Search: “reasoning”

MedVision: Benchmarking Quantitative Medical Image Analysis

arXiv:2511.18676v2 Announce Type: replace-cross Abstract: Current vision-language models (VLMs) in medicine are primarily designed for categorical question answering (e.g., 'Is this normal or abnormal

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omega-EVA: Envision, Verify, and Act with Latent Interactive World Models

DGX agent

arXiv:2606.09457v1 Announce Type: new Abstract: Embodied policies typically map current observations directly to actions, leaving candidate-action consequences implicit. World models provide predictiv

safetyarxiv-cs-ro

9 Jun 2026

PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow

arXiv:2606.07549v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patc

Prescriptive Scaling Reveals the Evolution of Language Model Capabilities

arXiv:2602.15327v2 Announce Type: replace-cross Abstract: Machine learning model performance improvements tend to arise from competition and application. For deployment, we consider prescriptive scali

Reward Evolution with Graph-of-Thoughts: A Bi-Level Language Model Framework for Reinforcement Learning

arXiv:2509.16136v5 Announce Type: replace Abstract: Designing effective reward functions remains a major challenge in reinforcement learning (RL), often requiring considerable human expertise and iter

agentsarxiv-cs-ro

RunAgent SuperBrowser: A Theory of Autonomous Web Navigation Grounded in Human Browsing Behaviour

arXiv:2606.09399v1 Announce Type: new Abstract: We present SUPERBROWSER, an autonomous web-navigation agent designed against a single guiding hypothesis: a web agent should browse the way a person bro

Scaling Participation in Modular AI Systems

arXiv:2606.07812v1 Announce Type: new Abstract: Humanity is a mosaic of multifaceted talents and needs, and any truly intelligent AI must reflect that richness. Yet the LLMs used by all are built by t

Sci-Rho: A Multilingual Visually-Grounded Symbolic Benchmark for STEM Problems

arXiv:2606.08034v1 Announce Type: cross Abstract: Symbolic benchmarks have emerged as a key approach to assess model robustness under minor modifications to STEM-related questions. However, existing s

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings

arXiv:2511.05017v2 Announce Type: replace Abstract: Hallucinations in Large Vision-Language Models (LVLMs) remain a persistent challenge, often stemming from inadequate integration of visual informati

safetyarxiv-cs-cv

Variational Proximal Policy Optimization

arXiv:2606.08032v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback via Proximal Policy Optimization often suffers from policy mode collapse, brittle exploration loops, and di

local-aiarxiv-cs-lg

Video Understanding by Design: How Datasets Shape Video Models

arXiv:2509.09151v2 Announce Type: replace-cross Abstract: Research in video understanding has advanced rapidly, driven by increasingly diverse datasets and more powerful model architectures. While exi

When Does Delegation Beat Majority? A Delegation-Based Aggregator for Multi-Sample LLM Inference

arXiv:2606.08098v1 Announce Type: new Abstract: Majority voting over sampled answers is the dominant unsupervised aggregator for multi-sample LLM inference. We show that piping the signals every sampl

Applications

A Dynamic Self-Evolving Extraction System

arXiv:2603.06915v2 Announce Type: replace Abstract: The extraction of structured information from raw text is a fundamental component of many NLP applications, including document retrieval, ranking, a

applicationsarxiv-cs-cl

M^3Exam: Benchmarking Multimodal Memory for Realistic User-Agent Interactions

arXiv:2606.07402v1 Announce Type: new Abstract: Language agents are increasingly deployed over accumulating multimodal information, yet existing benchmarks assume a human-human form with sparse visual

PandaAI: A Practical Agent CQ2 for Neuro-symbolic Data Analysis And Integrated Decision-Making in Quantitative Finance

arXiv:2606.06823v1 Announce Type: cross Abstract: While deep learning has excelled in various domains, its application to sequential decision-making in finance remains challenging due to the low Signa

agentsarxiv-cs-ai

PARSE: Part-Aware Relational Spatial Modeling

arXiv:2603.07704v2 Announce Type: replace Abstract: Inter-object relations underpin spatial intelligence, yet existing representations -- linguistic prepositions or object-level scene graphs -- are to

researcharxiv-cs-cv

Should You Use Your Large Language Model to Explore or Exploit?

arXiv:2502.00225v4 Announce Type: replace-cross Abstract: We evaluate the ability of the current generation of large language models (LLMs) to help a decision-making agent facing an exploration-exploi

agentsarxiv-cs-ai

Skip a Layer or Loop It? Learning Program-of-Layers in LLMs

arXiv:2606.06574v1 Announce Type: new Abstract: Large language models (LLMs) perform inference by following a fixed depth and order, non-recurrent execution of all layers. We reveal the wide existence

researcharxiv-cs-lg

Agent-Orchestrated Adaptive RAG: A Comparative Study on Structured and Multi-Hop Retrieval

arXiv:2606.05658v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by grounding their responses in external knowledge, but conventional pipeli

Benchmark Everything Everywhere All at Once

arXiv:2606.06462v1 Announce Type: new Abstract: Benchmarks are fundamental for evaluating and advancing LLMs and MLLMs by providing standardized and explicit measures of performance. However, their co

Beyond Output Matching: Preserving Internal Geometry in NVFP4 LLM Distillatio

arXiv:2606.05682v1 Announce Type: new Abstract: Demand for low-precision inference, including NVFP4-based approaches, has grown as large language models are increasingly deployed in latency and cost c

Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing

arXiv:2606.05950v1 Announce Type: new Abstract: Text-guided image editing has advanced rapidly with diffusion models and unified multimodal foundation models. However, most existing methods remain con

Reward-Decomposed Reinforcement Learning for Immersive Video Role-Playing

arXiv:2605.04733v2 Announce Type: replace Abstract: Text-based role-playing models can imitate character styles, but often fail to capture scene atmosphere and evolving tension, which are crucial for

The End of Software Engineering: How AI Agents Are Fundamentally Restructuring the Software Paradigm

arXiv:2606.05608v1 Announce Type: cross Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into s

Aligning Tree-Search Policies with Fixed Token Budgets in Test-Time Scaling of LLMs

arXiv:2602.09574v2 Announce Type: replace Abstract: Tree-search decoding is an effective form of test-time scaling for large language models (LLMs), but real-world deployment often imposes a fixed per

EGTR-Review: Efficient Evidence-Grounded Scientific Peer Review Generation via Multi-Agent Teacher Distillation

arXiv:2606.06025v1 Announce Type: new Abstract: Scientific peer review generation has attracted increasing attention for reducing reviewing burdens and providing timely feedback. However, existing Lar

agentsarxiv-cs-cl

Explainability of Large Language Models: Opportunities and Challenges toward Generating Trustworthy Explanations

arXiv:2510.17256v2 Announce Type: replace Abstract: Large language models have exhibited impressive performance across a broad range of downstream tasks in natural language processing. However, how a

local-aiarxiv-cs-cl

LongSpace: Exploring Long-Horizon Spatial Memory from Perception to Recall in Video

arXiv:2606.05677v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have advanced image and video understanding and can increasingly handle longer visual inputs. Long-horizon ta

MCBench: A Multicontext Safety Assessment Benchmark for Omni Large Language Models

arXiv:2606.05177v1 Announce Type: new Abstract: Existing multimodal safety benchmarks focus solely on visual inputs and cannot assess Omni Large Language Models (LLMs) that process vision, audio, and

Visual Commonsense Driven Knowledge Refinements for Scene Graph Generation

arXiv:2606.06369v1 Announce Type: new Abstract: Learning-driven Scene Graph Generation (SGG) models excel on frequent relation types but degrade sharply under annotation sparsity, failing to capture r

researcharxiv-cs-cv

Where, What, Why, and Importance: Structured Defect Grounding for Text-to-Image Feedback

arXiv:2606.06113v1 Announce Type: new Abstract: Despite generating increasingly photorealistic images, text-to-image (T2I) models still exhibit localized, subtle, and structurally complex failures. Di

local-aiarxiv-cs-cv

AgenticDiffusion: Agentic Diffusion-based Path Planning for Vision-Based UAV Navigation

arXiv:2606.04111v1 Announce Type: cross Abstract: Indoor UAV navigation requires efficient exploration, scene understanding, and reliable trajectory execution under limited field-of-view observations.

local-aiarxiv-cs-ai

An Empirical Audit of Input Encoders for Multi-Channel Signal Transformers

arXiv:2606.04752v1 Announce Type: cross Abstract: Transformers consuming multi-channel scalar signals must embed C simultaneous values into one d_{ext{model}}-dimensional vector per time step. We empi

Can I Take Another Dose? Evaluating LLM Decision-Making Under Temporal Uncertainty in OTC Dosing QA

arXiv:2606.04262v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for everyday health questions, including whether a user can safely take another dose of an over-the

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

arXiv:2507.21892v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) mitigates hallucination in LLMs by incorporating external knowledge, but relies on chunk-based retrieval that l

agentsarxiv-cs-cl

Inclusion-of-Thoughts: Mitigating Preference Instability via Purifying the Decision Space

arXiv:2604.04944v2 Announce Type: replace-cross Abstract: Multiple-choice questions (MCQs) are widely used to evaluate large language models (LLMs). However, LLMs remain vulnerable to the presence of

Safety Under Scaffolding: How Evaluation Conditions Shape Measured Safety

arXiv:2603.10044v2 Announce Type: replace-cross Abstract: A safety score earned on a benchmark need not predict how the same model behaves once it is wrapped in an agentic scaffold the benchmark never

Synthetic Personalities: How Well Can LLMs Mimic Individual Respondents Using Socio-Economic Microdata?

arXiv:2606.04592v1 Announce Type: cross Abstract: LLM-based digital twins promise to scale and accelerate market research, but most published twins are either coarse persona bots conditioned on a few

UniCanvas: A Diffusion-base Unified Model for Text-in-Image Joint Generation

arXiv:2606.04264v1 Announce Type: new Abstract: Recent years have seen remarkable progress in unified vision-language models handling both multimodal understanding and generation within a single archi

researcharxiv-cs-cv

VentAgent: When LLMs Learn to Breathe -- Multi-Objective Arbitration for ARDS Ventilation

arXiv:2606.04632v1 Announce Type: cross Abstract: Mechanical ventilation for Acute Respiratory Distress Syndrome (ARDS) requires balancing competing physiological goals, including oxygenation, lung pr

safetyarxiv-cs-cl

A Negative Result on Cross-Model Activation Transfer in a Pythia Multi-Hop Setting

arXiv:2606.03280v1 Announce Type: new Abstract: Recent work shows that language models can transmit behavioural traits through hidden signals in generated data during training. We ask whether a more d

AI Agents Enable Adaptive Computer Worms

arXiv:2606.03811v1 Announce Type: cross Abstract: A computer worm is malware that spreads on a network by replicating itself from one machine to another. Traditional worms, like WannaCry, exploited pr

Constitutional On-Policy Safe Distillation

arXiv:2606.03089v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD) has emerged as an efficient post-training paradigm by using a teacher conditioned on privileged information to prov

Dynamics of Cognitive Heterogeneity: Investigating Behavioral Biases in Multi-Stage Supply Chains with LLM-Based Simulation

arXiv:2604.17220v2 Announce Type: replace-cross Abstract: Modeling coordination among generative agents in complex multi-round decision-making presents a core challenge for AI and operations managemen

Economy of Minds: Emerging Multi-Agent Intelligence with Economic Interactions

arXiv:2606.02859v1 Announce Type: cross Abstract: How can a population of agents self-orchestrate and self-adapt into stronger collective intelligence without centralized control? Inspired by Friedric

agentsarxiv-cs-ai

FGRPO: Federated GRPO with Adaptive Aggregation on Non-IID Data

arXiv:2606.03094v1 Announce Type: new Abstract: Recent advances in language models have established reinforcement learning as the primary paradigm for eliciting self-correction and long-chain reasonin

safetyarxiv-cs-lg

Framing Migration News with LLMs: Structured CoT as a Support for Human Interpretation

arXiv:2606.03761v1 Announce Type: new Abstract: Frame analysis of migration news is a socially consequential task: media scholars and researchers who study how migration is narrated need tools that ar

local-aiarxiv-cs-cl

Learning Self-Interpretation from Interpretability Artifacts: Training Lightweight Adapters on Vector-Label Pairs

arXiv:2602.10352v2 Announce Type: replace-cross Abstract: Self-interpretation methods prompt language models to describe their own internal states, but remain unreliable due to hyperparameter sensitiv