Search: “reasoning”

arXiv:2603.19305v2 Announce Type: replace-cross Abstract: Humanoid robots are expected to execute agile and expressive whole-body motions in real-world settings. Existing text-to-motion generation mod

applicationsarxiv-cs-cv

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Agents

Plausible but Wrong: A case study on Agentic Failures in Astrophysical Workflows

DGX agent

arXiv:2604.25345v2 Announce Type: replace Abstract: Agentic AI systems are increasingly being integrated into scientific workflows, yet their behavior under realistic conditions remains insufficiently

agentsarxiv-cs-ai

25 Jun 2026

Reflective VLA: In-Context Action Consequences Make VLAs Generalize

arXiv:2606.25215v1 Announce Type: new Abstract: Most vision-language-action (VLA) models are reactive: they predict the next action from the current instruction and observation, implicitly assuming th

safetyarxiv-cs-cv

RoDyn: Taming Interactive Robot-Dynamic 2.5D World Model for Robotic Manipulation

arXiv:2510.09036v2 Announce Type: replace Abstract: Learned world models hold significant potential as neural simulators for robotic manipulation. However, prevalent 2D video-based models inherently l

agentsarxiv-cs-ro

Same Evidence, Different Answer: Auditing Order Sensitivity in Multimodal Large Language Models

arXiv:2606.26079v1 Announce Type: new Abstract: Standard benchmarks for multimodal large language models (MLLMs) score each item on one canonical ordering and miss whether order-irrelevant shuffling c

TheoremGraph: Bridging Formal and Informal Mathematics

arXiv:2606.25363v1 Announce Type: cross Abstract: Mathematical knowledge is organized around statements and their dependencies, but this structure is exposed unevenly: informal papers cite mostly at t

agentsarxiv-cs-ai

TIDAL: Temporally Interleaved Diffusion and Action Loop for High-Frequency VLA Control

arXiv:2601.14945v2 Announce Type: replace Abstract: Large-scale Vision-Language-Action (VLA) models offer semantic generalization but suffer from high inference latency, limiting them to low-frequency

safetyarxiv-cs-ro

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG

arXiv:2606.25191v1 Announce Type: cross Abstract: Multi-agent document assessment for retrieval-augmented generation is computationally expensive, driving practitioners toward smaller, deployable mode

agentsarxiv-cs-cl

TRUSTMEM: Learning Trustworthy Memory Consolidation for LLM Agents with Long-Term Memory

arXiv:2606.25161v1 Announce Type: new Abstract: Large language model (LLM) agents rely on long-term memory to support extended interactions and personalized assistance beyond finite context windows. E

researcharxiv-cs-ai

VPA-Guard: Defending and Benchmarking Image-to-Video Generation Against Visual Prompt Attacks

arXiv:2606.25592v1 Announce Type: new Abstract: Recent advancements in Image-to-Video (I2V) generation have transformed input images from simple appearance references into interactive control interfac

Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models

arXiv:2606.25041v1 Announce Type: new Abstract: We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex

researcharxiv-cs-cv

What Does It Mean to Break a Distillation Defense?

arXiv:2606.25059v1 Announce Type: cross Abstract: Black-box LLMs (accessible only via API) are vulnerable to distillation attacks, in which an attacker queries the model and trains a student on its ou

WOLF-VLA: Whole-Body Humanoid Optimal Locomotion Framework for Vision-Language-Action Learning

model-releasesarxiv-cs-ro

arXiv:2606.25591v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently demonstrated strong generalization in robotic manipulation, yet their applicability to whole-body, con

Hardware

Accelerating Disaggregated RL for Visual Generative LLMs with Diffusion-Based Parallelism and Trainer-Assisted Generation

arXiv:2606.24369v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a dominant post-training paradigm, driving the emergence of high-performance RL systems such as veRL for autoregr

hardwarearxiv-cs-ai

AgentRivet: an automated system for producing Rivet routines from journal publications

arXiv:2606.13535v3 Announce Type: replace-cross Abstract: Particle physics collider experiments provide Rivet routines as part of the analysis preservation strategy for model-independent measurements.

agentsarxiv-cs-ai

Applications

AI Tokenomics: The Economics of Tokens, Computation, and Pricing in Foundation Models

arXiv:2606.24616v1 Announce Type: new Abstract: Tokens have become the practical accounting unit for modern foundation model services, linking information processing, computation, memory use, energy e

applicationsarxiv-cs-ai

Are Safety Guarantees in Neural Networks Safe? How to Compute Trustworthy Robustness Certifications

arXiv:2606.23858v1 Announce Type: cross Abstract: A primary challenge in AI safety is the existence of adversarial examples -- slightly distorted inputs that cause a neural network (NN) to misclassify

AsyncOPD: How Stale Can On-Policy Distillation Be?

arXiv:2606.24143v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts guided by teacher feedback and is becoming increasingly important for large language m

safetyarxiv-cs-lg

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models

arXiv:2606.24152v1 Announce Type: new Abstract: Existing literature claims that video generation essentially is world modelling. On the one hand, the claim is productive because it pushes generative A

agentsarxiv-cs-cv

CAVEWOMAN: How Large Language Models Behave Under Linguistic Input and Output Compression

arXiv:2606.24083v1 Announce Type: cross Abstract: 'Talk short. Drop grammar. Save token.' This caveman style is widely promoted as a way to cut inference cost, but whether it actually saves anything d

Critique of Agent Model

arXiv:2606.23991v1 Announce Type: new Abstract: What is an agent? What constitutes agency? With the rise of Large Language Model (LLM) systems marketed as ``coding agents'', ``AI co-scientists'', and

Emergent Relational Order in LLM Agent Societies: From Collective Affect to Authority Stratification

arXiv:2606.23764v1 Announce Type: cross Abstract: Fei Xiaotong's Differential Order Pattern characterizes rural society as egocentric and relationally graded, with cooperation attenuating over social

agentsarxiv-cs-ai

GENA3D: Generative Amodal 3D Modeling by Bridging 2D Priors and 3D Coherence

arXiv:2511.21945v3 Announce Type: replace Abstract: Generating complete 3D objects under partial occlusions (i.e., amodal scenarios) is a practically important yet challenging problem, as large portio

safetyarxiv-cs-cv

HANCLIP: A Family of Hyperbolic Angular Negation Vision Language Models

arXiv:2606.23843v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are typically pre-trained on large-scale image-text datasets to capture semantic correspondences between visual content an

MedBench v5: A Dynamic, Process-Oriented, and Hallucination-Aware Benchmark for Clinical Multimodal Models

arXiv:2606.24155v1 Announce Type: new Abstract: Existing medical AI benchmarks lack process visibility, atomic skill evaluation, and integrated hallucination detection. We introduce MedBench v5, a red

Multimedia and Visual Analytics in the Agentic Era

arXiv:2504.06138v3 Announce Type: replace-cross Abstract: Professional users need tools to help them gain actionable insights from large multimedia collections. Foundation models and AI agents have ra

NavWM: A Unified Navigation World Model for Foresight-Driven Planning

arXiv:2606.24101v1 Announce Type: cross Abstract: Conventional visual navigation policies often struggle with myopic decision-making and mode collapse in complex environments. While world models offer

agentsarxiv-cs-cv

PETRA: Transforming Web Text for Petroleum-Engineering Domain Adaptation

arXiv:2606.24346v1 Announce Type: cross Abstract: Petroleum-engineering search exposes a supervision gap for strong general retrievers: relevant evidence exists in public web text, but domain relevanc

Quantifying Prior Dominance in RAG Systems

arXiv:2606.23695v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Models in external knowledge, yet current evaluations rely on discrete heuristics that suf

researcharxiv-cs-ai

Robust Dual-Signal Fusion: Hybrid Neuro-Symbolic Gating with Compressed Chain-of-Thought Refinement for Irony Detection in Social Media Texts

arXiv:2606.16845v2 Announce Type: replace-cross Abstract: Small-scale Large Language Models (LLMs) natively default to literal semantic interpretations, making few-shot irony detection a persistent ch

researcharxiv-cs-ai

RoPE-Aware Bit Allocation for KV-Cache Quantization

arXiv:2606.24033v1 Announce Type: cross Abstract: Existing low-bit KV-cache quantizers often treat each cached key as a flat vector. Under RoPE, however, a key's contribution to a future attention log

Rule2Text: A Framework for Generating and Evaluating Natural Language Explanations of Knowledge Graph Rules

arXiv:2508.10971v2 Announce Type: replace-cross Abstract: Knowledge graphs (KGs) can be enhanced through rule mining; however, the resulting logical rules are often difficult for humans to interpret d

SAFARI: Scaling Long Horizon Agentic Fault Attribution via Active Investigation

arXiv:2606.24626v1 Announce Type: new Abstract: As autonomous agents tackle increasingly complex multi-step, multi-agent tasks, their execution trajectories have scaled beyond the constraints of even

Applications

Scaling Laws for Task-Specific LLM Distillation

arXiv:2606.24747v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong performance across a growing range of domains, yet their scale poses deployment challenges in applications w

applicationsarxiv-cs-ai

TACTFUL: Tactile-Driven Exploration For Object Localization and Identification in Confined Environments

arXiv:2606.24712v1 Announce Type: cross Abstract: Humans effortlessly locate and identify objects by touch alone, even without vision. In contrast, robotic systems rely heavily on vision and struggle

Trimming the Long-Tail of Visual World Modeling Evaluation

arXiv:2606.24256v1 Announce Type: new Abstract: Physical interactions follow a long-tailed distribution: a set of common and regular interactions dominates human experience and visual data, while a br

Trustworthy Image Authentication using Forensic Knowledge Graphs

arXiv:2606.23917v1 Announce Type: new Abstract: Advances in generative AI have made image falsification highly realistic, demanding trustworthy authentication systems. Existing forensic detectors can

researcharxiv-cs-cv

Tuning without Peeking: Provable Generalization Bounds and Robust LLM Post-Training

arXiv:2507.01752v4 Announce Type: replace-cross Abstract: Gradient-based optimization is the workhorse of deep learning, offering efficient and scalable training via backpropagation. However, exposing

Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent

arXiv:2606.24094v1 Announce Type: new Abstract: Unifying image clustering across different clustering scenarios remains challenging due to fundamental gaps among tasks. We introduce a Guideline-Driven

agentsarxiv-cs-cv

video-SALMONN-R^3: Learning to ReWatch, ReAsk, and ReAnswer for Efficient Video Understanding

arXiv:2606.24477v1 Announce Type: cross Abstract: Video large language models (LLMs) are often constrained by computation and memory budgets, leading them to use reduced frame rates and spatial resolu

VieSpeaker: A Large-Scale Vietnamese Speaker Recognition Dataset Beyond Visual Dependency

arXiv:2606.24066v1 Announce Type: cross Abstract: Speaker recognition has advanced rapidly with large-scale training datasets, yet Vietnamese remains under-resourced, with existing corpora limited in

researcharxiv-cs-cl

VisCritic: Visual State Comparison as Process Reward for GUI Agents

arXiv:2606.24525v1 Announce Type: new Abstract: GUI agents powered by vision-language models show strong potential for automating digital tasks, yet frequently fail in long-horizon scenarios due to th

When Helpfulness Overrides Causal Caution: Context-Dependent Suppression and Recovery in LLMs

arXiv:2606.24370v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into decision-support roles in business and policy contexts. While prior benchmark studies have

Local Ai

A DVDrive Approach for doScenes Instructed Driving Challenge

arXiv:2606.21623v1 Announce Type: new Abstract: Instruction-conditioned trajectory prediction is an emerging problem in autonomous driving, where a model predicts the future ego trajectory not only fr

local-aiarxiv-cs-cv

A-Evolve-Training: Autonomous Post-Training of a 30B Model

model-releasesarxiv-cs-lg

arXiv:2606.20657v1 Announce Type: cross Abstract: Post-training a frontier model is normally weeks of human work: proposing data and recipe changes, launching runs, reading evals, deciding what to kee

A Verifiable Search Is Not a Learnable Chain-of-Thought

model-releasesarxiv-cs-lg

arXiv:2606.21884v1 Announce Type: new Abstract: It is tempting to assume any task solvable by a short program can be taught to a model as its chain-of-thought: write the steps out, fine-tune, and the

An Empirical Study of OpenPangu Quantization on Ascend NPUs

arXiv:2606.21257v1 Announce Type: new Abstract: OpenPangu models are attractive targets for private and domestic large-language-model deployment, yet their robustness under aggressive post-training qu

researcharxiv-cs-lg

Any-Body Guard: Universal Safeguarding for Manipulation Policies via Action Masking

arXiv:2606.22278v1 Announce Type: cross Abstract: Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. Existing

safetyarxiv-cs-lg