Search: “llm”

A Low Grounding Score Is Not an Ungrounded Judge: Identifying the Perceptibility Confound in Multimodal Oversight

arXiv:2610.00111v1 Announce Type: new Abstract: Model judges now supervise multimodal systems at scale, filtering training data, selecting outputs, and supplying the reward that shapes multimodal reas

researcharxiv-cs-cv

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A rubric landscape for evaluating clinical reasoning in large language models: what exists, what is missing, and what needs to be combined

DGX agent

arXiv:2610.01938v1 Announce Type: cross Abstract: Exam-style accuracy does not establish whether large language models (LLMs) reason well over clinical records. We define clinical reasoning as integra

safetyarxiv-cs-ai

2 Oct 2026

AF-Muon: An AdamW-Free Muon Optimizer for Tied-Embedding Models

arXiv:2610.01395v1 Announce Type: new Abstract: Muon improves large-scale training by applying a spectral-norm steepest-descent update to matrix parameters, but practical models also contain parameter

Agents Are Systems, Not Models: Rethinking Agentic Evaluation

arXiv:2610.01618v1 Announce Type: new Abstract: Agent evaluations increasingly go beyond a single success rate, reporting metrics such as cost, consistency, and robustness. Yet they typically treat th

Authorization for Self-Modifying AI Agent Populations: Conserving Authority across Replacement, Forking, and Rollback

arXiv:2610.00347v1 Announce Type: cross Abstract: Self-modifying AI agents can replace, fork, and roll back identity-bearing software while descendants remain executable. Per-successor authorization d

Autoregressive Drillhole Modelling Under Distribution Shift

arXiv:2610.01204v1 Announce Type: new Abstract: Autoregressive modelling has achieved remarkable success in language and sequence tasks by learning to predict future states from previous observation.

AVSD-Scenes: A Dataset for Audio-Visual Description of Urban Scenes

arXiv:2610.01861v1 Announce Type: new Abstract: Natural language descriptions can provide rich semantic representations of audio-visual urban scenes, yet datasets that jointly describe both auditory a

Beyond Answer Confidence: A Controlled Audit of Self-Knowledge in a Black-Box Decision Model

arXiv:2610.01006v1 Announce Type: new Abstract: Decision models return probabilities intended for routing, abstention and automated action. Calibration makes those probabilities useful on average, but

Beyond State-of-the-Art: Standardising Environmental Impact Metrics for AI Research

arXiv:2610.01116v1 Announce Type: new Abstract: As the capabilities and ubiquity of Large Language Models (LLMs) grow, so does their environmental footprint. Despite calls for responsible AI, the mach

Bounded-Fidelity Sim-as-Demo-Stage: Mocap Handoff for Governance Benchmarks

arXiv:2610.00008v1 Announce Type: cross Abstract: Sim-to-real research pursues physics fidelity as a primary objective: simulators are judged by how closely they reproduce real-world contact dynamics.

BudgetSchemaBench: A Budget-Swept Diagnostic for Schema Context in Text-to-SQL

arXiv:2610.00092v1 Announce Type: cross Abstract: Data agents over structured sources must fit database schema into the model's context window. Large catalogs can span many databases and thousands of

Characterizing a Configuration Where Inference-Time PRM-Pruned Fragment Grafting Is Inert: Evidence from Three Reasoning LMs

arXiv:2610.00047v1 Announce Type: new Abstract: Diversity collapse in parallel chain-of-thought has motivated inference-time interventions built on a natural design: when a process reward model (PRM)

CompMat-Bench: Benchmarking AI Agents for Computational Materials Science

arXiv:2610.00636v1 Announce Type: new Abstract: Evaluating AI agents on scientific research tasks is constrained by the time and resources required for the underlying experiments or calculations. In c

Continuous Process-Level Evaluation for Evolving Enterprise AI Agent Skills

arXiv:2610.01833v1 Announce Type: new Abstract: Enterprise AI agent skills evolve as tool APIs, models, and specifications change, yet final-output evaluation can miss process-level behavioral drift.

ContractRL: Shielded Group-Relative Policy Optimization for Auditable Tool-Call Repair

arXiv:2610.00328v1 Announce Type: new Abstract: Structured tool calls often fail after only a small number of fields violate a schema or an execution contract. Regenerating the complete object enlarge

Cross-Lingual Alignment for Decoder-Only Models using MoE Routers

arXiv:2610.01921v1 Announce Type: cross Abstract: Cross-lingual contrastive learning has been a core component of multilingual encoder training, but the ability to explicitly align representations is

DMAD: Distribution Matching as Adversarial Distillation for Fast Visual Generation

arXiv:2610.02188v1 Announce Type: cross Abstract: Distribution Matching Distillation (DMD) trains a few-step student from the difference between separately estimated target and student scores, so it m

DuplexSpeechBench-Document Grounding: Benchmarking Document Grounding and Hallucinations in Voice Agents

arXiv:2610.00316v1 Announce Type: cross Abstract: Voice agents enable low-latency, natural interaction, yet their ability to faithfully ground responses in external documents remains underexplored. We

ECHO: A Participatory Framework for Bias-Anchored AI Harm Anticipation

arXiv:2512.03068v2 Announce Type: replace-cross Abstract: Artificial Intelligence (AI) systems increasingly shape consequential decisions, creating value but also potential harms for individuals, soci

Evaluating Physical Consistency and Plausibility in Generative Scenario Models for Autonomous Driving

arXiv:2610.01581v1 Announce Type: new Abstract: Generative AI models are increasingly used for scenario generation in autonomous driving. While they can generate realistic-looking scenarios, they ofte

External Observers May See More Clearly: Cross-Model Span-Level Hallucination Detection in Large Language Models via Hidden State Probing

arXiv:2610.02066v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly serve as foundational reasoning engines, their tendency to hallucinate remains a critical vulnerability. Wh

FocusGraph: Graph-Structured Frame Selection for Embodied Long Video Question Answering

arXiv:2603.04349v2 Announce Type: replace Abstract: Understanding long videos is crucial for embodied intelligent agents, as their performance depends on effectively accumulating and using long-horizo

researcharxiv-cs-cv

FourierQK: Filter Shape, Admissibility and the Leakage-Coverage Law

arXiv:2610.00009v1 Announce Type: new Abstract: Frequency-collapse attention [Zeris, 2026e] achieves large gains over standard dot-product attention by replacing the Q/K dot product with a bandpass-fi

researcharxiv-cs-lg

From Network Intrusion Detection to Blockchain-Backed Endpoint Detection and Response: Mapping the Landscape of Decentralized Detection-and-Response Architectures

arXiv:2610.01872v1 Announce Type: cross Abstract: While the literature on blockchain-assisted intrusion detection and prevention systems (IDS/IPS) for Internet of Things (IoT) and Industrial Internet

Heavy-Tailed Memory Traces in Long-Horizon Language Agents

arXiv:2610.00010v1 Announce Type: new Abstract: Long-horizon language agents increasingly rely on external memory as a frozen world model, yet current memory systems are usually judged only by task su

Homomorphic Advantage Operator: Stabilizing Reinforcement Learning Under Fully Homomorphic Encryption Constraints

arXiv:2610.02074v1 Announce Type: new Abstract: Privacy-preserving machine learning presents significant deployment challenges on the cloud for intelligent systems with confidential data. Fully Homomo

How AI Agents Discover Scientific Equations: From Hydrotope Rediscovery to New Water-Wave Amplitudes

arXiv:2610.00435v1 Announce Type: cross Abstract: We study how AI agents discover and validate scientific formulas using a controlled case study of the hydrotope, a recently discovered geometric formu

How Much Can Language Models Gain from Test-Time Computation?

arXiv:2610.01110v1 Announce Type: new Abstract: How much can test-time computation improve a language model, and at what cost? Test-time scaling is widely proposed as a substitute for larger models, b

In Dialogue with Intelligence: Toward Insightful Co-Augmentation

arXiv:2505.22767v4 Announce Type: replace-cross Abstract: Dialogue with a large language model can lead a person to insight: a sudden change in how they understand a problem. This perspective asks how

InterEvolve: Test-Time Evolution of Reward Programs for Humanoid Loco-Manipulation

arXiv:2610.02196v1 Announce Type: cross Abstract: We study test-time evolution for humanoid loco-manipulation: solving tasks that a controller was never trained for by repurposing its existing skills,

agentsarxiv-cs-cv

ITC-MoE: Importance-guided Token-aware Compression for MoE Diffusion Language Models

arXiv:2610.01296v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) Diffusion Language Models (DLMs) offer flexible parallel decoding and increased model capacity, but their large number of exper

Knowing When to Yield: Grounded Arbitration of User Corrections in Text-Based Embodied Agents

arXiv:2610.00282v1 Announce Type: new Abstract: How should an embodied agent respond when a person's correction may be wrong? We formulate grounded correction arbitration as a choice among accepting,

Learning to Predict Distributions over Weight Updates for Test-Time Adaptation

arXiv:2610.01934v1 Announce Type: new Abstract: Hypernetworks have recently shown success in dynamically adapting the parameters of Large Language Models (LLMs) at runtime based on signals such as tas

Legal Research Bench: Measuring End-to-End Reliability in Long-Horizon Legal Research Agents

arXiv:2610.00609v1 Announce Type: new Abstract: Legal research is a core and time-consuming legal workflow. Lawyers must identify controlling authority, verify that it remains valid, reconcile statute

LEGO-OPD: Factorized Teacher Composition for Multimodal On-Policy Distillation

arXiv:2610.00333v1 Announce Type: cross Abstract: Multimodal on-policy distillation (OPD) aims to improve visual grounding while preserving the strong reasoning capabilities of language models. Recent

Make Sparse Rewards Count: Density-Aware Reward Aggregation for Multi-Reward RL

arXiv:2610.00574v1 Announce Type: new Abstract: Multi-reward reinforcement learning trains large language models to satisfy multiple behavioral objectives simultaneously. Reward-wise normalization, as

safetyarxiv-cs-lg

MCRI: A Four-Dimensional Framework for Analyzing and Evaluating Agent Skills

arXiv:2610.01506v1 Announce Type: new Abstract: As agents evolve from single-tool systems into modular, composite architectures, skills are becoming an important mechanism for capability development a

MoRA: MoE Pruning via Router Bias Learning and Expert Approximation

arXiv:2610.00367v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models enable parameter scaling with limited per-token computation by activating only a small subset of experts for each token,

MorphoBranch: A Fine-Structure-Preserving Workbench for Morphometric Analysis of Branched Cellular Structures

model-releasesarxiv-cs-cv

arXiv:2610.00860v1 Announce Type: cross Abstract: Background and Objectives: Fluorescence-labeled cellular arbors provide readouts of neuronal and microglial morphology, but fine and weakly labeled pr

Pushing CPU Speech Synthesis to the Wall: Extreme Inference Tuning under Serverless Architecture and Billing

arXiv:2610.00063v1 Announce Type: cross Abstract: Instance-billed serverless platforms charge for CPU and memory over the lifetime of a warm instance, making idle inference state a direct serving cost

R-GroundBench: A Diagnostic Benchmark for R-Group Groundingin Markush Molecular Editing

arXiv:2610.00700v1 Announce Type: new Abstract: Recent advances in AI for scientific discovery enable molecular understandingand design, yet reasoning over incomplete chemical representations remainsu

Reconstruct, Practice, Go Real: Guided Self-Improvement for Embodied Agents

arXiv:2610.02204v1 Announce Type: cross Abstract: Building reliable robot capabilities across diverse tasks requires substantial human effort to develop and maintain skills, design rewards, and integr

Rethinking Probability-Based Reinforcement Learning From Posterior Concentration

arXiv:2610.01458v1 Announce Type: new Abstract: Verifier-free reinforcement learning with probability-based rewards offers a promising way to train LLMs on general reasoning tasks where external verif

Self-Evolving Coding Rules for AI Coding Agents

arXiv:2610.00650v1 Announce Type: cross Abstract: The performance of AI coding agents is highly dependent on their underlying coding rules. However, existing coding rules are typically hand-crafted an

Sentence Specificity Scores for Collaborative Technical Documentation: A Domain-Transfer Study

arXiv:2610.01046v1 Announce Type: cross Abstract: Collaboration depends on shared context, and technical documentation is one way that context persists across people and AI teammates. Specificity, the

SoK: Decentralized Agent Economic Infrastructure

arXiv:2610.01756v1 Announce Type: cross Abstract: Decentralized agent economies increasingly build a single task from protocols that were designed and secured separately. This creates a simple problem

Temporally-Resolved Token Attribution Reveals the Generation Dynamics of Diffusion Language Models

arXiv:2610.01177v1 Announce Type: cross Abstract: This work presents Diffusion Layer Integrated Gradients (DLIG), a token attribution method for diffusion language models (DLMs) that extends Integrate

TRACE: Trajectory Return Attribution and Contrastive Erasure for Multi-Turn Safety

arXiv:2610.01323v1 Announce Type: new Abstract: Safety-aligned large language models (LLMs) often refuse a harmful request but comply once the same goal is spread over several turns. Preference object