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Do not be greedy, Think Twice: Sampling and Selection for Document-level Information Extraction

arXiv:2601.18395v2 Announce Type: replace Abstract: Document-level Information Extraction (DocIE) aims to produce an output template with the entities, relations, and events of interest occurring in t

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Model Releases

Do Physics Foundation Models Learn Generalizable Physics? A Bias-Aware Benchmark Across Physical Regimes and Distribution Shifts

DGX agent

arXiv:2605.29283v1 Announce Type: cross Abstract: Recent physics foundation models claim general spatiotemporal forecasting ability, yet their evaluations often collapse performance into a single aver

model-releasesarxiv-cs-ai

29 May 2026

Local Ai

Do Proactive Agents Really Need an LLM to Decide When to Wake and What to Anchor?

arXiv:2605.30152v1 Announce Type: cross Abstract: Proactive agents read user activity as text and call an LLM on every event to decide whether to act. But user activity is not natively text: it is a s

local-aiarxiv-cs-ai

DocRetriever: A Plug-and-Play Framework for Multimodal Document Retrieval with Comprehensive Benchmark

model-releasesarxiv-cs-cv

arXiv:2605.30027v1 Announce Type: new Abstract: Multimodal documents contain diverse elements, such as tables, figures, and layouts, which can complicate retrieval tasks. While current approaches typi

Does Distributed Training Undermine Compute Governance?

arXiv:2605.29359v1 Announce Type: cross Abstract: Compute governance proposals often rely on the assumption that frontier AI training requires large, detectable computing clusters. However, recent adv

researcharxiv-cs-ai

Does The Way You Plan Matter? An Empirical Study of Planning Representations for LLM Web Agents

arXiv:2605.29927v1 Announce Type: cross Abstract: Despite recent advances, LLM-based web agents still struggle with limited exploration, omission of critical steps, and sensitivity to task constraints

agentsarxiv-cs-ai

Domain-Agnostic Feature Modulation for Semi-Supervised Domain Generalization

arXiv:2503.20897v2 Announce Type: replace Abstract: Semi-supervised domain generalization (SSDG) leverages a small fraction of labeled data alongside unlabeled data to enhance model generalization. Mo

researcharxiv-cs-cv

Domain-Informed Representation for Evolutionary Sieving in Integral and Module Lattices

arXiv:2605.29169v1 Announce Type: cross Abstract: Traditional cryptography, rooted in problems, e.g., integer factorisation or discrete log, is inevitably vulnerable to a fully operational quantum com

researcharxiv-cs-ai

Tutorials

Domain-Specific Data Synthesis for LLMs via Minimal Sufficient Representation Learning

arXiv:2605.30039v1 Announce Type: new Abstract: Large Language Models have demonstrated remarkable progress in general-purpose capabilities and can achieve strong performance in specific domains throu

tutorialsarxiv-cs-ai

Domino: Decoupling Causal Modeling from Autoregressive Drafting in Speculative Decoding

arXiv:2605.29707v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting multiple tokens and verifying them in parallel with the target model. However, its practical

Double-Edged Sword or Sharp Tool? Designing and Evaluating Triadic LLM-Teacher Collaboration for K-12 Writing at Scale

arXiv:2605.30200v1 Announce Type: new Abstract: The double-edged sword of integrating Large Language Models (LLMs) requires an effective triadic collaboration mechanism among LLMs, teachers and studen

applicationsarxiv-cs-ai

Draft-OPD: On-Policy Distillation for Speculative Draft Models

arXiv:2605.29343v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference by pairing a target model with a lightweight draft model whose proposed tokens are verif

safetyarxiv-cs-cl

Dual Quaternion SE(3) Synchronization with Recovery Guarantees

arXiv:2602.00324v2 Announce Type: replace-cross Abstract: Synchronization over the special Euclidean group SE(3) aims to recover absolute poses from noisy pairwise relative transformations and is a co

applicationsarxiv-cs-cv

Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model

arXiv:2510.27607v3 Announce Type: replace Abstract: Augmenting vision-language-action models (VLAs) with world models is promising for robotic policy learning but faces challenges in jointly predictin

safetyarxiv-cs-cv

DVSM: Decoder-only View Synthesis Model Done Right

arXiv:2605.29891v1 Announce Type: new Abstract: Recent Large View Synthesis Models (LVSMs) advocate an encoder-decoder architecture that separates reconstruction and rendering into distinct networks.

researcharxiv-cs-cv

DynaFLIP: Rethinking Robotics Perception via Tri-Modal-Dynamics Guided Representation

arXiv:2605.30350v1 Announce Type: cross Abstract: Robot manipulation critically depends on perception that preserves the action-relevant aspects of a scene. Yet most robot learning pipelines are built

safetyarxiv-cs-lg

Local Ai

DynaGraph: Lightweight Multi-Model Interaction Framework via Dynamic Topological Reconfiguration

arXiv:2605.29511v1 Announce Type: cross Abstract: Tackling complex reasoning tasks typically relies on massive monolithic LLMs, which suffer from severe computational redundancy. While task decomposit

local-aiarxiv-cs-cl

Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning

model-releasesarxiv-cs-lg

arXiv:2506.05985v3 Announce Type: replace Abstract: A generalist agent must continuously learn and adapt throughout its lifetime, achieving efficient forward transfer while minimizing catastrophic for

Dynamics of Stochastic Momentum with Sparse Updates in High Dimensions

model-releasesarxiv-cs-lg

arXiv:2605.28961v1 Announce Type: cross Abstract: Existing theory of momentum assumes that gradients arrive at every parameter at a roughly constant rate, an assumption violated in practice by heavy-t

Dynamics Within Latent Chain-of-Thought: An Empirical Study of Causal Structure

arXiv:2602.08783v3 Announce Type: replace Abstract: Latent or continuous chain-of-thought methods replace explicit textual rationales with a number of internal latent steps, but these intermediate com

DynSess: Dynamic Session-Level Evaluation and Optimization Framework for Role-Playing Agents

model-releasesarxiv-cs-ai

arXiv:2605.29256v1 Announce Type: cross Abstract: Role-playing with large language models is fundamentally a session-level task, requiring agents to sustain character identity and interaction quality

DySem: Uncovering Dynamic Semantic Components via Multilingual Consensus for Calculating Semantic Textual Similarity

model-releasesarxiv-cs-cl

arXiv:2605.29751v1 Announce Type: new Abstract: Calculating semantic textual similarity is a foundational task in natural language processing. Current large language models (LLMs) based methods typica

E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing

arXiv:2512.03109v2 Announce Type: replace-cross Abstract: Agentic AI systems execute a sequence of actions, such as reasoning steps or tool calls, in response to a user prompt. To evaluate the success

agentsarxiv-cs-ai

EAPO: Enhancing Policy Optimization with On-Demand Expert Assistance

arXiv:2509.23730v2 Announce Type: replace Abstract: Large language models (LLMs) have recently advanced in reasoning when optimized with reinforcement learning (RL) under verifiable rewards. Existing

Tutorials

Early Detection of Misinformation for Infodemic Management: A Domain Adaptation Approach

arXiv:2406.10238v2 Announce Type: replace Abstract: An infodemic refers to an enormous amount of true information and misinformation disseminated during a disease outbreak. Detecting misinformation at

tutorialsarxiv-cs-cl

Hardware

EarlyTom: Early Token Compression Completes Fast Video Understanding

arXiv:2605.30010v1 Announce Type: new Abstract: Video large language models (Video-LLMs) have demonstrated strong capabilities in video understanding tasks. However, their practical deployment is stil

hardwarearxiv-cs-cv

EarthShift: a benchmark for measuring robustness to real-world distribution shifts in Earth observation

model-releasesarxiv-cs-cv

arXiv:2605.29330v1 Announce Type: new Abstract: Current Earth observation benchmarks focus on measuring performance on diverse tasks and applications, typically measuring generalization in-distributio

Echoes within the Reasoning: Stealthy and Effective Watermarking via Chain of Thought

arXiv:2605.28890v1 Announce Type: cross Abstract: Large Language Models with Chain-of-Thought reasoning capabilities represent valuable intellectual property, yet existing black-box watermarking metho

Efficient Test-Time Finetuning of LLMs via Convex Reconstruction and Gradient Caching

arXiv:2605.30337v1 Announce Type: new Abstract: Test-time finetuning (TTFT) is a rapidly evolving paradigm that adapts a language model to each prompt by retrieving related sequences, updating the mod

Efficient Training-Free Multi-Token Prediction via Embedding-Space Probing

arXiv:2603.17942v2 Announce Type: replace Abstract: Large Language Models (LLMs) possess latent multi-token prediction (MTP) abilities despite being trained only for next-token generation. We introduc

Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets

arXiv:2605.29720v1 Announce Type: new Abstract: We propose Intrinsic Quality (IQ), a validation-free metric designed to estimate the inherent potential of face recognition (FR) datasets to produce hig

researcharxiv-cs-cv

Eigen-Spike Emergence and Quadratic Equivalents for Conjugate Kernels on Nonlinearly Separable Data

arXiv:2605.29669v1 Announce Type: cross Abstract: Recent work in random matrix theory (RMT) has developed the notion of deterministic equivalents: typically linear surrogate models that approximate th

Tutorials

ElegantVLA: Learning When to Think for Efficient Vision-Language-Action Models

arXiv:2605.29438v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are a powerful paradigm for generalist robotic control. However, their high computational cost and limited control f

tutorialsarxiv-cs-ro

EMAG: Differentiable 4D Gaussian Mixture Splatting for EEG Spatial Super-Resolution

arXiv:2605.29731v1 Announce Type: new Abstract: High-density electroencephalography (HD-EEG) enables fine-grained measurement of cortical activity but requires expensive hardware and lengthy setup tim

Embodied3DBench: Benchmarking Low-Level Embodied Spatial Intelligence of Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2605.29074v1 Announce Type: new Abstract: Are current Vision Language Models (VLMs) ready to comprehend and reason about complex embodied interactions in 3D environments? We introduce Embodied3D

Emergent Semantic Representations in World Models through Physical Interaction without Linguistic Supervision

arXiv:2605.28865v1 Announce Type: cross Abstract: What does a world model learn from physical exploration, without any linguistic supervision? We argue the answer is organized by a single principle: t

Empathic Prompting: Non-Verbal Context Integration for Multimodal LLM Conversations

model-releasesarxiv-cs-ai

arXiv:2510.20743v2 Announce Type: replace-cross Abstract: We present Empathic Prompting, a novel framework for multimodal human-AI interaction that enriches Large Language Model (LLM) conversations wi

Energy-Aware NECO for Single-Pass Pixel-wise Out-of-Distribution Detection in Semantic Segmentation

arXiv:2605.29773v1 Announce Type: cross Abstract: Reliable semantic segmentation for mobile robots requires both accurate dense prediction and robust uncertainty estimation under distribution shift. S

applicationsarxiv-cs-ai

Enhancing Factuality through Consensus and Consistency in Summarization Using Minimum Bayes Risk Decoding

arXiv:2605.29336v1 Announce Type: new Abstract: Improving the quality of model-generated summaries, especially factuality, the accuracy of a summary with respect to its source content, remains a chall

Enhancing LLM Training via Spectral Clipping

arXiv:2603.14315v2 Announce Type: replace Abstract: While spectral-based optimizers like Muon operate directly on the spectrum of updates, standard adaptive methods such as AdamW do not account for th

Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective

arXiv:2505.20955v4 Announce Type: replace-cross Abstract: Diffusion models have achieved tremendous success in image generation, but they also raise significant concerns regarding privacy and copyrigh

Enhancing Multi-Agent Communication through Attention Steering with Context Relevance

arXiv:2605.30136v1 Announce Type: new Abstract: LLM-based multi-agent systems have demonstrated remarkable performance on complex tasks through collaborative reasoning. However, these systems tend to

agentsarxiv-cs-ai

Enhancing Reinforcement Learning in 3D Environments through Semantic Segmentation: A Case Study in ViZDoom

arXiv:2511.11703v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) in 3D environments with high-dimensional sensory input poses two major challenges: (1) the high memory consumption

applicationsarxiv-cs-ai

Ensemble Score Filtering for Real-Data Energy Consumption Forecast Correction

arXiv:2605.29072v1 Announce Type: new Abstract: Accurate estimation and forecasting of energy consumption are important for power-system operation, planning, and demand-side management. In practice, h

Entity-Collision: A Stratified Protocol for Attributing Retrieval Lift in Agent Memory

model-releasesarxiv-cs-ai

arXiv:2605.29630v1 Announce Type: cross Abstract: End-to-end agent-memory benchmarks report a single hit@k per retriever, confounding lexical leakage (uncontrolled query/gold/distractor entity overlap

Entropy-KL Divergence-based Token Masking: A Novel Approach for Selective Fine-tuning of Large Language Models

arXiv:2605.29303v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) followed by reinforcement learning (RL) has become a standard post-training paradigm for large language models. This paradi

Envy-Free Allocation of Indivisible Goods via Noisy Queries

arXiv:2602.06361v2 Announce Type: replace-cross Abstract: We introduce a problem of fairly allocating indivisible goods (items) in which the agents' valuations cannot be observed directly, but instead

agentsarxiv-cs-lg

EPiC: Efficient Video Camera Control Learning with Precise Anchor-Video Guidance

arXiv:2505.21876v2 Announce Type: replace-cross Abstract: Recent approaches for video generation with camera control often create anchor videos (i.e., rendered videos that approximate desired camera m