Search: “reasoning”

TaxoMIL: Taxonomy-Constrained Learning for Hierarchical Whole Slide Image Analysis

arXiv:2606.31100v1 Announce Type: new Abstract: Whole slide image (WSI) analysis is central to computational pathology, with multiple instance learning (MIL) emerging as the standard pipeline for slid

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Theory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action

DGX agent

arXiv:2606.31916v1 Announce Type: new Abstract: Theory of Mind (ToM) benchmarks for Large Language Models (LLMs) typically rely on passive question-answering formats, but the deployment of LLMs in inc

model-releasesarxiv-cs-cl

1 Jul 2026

Thinking Before Retrieving: Robust Zero-Shot Composed Image Retrieval via Strategic Planning and Self-Criticism

arXiv:2606.31222v1 Announce Type: new Abstract: Composed image retrieval requires identifying a target image from a gallery by integrating a reference image with a textual modification instruction. In

This is pretty concerning. You could still do this at the API level to some degree, but they seemingly just blatantly put it right into the …

model-releasesnous-research--x

This is pretty concerning. You could still do this at the API level to some degree, but they seemingly just blatantly put it right into the code? This is why open harnesses and agents are a much bette

UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation

arXiv:2606.31451v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) have shown great promise in integrating understanding and generation across diverse modalities. However, existing res

Applications

UniTacVLA: Unified Tactile Understanding and Prediction in Vision Language Action Models

arXiv:2606.31723v1 Announce Type: new Abstract: Vision-language-action (VLA) models have achieved strong performance in many robotic manipulation tasks, yet remain limited in contact-rich dexterous ma

applicationsarxiv-cs-ro

Using AI Agents to Automate Black-Box Audits of Personalization Algorithms at Scale

arXiv:2606.30801v1 Announce Type: new Abstract: Personalization algorithms determine what content users encounter on online platforms. Auditing these systems is difficult because independent auditors

agentsarxiv-cs-cl

Verification-Gated Agentic Mission-State Governance for Intelligent Industrial Multi-Robot Systems

arXiv:2606.31339v1 Announce Type: new Abstract: Agentic artificial intelligence is increasingly used to decompose industrial tasks, propose robot actions, and adapt execution plans in dynamic cyber-ph

safetyarxiv-cs-ro

What Probing Reveals about Autonomous Driving: Linking Internal Prediction Errors to Ego Planning

arXiv:2606.31106v1 Announce Type: cross Abstract: Large-scale datasets and fast simulators have enabled improvements in driving policies that appear safe and robust, yet strong performance in nominal

When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors

arXiv:2606.32029v1 Announce Type: cross Abstract: While large language models (LLMs) perform well on table tasks, they still make data referencing errors (DREs), i.e., incorrectly citing or omitting t

When Sinks Help or Hurt: Unified Framework for Attention Sink in Large Vision-Language Models

arXiv:2604.03316v2 Announce Type: replace Abstract: Attention sinks are defined as tokens that attract disproportionate attention. While these have been studied in single modality transformers, their

researcharxiv-cs-cv

WorldRoamBench: An Open-World Benchmark for Long-Horizon Stability of Interactive World Models

arXiv:2606.31672v1 Announce Type: cross Abstract: Despite rapid progress in interactive world models (IWMs), existing benchmarks evaluate action following only at trajectory level and ignore memory an

You can now run recursive language model (RLM) workflows in Deep Agents. Everything you need to know in 6 minutes from @sydneyrunkle.

Recursive Language Model (RLM) workflows are now available as a feature in Deep Agents, allowing AI systems to iteratively call language models within multi-step processes. This capability enables mor

agentsharrison-chase--x

3D Scene-Adaptive Trajectory-Controllable Human Image Animation with Camera Movement

arXiv:2606.30514v1 Announce Type: new Abstract: Human image animation, which aims to generate a video of a reference subject following a provided action sequence, has received increasing research inte

A Machine-Verified Proof of a Quantum-Optimization Conjecture

arXiv:2606.29687v1 Announce Type: cross Abstract: We report a machine-verified resolution of a problem open for over a decade in quantum optimization: the Farhi, Goldstone and Gutmann (FGG) conjecture

A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions

arXiv:2606.28943v1 Announce Type: new Abstract: Learning to bid in repeated multi-unit auctions with bandit feedback poses a fundamental challenge. Existing methods often rely on rigid explore-then-ex

safetyarxiv-cs-cl

Agentic Abstention: Do Agents Know When to Stop Instead of Act?

arXiv:2606.28733v1 Announce Type: new Abstract: LLM agents are expected to act over multiple turns, using search, browsing interfaces, and terminal tools to complete user goals. Yet not every goal is

Agentic AI for ISAC: Analysis, Framework, and Case Study

arXiv:2512.15044v2 Announce Type: replace Abstract: Integrated sensing and communication (ISAC) has emerged as a key development direction in the sixth-generation (6G) era, which provides essential su

agentsarxiv-cs-ai

Analytic Concept-Centric Memory for Agentic Embodied Manipulation

arXiv:2606.29774v1 Announce Type: new Abstract: Long-horizon embodied manipulation requires agents to remember persistent objects, track changing scene states, and reuse prior interaction knowledge. H

safetyarxiv-cs-ro

Anthropic integration with Modal brings scalable compute to Claude Science

Anthropic has integrated Claude with Modal's serverless compute platform, enabling scalable cloud infrastructure for scientific computing workflows. This integration allows Claude to leverage Modal's

model-releasesmodal-blog

Applications

Auditing LLM-Governed Social Robots with Culture-Specific Moral Gradients

arXiv:2606.28345v1 Announce Type: cross Abstract: LLM-governed social robots increasingly decide who receives real-world assistance first. As prioritization norms vary across cultures by age, status,

applicationsarxiv-cs-ai

AURORA: Asymmetry and Update-Induced Rotation for Robust Hallucination Detection in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.29545v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing tasks. However, their tendency

BackTranslation2.0 -- A Linguistically Motivated Metric to Assess Sign Language Production

arXiv:2606.28673v1 Announce Type: new Abstract: Sign Languages (SLs) are the primary means of communication for millions of deaf individuals, yet existing evaluation metrics for generated SL remain si

agentsarxiv-cs-cv

Benchmarking LLM Agents on Meta-Analysis Articles from Nature Portfolio

arXiv:2606.17041v4 Announce Type: replace Abstract: Meta-analysis is a demanding form of evidence synthesis that combines literature retrieval, PI/ECO-guided study selection, and statistical aggregati

agentsarxiv-cs-cl

Beyond Triplet Plausibility: Relation Set Completion in Knowledge Graphs

arXiv:2606.29860v1 Announce Type: new Abstract: Knowledge graphs (KGs) organize real-world knowledge as triplets and underpin many downstream applications. Due to their inherent incompleteness, knowle

Bit-ViP: Leveraging Bit-planes to Preserve Visual Privacy in Images through Obfuscation

arXiv:2606.29417v1 Announce Type: new Abstract: The unprecedented growth of computer vision applications, such as surveillance systems and social media, raises security and visual privacy concerns, es

researcharxiv-cs-cv

BrepLLM: Enabling Large Language Models to Understand Boundary Representations

arXiv:2512.16413v2 Announce Type: replace Abstract: Current token-sequence-based Large Language Models (LLMs) struggle to directly process 3D Boundary Representation (B-rep) models that contain comple

BV-Blend: Uncertainty-Weighted Historical Baselines for Stable Critic-Free RL with Verifiable Rewards

arXiv:2606.28707v1 Announce Type: new Abstract: Critic-free reinforcement learning with verifiable rewards (RLVR), exemplified by Group Relative Policy Optimization (GRPO), avoids training a value fun

Can LLMs Reliably Self-Report Adversarial Prefills, and How?

arXiv:2606.23671v2 Announce Type: replace Abstract: Prior work shows that large language models (LLMs) exhibit introspective capability on benign tasks. We extend the question to safety contexts and e

safetyarxiv-cs-cl

Characterizing Large Language Model Agentic Workflows: A Study on N8n Ecosystem

arXiv:2606.29116v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combin

CLQT: A Closed-Loop, Cost-Aware, Strategy-Consistent Benchmark for Diagnostic Evaluation of LLM Portfolio-Management Agents

arXiv:2606.29771v1 Announce Type: new Abstract: LLM agents are increasingly cast as autonomous portfolio managers, and benchmarks have moved from financial question-answering to sequential trading. Ye

COMPASS: Grounding Composition-Intent Guidance in Unified Multimodal Models

arXiv:2606.28696v1 Announce Type: new Abstract: Composition is a high-level visual intent that governs where subjects are placed and how a scene is organized, yet current unified multimodal models rem

Conversational Query Engine for Mixed-Modality Heterogeneous Enterprise Data Sources

arXiv:2606.28370v1 Announce Type: cross Abstract: Enterprise business intelligence queries span structured warehouses and unstructured document repositories -- modalities with fundamentally different

CORTEX: High-Quality Cross-Domain Organization of Web-Scale Corpora through Ontological Corpus Graph

model-releasesarxiv-cs-cl

arXiv:2606.30175v1 Announce Type: new Abstract: The continuous evolution of large language models drives escalating demands on data scale and quality, and as different training stages impose increasin

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

arXiv:2511.02734v3 Announce Type: replace Abstract: Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability

Couchbase’s AI Data Plane aims to turn fragmented data into real enterprise agent memory

Couchbase Inc. is trying to solve one of the hardest problems in enterprise artificial intelligence today: turning brittle, chat-style pilots into production-grade agents capable of remembering, reaso

agentssiliconangle

Coverage-Driven KV Cache Eviction for Efficient and Improved Inference of LLM

arXiv:2606.29563v1 Announce Type: cross Abstract: Large language models (LLMs) excel at complex tasks like question answering and summarization, thanks to their ability to handle long-context inputs.

Cybersecurity is the True Frontier for Generative AI Success or Failure

arXiv:2606.28929v1 Announce Type: cross Abstract: Cybersecurity is a real-life test-bed for many machine learning problems at once, especially when considering modern strides in using Large Language M

researcharxiv-cs-lg

Database Context Compression for Text-to-SQL on Real-World Large Databases

arXiv:2606.28601v1 Announce Type: cross Abstract: Recent progress in Text-to-SQL has been driven by stronger language models and prompting strategies, yet performance on real enterprise benchmarks suc

Developmental Trajectories of Situation Modeling and Mentalizing in Transformer Language Models

arXiv:2606.28524v1 Announce Type: new Abstract: Recent work suggests that Large Language Models (LLMs) are sensitive to the belief states of agents described by text, as measured by the false belief t

agentsarxiv-cs-cl

Diffusion Models Observe Only Gradients: A Geometric Perspective on Score Matching Errors

arXiv:2606.06179v2 Announce Type: replace-cross Abstract: Score-based diffusion models are typically trained by minimizing the L^2 score matching error, and standard theoretical analyses rely on this

researcharxiv-cs-lg

Digitizing Coaching Intelligence: An Agentic Framework for Holistic Athlete Profiling using VLM and RAG

arXiv:2606.28570v1 Announce Type: cross Abstract: Athlete assessment is a critical process for tracking physical progress and identifying elite talent. However, during mass recruitment drives, traditi

Distributionally Robust Reinforcement Learning with Human Feedback

arXiv:2503.00539v2 Announce Type: replace-cross Abstract: Reinforcement learning from human feedback (RLHF) has evolved to be one of the main methods for fine-tuning large language models (LLMs). Howe

DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks

arXiv:2503.09679v2 Announce Type: replace-cross Abstract: Meta-learning represents a strong class of approaches for solving few-shot learning tasks. Nonetheless, recent research suggests that simply p

researcharxiv-cs-cv

Efficient Visual Pointing for Embodied AI:Agent-Driven Data Synthesis, Cross-Block Attention, and Iterative Correction

arXiv:2606.29850v1 Announce Type: new Abstract: Visual pointing maps a language instruction to pixel co ordinates, a core skill for embodied AI. We describe our PointArena 2026 solution, which achieve

Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems

arXiv:2504.02918v3 Announce Type: replace Abstract: Recent advances in image and video generation raise hopes that these models possess world modeling capabilities-the ability to generate realistic, p

agentsarxiv-cs-cv

Applications

Event-VLA: Action-Conditioned Event Fusion for Robust Vision-Language-Action Model

arXiv:2606.29384v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become an important paradigm of embodied AI. However, existing VLA models typically assume well-lit and stable

applicationsarxiv-cs-cv

Evidence-Informed LLM Beliefs for Continual Scientific Discovery

arXiv:2606.29182v1 Announce Type: new Abstract: Open-ended scientific discovery with large language models (LLMs) increasingly operates as a long-horizon loop of hypothesis search and verification, wh