innate grammatical knowledge, while others suggest that the d

tutorialsarxiv-cs-cl

When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop

arXiv:2605.29267v1 Announce Type: new Abstract: Foundation models are increasingly trained on synthetic data generated by prior model iterations rather than exclusively on real data. This self-consumi

When and How Long? The Readout-Mediator Angle in Temporal Reasoning

arXiv:2605.29126v1 Announce Type: cross Abstract: A linear probe can decode a representation almost perfectly and yet be completely irrelevant to how the model uses it. On calendar-date duration reaso

Local Ai

When Cloud Agents Meet Device Agents: Lessons from Hybrid Multi-Agent Systems

arXiv:2605.30102v1 Announce Type: cross Abstract: The design space of agentic AI inference spans two extremes: frontier large language models (LLMs), typically hosted in the cloud and offering strong

local-aiarxiv-cs-ai

When Do Graph Foundation Models Transfer? A Data-Centric Theory

arXiv:2605.29828v1 Announce Type: new Abstract: Graph foundation models (GFMs) aim to reuse a single backbone across diverse graph domains, yet their transfer is often uneven and can exhibit negative

researcharxiv-cs-lg

Applications

When Does Persona Prompting Actually Help? A Retrieval and Metric Analysis of Expert Role Injection in LLMs

arXiv:2605.29420v1 Announce Type: new Abstract: Persona prompting is widely used to steer large language models, yet its practical value remains unclear. Prior work often evaluates persona prompting u

applicationsarxiv-cs-ai

When LLM Reward Design Fails: Diagnostic-Driven Refinement for Sparse Structured RL

arXiv:2605.28918v1 Announce Type: new Abstract: For sparse, structured reinforcement-learning tasks with semantic reward-function interfaces, LLM-generated reward shaping is better framed as debugging

When Models Disagree: Rethinking LLM Evaluation for Public Comment Analysis

arXiv:2605.29025v1 Announce Type: new Abstract: Federal agencies are deploying large language models (LLMs) to categorize public comment corpora, where the model's organization of the record shapes wh

When Models Learn to Ask Why: Adaptive Causal Reasoning for Trustworthy Medical Vision-Language Models

arXiv:2603.23085v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) have enabled interpretable medical diagnosis by integrating visual perception with linguistic reasoning. Yet, existing

tutorialsarxiv-cs-ai

When RL Suppresses Its Own Vocabulary: Recovering Reasoning Diversity in Puzzle-to-Math Transfer

arXiv:2605.29190v1 Announce Type: cross Abstract: Reinforcement learning using verifiable rewards (RLVR) improves LLM reasoning, but the conditions under which it transfers across domains -- and why i

When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Robotic Decision-Making

arXiv:2603.16673v4 Announce Type: replace-cross Abstract: Embodied robotic systems increasingly rely on large language model (LLM)-based agents to support high-level reasoning, planning, and decision-

When Should Models Change Their Minds? Contextual Belief Management in Large Language Models

arXiv:2605.30219v1 Announce Type: new Abstract: Long-horizon interactions require language models to manage accumulating information: when to update their state, when to preserve their state, and what

When the Same Coefficients Reach Different Places: Asymmetric Realizability in Transplanting Tokenizers across Large Language Models

model-releasesarxiv-cs-cl

arXiv:2601.00065v3 Announce Type: replace-cross Abstract: Tokenizer transplant in cross-vocabulary model composition reconstructs donor-only embedding rows as weighted combinations over shared lexical

When, why, and how do diffusion posterior samplers fail? A finite-sample lens

arXiv:2605.30330v1 Announce Type: new Abstract: Diffusion models have excellent capacity to model complex distributions of natural data, which has made them a popular and effective choice for posterio

researcharxiv-cs-lg

Applications

Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues

arXiv:2605.30051v1 Announce Type: new Abstract: A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students,

applicationsarxiv-cs-cl

Who can we trust? LLM-as-a-jury for Comparative Assessment

arXiv:2602.16610v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly applied as automatic evaluators for natural language generation assessment often using pairwise

Why Far Looks Up: Probing Spatial Representation in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.30161v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong performance on spatial reasoning benchmarks, yet it remains unclear whether this reflects structured 3D und

Why Larger Models Learn More: Effects of Capacity, Interference, and Rare-Task Retention

arXiv:2605.29548v1 Announce Type: new Abstract: Larger models learn tasks smaller models do not. What drives this phenomenon? We develop a simple phenomenological argument that power-law scaling alrea

tutorialsarxiv-cs-lg

Why Specialist Models Still Matter: A Heterogeneous Multi-Agent Paradigm for Medical Artificial Intelligence

arXiv:2605.29744v1 Announce Type: new Abstract: The impressive performance of generalist large language models (LLMs) such as GPT and Claude in healthcare raises a critical question: will domain-speci

World Models in Words: Auditing Physical State-Transition Commitments in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2605.29585v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used to answer questions about physical scenes, yet most evaluations reduce performance to a final answer

Agents

WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction

arXiv:2605.29341v1 Announce Type: cross Abstract: Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving wo

agentsarxiv-cs-cl

X-GS: An Extensible Framework for Perceiving and Thinking via 3D Gaussian Splatting

arXiv:2603.09632v3 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, subsequently extending into numerous spatial AI app

Xetrieval: Mechanistically Explaining Dense Retrieval

arXiv:2605.29507v1 Announce Type: new Abstract: Explaining why dense retrievers assign high relevance scores remains challenging because retrieval decisions are made through opaque high-dimensional em

xModel-KD: Cross-modal Knowledge Distillation for 3D Scene Perception using LiDAR

arXiv:2605.30111v1 Announce Type: cross Abstract: Point cloud segmentation is a fundamental task in 3D scene understanding. Its progress is constrained by the high cost and time required for dense 3D

YoCausal: How Far is Video Generation from World Model? A Causality Perspective

model-releasesarxiv-cs-cv

arXiv:2605.30346v1 Announce Type: new Abstract: As video diffusion models (VDMs) advance toward world models, a key question arises: do they truly understand causality, or merely overfit to statistica

Zero-shot CT Super-Resolution using Diffusion-based 2D Projection Priors and Signed 3D Gaussians

arXiv:2508.15151v3 Announce Type: replace-cross Abstract: Computed tomography (CT) is important in clinical diagnosis, but acquiring high-resolution (HR) CT is constrained by radiation exposure risks.

tutorialsarxiv-cs-cv

A Bayesian Nonparametric Perspective on Mahalanobis Distance for Out of Distribution Detection

arXiv:2502.08695v2 Announce Type: replace-cross Abstract: Bayesian nonparametric methods are naturally suited to the problem of out-of-distribution (OOD) detection. However, these techniques have larg

A Broader View of Thompson Sampling

arXiv:2510.07208v2 Announce Type: replace Abstract: Thompson Sampling is one of the most widely used and studied bandit algorithms, known for its simple structure, low regret performance, and solid th

A Comparative Study of Rule-Based and Data-Driven Approaches in Industrial Monitoring

arXiv:2509.15848v2 Announce Type: replace Abstract: Industrial monitoring systems, especially when deployed in Industry 4.0 environments, are experiencing a shift in paradigm from traditional rule-bas

A Conflict-Aware Penalty and Statistical Loss Framework for Balancing Modalities and Enhancing Stability in Multimodal Sentiment Analysis

arXiv:2605.28575v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) fuses text, acoustic, and visual streams to infer sentiment. Because pre-trained text encoders are far more expressi

A Digital Twin Framework for Virtual Visuo-Haptic Teleoperation of Complex-Shaped Optical Microrobots

arXiv:2605.28448v1 Announce Type: new Abstract: Optical tweezers (OT) provide piconewton-scale manipulation for delicate biomedical tasks, where visuo-haptic feedback can improve operator awareness by

researcharxiv-cs-ro