Search: “benchmark”

A GHOST in Long-Horizon Agents: Governance Hazard from Overlooked Safety Constraints across Turns

arXiv:2610.02664v1 Announce Type: new Abstract: Long-horizon agents are now playing an increasingly significant role in assisting humans with complex problem-solving. However, it is exactly their exte

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Model Releases

Automatic Evaluation of Mental Health Stigma in Online Communication

DGX agent

arXiv:2610.02775v1 Announce Type: new Abstract: Mental health stigma has profoundly harmful impacts but its complexity makes it difficult to evaluate. Stigma may involve explicit derogation, but also

model-releasesarxiv-cs-cl

5 Oct 2026

Safety

Collective Bias Mitigation via Model Routing and Collaboration

arXiv:2610.03240v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in public health, finance, and governance, requiring both accuracy and societal value alignment.

safetyarxiv-cs-cl

CONTRA: Discovering and Qualifying Behavior-Changing Questions for Selective Clarification in LLM Code Generation

arXiv:2610.01769v1 Announce Type: cross Abstract: Coding agents can generate code that appears correct but implements behavior the user never intended. This mismatch can arise when an agent silently r

Decoupling Memory from Context: Structured Memory for Token-Efficient Test-Time Continual Learning

arXiv:2610.02687v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in enterprise, scientific, and medical applications, where agents must incorporate domain-specifi

DeReAct: Decomposed Reasoning and Acting for Reliable AI Agents

arXiv:2610.02351v1 Announce Type: new Abstract: ReAct-based agents typically rely on a single LLM policy to propose actions, interact with the environment, and decide when a task is complete. This cou

Flow Map Denoisers: Traversing the Distortion-Perception Plane for Inverse Problems

arXiv:2606.19802v2 Announce Type: replace-cross Abstract: Image restoration faces a fundamental tradeoff: methods that minimize error produce blurry reconstructions, while those that maximize perceptu

Improving the Energy-Efficiency of the Code Generated by LLMs through Effective Prompting

arXiv:2610.02571v1 Announce Type: cross Abstract: As AI-assisted programming becomes increasingly mainstream, the environmental impact of AI-generated software has emerged as an important consideratio

Investigating the Role of Reasoning-Language Alignment in Monolingual Retrieval-Augmented Generation

model-releasesarxiv-cs-cl

arXiv:2610.03136v1 Announce Type: new Abstract: Reasoning traces improve large language models (LLMs), but current models are trained to reason mostly in English. It has been shown that forcing a mode

Applications

Learning Query Encoders Can Be Hard Even When Vector Retrieval Is Geometrically Easy

arXiv:2610.02749v1 Announce Type: cross Abstract: Efficient vector retrieval requires both a corpus geometry that supports retrieving the right documents through vector similarity, and a query encoder

applicationsarxiv-cs-lg

MOF-VERIFY: A Failure-Aware Agentic Harness for MOF Hypothesis Verification

arXiv:2610.03056v1 Announce Type: new Abstract: Large language models are increasingly used as reasoning components in AI-driven materials Co-Scientists, yet the reliability of the resulting verificat

NeutronGym: Physics-Graded Neutron Instrument Design for LLM Agents

arXiv:2610.03631v1 Announce Type: new Abstract: Designing a scientific instrument tests whether language-model agents can do physics rather than recall it, provided the grading cannot be argued with.

OmniConfess: Eliciting Token Confessions to Mitigate Omni-Modal Hallucination

model-releasesarxiv-cs-cl

arXiv:2610.02999v1 Announce Type: new Abstract: Omni-modal large language models (OmniLLMs) unify text, images, audio, and video, yet hallucinate when generation relies on the wrong evidence. Existing

On the Chain-of-Thought Monitorability of Looped Language Models

arXiv:2610.02741v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring provides a promising approach for detecting undesirable model behavior. Looped language models (LoopLMs) repeatedly ap

On Unlearning for Time-series Forecasting

arXiv:2610.02865v1 Announce Type: new Abstract: Time-series forecasting is widely used in sensitive domains. Models in these settings are often trained on longitudinal user- or entity-level records, w

Tutorials

PAPER2LLM++: Continual Self-Evolution of LLMs from Research Papers

arXiv:2610.02793v1 Announce Type: new Abstract: Research on LLMs continually uncovers model limitations, their causes, and potential solutions. Yet these human discoveries remain largely disconnected

tutorialsarxiv-cs-ai

Research

RASPER: Reward-Aligned Summarization of Clinical Notes for EHR Outcome Prediction

arXiv:2610.02979v1 Announce Type: new Abstract: Unstructured discharge notes in Electronic Health Records (EHRs) often carry signal complementary to structured medical codes, holding patient-specific

researcharxiv-cs-ai

Reasoning Models Are Accurate but Unsound on Identification

arXiv:2610.03519v1 Announce Type: new Abstract: A reasoning model asked whether a causal effect is recoverable from observational data can fail in two ways: it refuses an identifiable query or answers

Rethinking RAG in Long Videos: What to Retrieve and How to Use It?

arXiv:2606.13141v2 Announce Type: replace Abstract: Retrieval-augmented generation is extending beyond text to long videos, where query-relevant chunks can be represented across multiple modalities an

Science Is Falling Behind the Frontier: Foundation Model Adoption Across Half a Million Papers

arXiv:2511.21739v2 Announce Type: replace-cross Abstract: We present the first large-scale analysis of AI foundation model usage in science -- not just citations or keywords. We find that adoption has

SD-DPC: Sparse Dictionary Differentiable Predictive Control

arXiv:2610.02466v1 Announce Type: cross Abstract: We present sparse dictionary differentiable predictive control (SD-DPC), a framework for learning sparse, interpretable feedback policies for nonlinea

Applications

Social bot detection in the age of ChatGPT: Challenges and opportunities

arXiv:2610.02386v1 Announce Type: cross Abstract: We present a comprehensive overview of the challenges and opportunities in social bot detection in the context of the rise of sophisticated AI-based c

applicationsarxiv-cs-cl

Understanding Trajectory Heterogeneity in Federated World Model Learning

model-releasesarxiv-cs-cl

arXiv:2610.02957v1 Announce Type: cross Abstract: World models learn state evolution from trajectories, making access to temporal context a central training requirement. Federated learning can use dis

WebFovea: When the Model Is Right but the Click Is Wrong -- Reliable Round Trips for Vision-Based Web Agents on Live Websites

arXiv:2610.03036v1 Announce Type: cross Abstract: We present WebFovea, a vision-based web agent that placed 2nd in the WebRetriever Challenge 2026 with a final score of 57.0 out of 100. The challenge

Tutorials

When History Fails to Become Experience: Action Calibration in Language Agents

arXiv:2610.02769v1 Announce Type: cross Abstract: Language agents should draw on prior attempts and environmental feedback to improve subsequent decisions within the same task. However, providing addi

tutorialsarxiv-cs-ai

Research

AI-assisted mitotic counting improves reproducibility and efficiency across multiple tumour types

arXiv:2610.01813v1 Announce Type: new Abstract: Mitotic counting is an important component of tumour grading, diagnosis and prognostic assessment across several tumour types, but manual assessment is

researcharxiv-cs-ai

Align Then Reason: A Multimodal Lip-Sync Judge for Dubbing

arXiv:2610.00825v1 Announce Type: new Abstract: Dubbing quality control requires a reference-free judge that can determine whether a candidate text line matches a speaker's visible articulation in bot

AnchorPrompt: Self-Distilled Soft Prompts for Robust Audio-Language Models

arXiv:2610.00706v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are sensitive to input perturbations, such as noise, waveform corruption, and adversarial injections. We propose A

Architecture Without an Architect? Global Governance of Artificial Intelligence in a Divided World

arXiv:2610.01716v1 Announce Type: cross Abstract: Artificial intelligence presents an unusually difficult problem for global governance. The technology develops rapidly, crosses borders easily, and is

Agents

Argo-Bench: Evaluating Data Agents on Enterprise-Scale Workflows

arXiv:2610.02122v1 Announce Type: cross Abstract: Real-world enterprise data science and analytics workflows require reasoning across dozens of tables, performing statistical analyses, and acting on t

agentsarxiv-cs-ai

Auto-Formalizing Neuro-Symbolic Predictors

arXiv:2610.01519v1 Announce Type: cross Abstract: Neuro-Symbolic (NeSy) predictors incorporate prior knowledge into the prediction process of neural networks, ensuring that outputs satisfy specified c

Safety

Beyond Final Accuracy: Auditing Communication in LLM Multi-Agent Systems

arXiv:2610.01042v1 Announce Type: new Abstract: Multi-agent communication aims to help agents benefit from one another's information. Yet improvements in system performance leave a fundamental ambigui

safetyarxiv-cs-ai

Beyond Leaderboard Scores: A Deployment-Focused Protocol for Interpretable Tracking Evaluation in Pedestrian-Centric Environments

arXiv:2610.01682v1 Announce Type: cross Abstract: Mobile robots operating among pedestrians need trajectories that become available quickly, remain spatially credible through missed observations, pres

Beyond Memory: Harnessing Long-Horizon Agents with Explicit Belief States

arXiv:2610.01415v1 Announce Type: new Abstract: Large language model (LLM) agents can now undertake increasingly complex tasks, but the way they organize interaction history into memory does not ensur

Block Optimism for Nonstationary Bandits with Latent Linear Dynamics

arXiv:2610.00911v1 Announce Type: cross Abstract: We study an endogenous nonstationary stochastic bandit problem with latent linear dynamics, where actions affect both immediate rewards and the future

Chaining Skills to Hijack LLM Agents

arXiv:2610.01564v1 Announce Type: cross Abstract: LLM agents use skills to improve performance on specialized tasks. To complete a user request, an agent may invoke several skills in sequence, allowin

ChainLoRA: Geometry-Preserving Task Vector Merging for Continual Learning in LLMs

arXiv:2610.00431v1 Announce Type: cross Abstract: Continual parameter-efficient fine-tuning for large language models (LLMs) must balance retention of previously acquired knowledge, adaptation to new

CHORDONOMICON: A Dataset of 666,000 Songs and their Chord Progressions

arXiv:2410.22046v4 Announce Type: replace-cross Abstract: Chord progressions encapsulate important information about music, pertaining to its structure and conveyed emotions. They serve as the backbon

CLASP: Continual Low-rank Adapters for Spatially Placed Concepts from One Hypernetwork

arXiv:2610.01331v1 Announce Type: new Abstract: Continual personalization of text-to-image diffusion models requires sequentially acquiring new concepts while retaining previously learned ones. Howeve

Research

Classification Based on Association Rules Algorithm for Breast Cancer

arXiv:2610.00174v1 Announce Type: new Abstract: Breast cancer is a significant contributor to female mortality across the world, displaying one of the highest oc currence rates among the various cance

researcharxiv-cs-lg

Closing the Loop: Practical Training Recipes for Looped Language Models

arXiv:2610.00673v1 Announce Type: cross Abstract: Looped language models increase effective depth by repeatedly applying a shared block of layers, but existing large-scale recipes require multi-stage

Decision Titan: Test-Time Training for Long-Term Memory in Offline Reinforcement Learning

arXiv:2610.01513v1 Announce Type: new Abstract: Long-term dependencies remain a major challenge for sequential decision-making in the field of AI: RNNs suffer from vanishing gradients and the limited

DiDE:Direct Injection with Color-Texture DEcoupling for 3D Stylization

arXiv:2610.02044v1 Announce Type: new Abstract: Recent advances in rectified flow-based image-to-3D generative models have enabled high-fidelity 3D asset generation. Building on this, a growing line o

Discrete Annotation, Continuous Preference: Rethinking Supervision for Accurate and Generalizable Aesthetic Image Cropping

arXiv:2610.00582v1 Announce Type: new Abstract: Aesthetic image cropping aims to identify the optimal crop of an image in terms of aesthetics and composition. While supervision based on annotated data

Do Better Scores Mean Better Physics? Physics-Grounded Explanations for Sim2Real Neural Operators

arXiv:2610.00415v1 Announce Type: new Abstract: Machine-learning surrogates accelerate physical simulation, but lower prediction error need not coincide with lower error in physically relevant flow st

DuoMind: Enabling Distributed Multi-Robot Coordination with Semantic Communication

arXiv:2610.02161v1 Announce Type: cross Abstract: Vision-language models (VLMs) and vision-language-action models (VLAs) have recently driven rapid progress in general-purpose robots, yet most progres

Evidence-Gated Research: Statistically Controlled Model Adoption in Adaptive Search

arXiv:2610.01751v1 Announce Type: new Abstract: Adaptive model search is path dependent: once a challenger is adopted, it becomes the reference from which later candidates are generated. A statistical

Faynt: Scaling and Optimizing Policies for Competitive Melee

arXiv:2610.02144v1 Announce Type: new Abstract: We introduce Faynt, a family of 10M- and 75M-parameter Transformer policies for Super Smash Bros. Melee, each controlling all 26 characters with a singl