Search: “reasoning”

Representation-Based Exploration for Language Models: From Test-Time to Post-Training

arXiv:2510.11686v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) promises to expand the capabilities of language models, but it is unclear if current RL techniques promote the dis

16 Jul 2026

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The Entanglement Wall: Activation-Space Probes as Risk Detectors, Not Context Adjudicators

DGX agent

arXiv:2607.13075v1 Announce Type: cross Abstract: Context can change whether a request is harmful without changing its topic or surface form. We ask whether residual-stream probes distinguish harmful

researcharxiv-cs-ai

16 Jul 2026

Theory-Level Autoformalization: From Isolated Statements to Unified Formal Knowledge Bases

arXiv:2607.13292v1 Announce Type: new Abstract: Autoformalization translates informal natural language into formal, machine-verifiable languages. While most work focuses on individual statements, real

16 Jul 2026

A Threshold Exceedance Framework for CBRN Uplift Evaluation in Frontier Language Models

arXiv:2607.12200v1 Announce Type: new Abstract: As frontier language models advance, policymakers and model developers need methods for assessing whether model access materially increases a non-expert

Auditing Data Leakage in Whole-Slide Image Multimodal Benchmarks

model-releasesarxiv-cs-cv

arXiv:2607.12278v1 Announce Type: new Abstract: Recent vision-language models (VLMs) for computational pathology report striking zero-shot performance on whole-slide image (WSI) visual question answer

AutoTrace: From Patches to Triggers via Agentic Interprocedural Exploration

arXiv:2607.12058v1 Announce Type: cross Abstract: Given a vulnerability-fixing commit, trigger localization asks which specific statement turns the vulnerable program state into a concrete unsafe oper

AVQ-Attention: Adaptive Vector-Quantized Attention

arXiv:2607.12789v1 Announce Type: cross Abstract: The O(N^2) complexity of attention over N tokens remains a computational bottleneck in transformer models. Vector-Quantized (VQ) attention reduces thi

researcharxiv-cs-cv

Belief-reality separation lives in routing over a shared value slot in language models

model-releasesarxiv-cs-cl

arXiv:2607.11945v1 Announce Type: new Abstract: Capable language models hold what a character believes apart from what is true: told 'Anna believes the cup is blue; in reality it is red,' they answer

CANDI: Contextual Alignment for Niche Domains Question Answering

arXiv:2607.11891v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) in specialized domains like medical diagnostics and financial advisory necessitates evaluating capabili

Contract-Grounded Behavior Tree Synthesis via Coding Agents

arXiv:2607.12220v1 Announce Type: new Abstract: Synthesizing deployable robot behavior trees (BTs) from natural language (NL) requires grounding to ensure every generated BT references only skills a r

agentsarxiv-cs-ro

Contrastive-Augmented Flow Matching for Style-Content Disentanglement

arXiv:2607.12404v1 Announce Type: new Abstract: Learning representations that separate content and style is crucial for controllable generation and compositional generalization. However, diffusion and

applicationsarxiv-cs-cv

CrochetBench: Can Vision-Language Models Move from Describing to Doing in Crochet Domain?

arXiv:2511.09483v3 Announce Type: replace Abstract: While multimodal large language models can describe visual content, their ability to generate executable procedures remains underexplored. CrochetBe

DA-Nav: Direction-Aware City-Scale Vision-Language Navigation

arXiv:2607.11638v2 Announce Type: replace Abstract: City-scale outdoor navigation is currently hindered by the heavy reliance on dense maps or costly navigation supervision. In this work, we introduce

applicationsarxiv-cs-ro

Declarative by Design, Assistable Only by Convention: Benchmarking Multi-Agent Frameworks for AI-Assistability

arXiv:2602.11198v2 Announce Type: replace-cross Abstract: Multi-agent frameworks (MAFs) promise to simplify LLM-driven software development, yet no principled metric captures how well AI coding assist

Do You Remember? Toward Memory-Centric Multimodal AI

arXiv:2607.11919v1 Announce Type: cross Abstract: Human memory is reconstructive, not a faithful recording. Current multimodal LLMs (MLLMs) lack this capability: they process images through a frozen v

Evaluating Nonuniform Dependability Across Response Conditions: A Conditional Generalizability Framework Illustrated in Automated Essay Scoring

arXiv:2607.11981v1 Announce Type: cross Abstract: Aggregate reliability estimates can obscure heterogeneity in measurement-design burden across response conditions, so a single G- or D-study may misch

Evaluating Reliability in Machine Learning Models for Early Chronic Kidney Disease Prediction: A Systematic Review of Data Leakage and Predictor Stability

arXiv:2607.11963v1 Announce Type: cross Abstract: The early detection of Chronic Kidney Disease using machine learning has attracted significant interest in healthcare-related computer science. Despit

applicationsarxiv-cs-ai

Evidence-Grounded AI for Musculoskeletal Care

arXiv:2607.12527v1 Announce Type: new Abstract: Musculoskeletal diseases are among the leading causes of disability worldwide and create the greatest global need for rehabilitation. Because recovery,

From Critic to Confidence: PPO for Language-Based Quantitative Prediction with Confidence Estimation

arXiv:2607.12687v1 Announce Type: cross Abstract: LLMs can perform language-based quantitative prediction from unstructured inputs, but remain susceptible to hallucinations and overconfident errors, m

From Observation to Insight: Mechanistic World Models and the Quest for Autonomous Discovery

arXiv:2607.12474v1 Announce Type: new Abstract: Recent advances in foundation models have transformed AI for Science, enabling remarkably accurate predictive performance across domains ranging from pr

Gene Expression-Informed Jointly Controlled Generative Modeling for Precision Molecular Design

arXiv:2607.11978v1 Announce Type: cross Abstract: Precision molecular design aims to discover personalized drug candidates through joint control of multiple conditions, such as biological relevance an

Git-Assistant: Planning-Based Support for Updating Git Repositories

arXiv:2607.09224v2 Announce Type: replace-cross Abstract: Version control systems are essential for collaborative software development, yet tools like git remain challenging for many practitioners. Re

Higher Embedding Dimension Creates a Stronger World Model for a Simple Sorting Task

arXiv:2510.18315v2 Announce Type: replace-cross Abstract: We investigate how embedding dimension affects the emergence of an internal 'world model' in a transformer trained with reinforcement learning

Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answering

arXiv:2603.28583v2 Announce Type: replace-cross Abstract: Despite the success of Vision-Language Models (VLMs), misleading charts remain a significant challenge due to their deceptive visual structure

Local Ai

Open-KNEAD: Knowledge-grounded Nutrition Estimation via Agentic Decomposition

arXiv:2607.12911v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly used for dietary assessment from meal images, where retrieval-augmented grounding was shown to

local-aiarxiv-cs-cv

Operationalising Multi-Dimensional Evaluation for Conversational Agents: A Scalable, Governed Pipeline with Selective Re-evaluation and Model Benchmarking

arXiv:2607.12085v1 Announce Type: new Abstract: Evaluating retail conversational agents requires methods beyond lexical-overlap metrics to assess intent alignment, factuality, helpfulness, clarity, to

Optimization Is Not All You Need

arXiv:2607.11977v1 Announce Type: new Abstract: In 2019, OpenAI released two million GPT-2 outputs-ungrammatical, half broken-to aid the detection of machine-generated text. The alignment that produce

ProtoPointNet: Prototype-Based Interpretable Classification of 3D Dental Point Clouds with Verifiable Spatial Activations

arXiv:2607.12335v1 Announce Type: new Abstract: Prototype-based networks provide inherently interpretable classification by linking predictions to learned exemplars, but their use in 3D point clouds a

researcharxiv-cs-cv

RecRec: Recursive Refinement for Sequential Recommendation

model-releasesarxiv-cs-lg

arXiv:2607.10541v2 Announce Type: replace-cross Abstract: Sequential recommender systems typically infer user preferences through single-pass encoding of interaction histories without iterative refine

Resist and Update: Counterfactual Report Coordinates for Incentive-Compatible LLMs

arXiv:2607.12985v1 Announce Type: new Abstract: Aligned language models routinely misreport under non-evidential incentive pressure: they agree with a confident user or overstate certainty even when t

Sensitivity to Subjective Expected Utility Maximization: A Methodological Study, with an Illustrative Application to LLM Decision-Making

arXiv:2607.11920v1 Announce Type: cross Abstract: Evaluating decisions made under uncertainty is hard when labeled outcomes are scarce, costly, or confounded with luck. We treat subjective expected ut

The Illusion of Robustness: Aggregate Accuracy Hides Prediction Flips under Task-Irrelevant Context

model-releasesarxiv-cs-cl

arXiv:2607.12963v1 Announce Type: new Abstract: As large language models (LLMs) grow more capable, they are increasingly deployed in context-rich settings where task inputs are often accompanied by lo

Local Ai

Toward Localizing and Repairing Bias in Transformer Attention Heads

arXiv:2607.12863v1 Announce Type: cross Abstract: Transformer language models are increasingly used as software components, yet biased outputs remain difficult to localize and repair inside the model.

local-aiarxiv-cs-lg

Local Ai

TSCA-Net: Temporal-Spatial Clique Attention for Interpretable Multimodal Pedestrian Trajectory Prediction

arXiv:2607.11939v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction in crowded environments remains challenging due to the multimodal uncertainty of human motion and the variable

local-aiarxiv-cs-cv

VistaVLA: Geometry- and Semantic-Aware 3D Gaussian-Grounded VLA for Robotic Manipulation

arXiv:2607.12356v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a powerful end-to-end paradigm for robotic manipulation by mapping language instructions and 2D visu

safetyarxiv-cs-ro

What Does a Temporal Benchmark Score Measure? Decomposing Channel Use in Video VLM Evaluation

model-releasesarxiv-cs-cv

arXiv:2607.12304v1 Announce Type: new Abstract: A score on a temporal video question answering benchmark is meant to measure that a model has temporal understanding, but it conflates two questions. 1.

Xray-Visual Models: Scaling Vision models on Industry Scale Data

arXiv:2602.16918v2 Announce Type: replace-cross Abstract: We present Xray-Visual, a unified vision model architecture for large-scale image and video understanding trained on industry-scale social med

applicationsarxiv-cs-ai

A Vision Toward Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents

arXiv:2510.22052v2 Announce Type: replace Abstract: The field of artificial intelligence (AI) has taken a tight hold on broad aspects of society, industry, business, and governance in ways that dictat

Classifier Chain-based Pathological Test Recommendation

arXiv:2607.08299v1 Announce Type: new Abstract: Accurate and timely diagnoses are essential for quality patient care. However, delayed recommendation of diagnostic tests and physicians' subjective int

researcharxiv-cs-lg

FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation

arXiv:2607.08359v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs

ImputeViz: A Visual Analytics Dashboard for Diagnosing Missing Data and Comparing Imputation Methods

arXiv:2607.08579v1 Announce Type: cross Abstract: Missing data is a persistent obstacle in scientific, social science, and public health research, often biasing analyses and placing accountability on

researcharxiv-cs-lg

LEEVLA: Seeing What Matters in Latent Environment Evolution for Vision-Language-Action

arXiv:2607.08182v1 Announce Type: cross Abstract: Vision-language-action (VLA) models aim to map multimodal inputs to robot actions. However, most existing approaches struggle to cover complex dynamic

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs

arXiv:2607.07903v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks. Existing appro

Playing ZendoWorld: Challenging AI Agents on Active Visual Concept Induction

arXiv:2607.08233v1 Announce Type: new Abstract: A central challenge in building intelligent systems is enabling agents to jointly perceive complex inputs, form hypotheses about hidden patterns, and de

Reinforcing the Generation Order of Multimodal Masked Diffusion Models

arXiv:2607.08056v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that a

Trustworthy Machine Learning through the Lens of Combinatorial Optimization: Survey and Research Perspectives

arXiv:2607.07762v1 Announce Type: new Abstract: Modern machine learning (ML) increasingly relies on complex models whose behavior is difficult to characterize beyond empirical performance metrics. Acr

safetyarxiv-cs-lg

Understanding Axes of Difficulty For Long Context Tasks Via PredicateLongBench

arXiv:2607.08284v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated rapidly improving long-context capabilities, prompting a wave of benchmarks designed to evaluate them. Ho

Whareformer: Learning to Track What is Where in Long Egocentric Videos

arXiv:2607.08537v1 Announce Type: new Abstract: The recently established 'Out of Sight, Not out of Mind' (OSNOM) task for egocentric videos focuses on tracking objects that are moved by the camera wea

researcharxiv-cs-cv