Search: “evaluation”

Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models

arXiv:2605.07514v1 Announce Type: cross Abstract: World Action Models (WAMs) enable decision-making through imagined rollouts by predicting future observations and actions. However, the reliability of

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Model Releases

Is Your Prompt Poisoning Code? Defect Induction Rates and Security Mitigation Strategies

DGX agent

arXiv:2510.22944v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have become indispensable for automated code generation, yet the quality and security of their outputs remain a c

model-releasesarxiv-cs-ai

11 May 2026

Knowing but Not Correcting: Routine Task Requests Suppress Factual Correction in LLMs

model-releasesarxiv-cs-lg

arXiv:2605.05957v2 Announce Type: replace Abstract: LLMs reliably correct false claims when presented in isolation, yet when the same claims are embedded in task-oriented requests, they often comply r

Applications

Large Video Planner Enables Generalizable Robot Control

arXiv:2512.15840v2 Announce Type: replace-cross Abstract: General-purpose robots require decision-making models that generalize across diverse tasks and environments. Recent works build robot foundati

applicationsarxiv-cs-cv

Latent Reasoning VLA: Latent Thinking and Prediction for Vision-Language-Action Models

arXiv:2602.01166v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models benefit from chain-of-thought (CoT) reasoning, but existing approaches incur high inference overhead and rely on

researcharxiv-cs-ro

Learning Agent Routing From Early Experience

model-releasesarxiv-cs-cl

arXiv:2605.07180v1 Announce Type: new Abstract: LLM agents achieve strong performance on complex reasoning tasks but incur high latency and compute cost. In practice, many queries fall within the capa

Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents

arXiv:2605.06957v1 Announce Type: new Abstract: We present a dynamic policy-learning approach that combines generalized planning and hierarchical task decomposition for LLM-based agents. Our method, H

Agents

Learning CLI Agents with Structured Action Credit under Selective Observation

arXiv:2605.08013v1 Announce Type: new Abstract: Command line interface (CLI) agents are emerging as a practical paradigm for agent-computer interaction over evolving filesystems, executable command li

agentsarxiv-cs-ai

Learning to Track Instance from Single Nature Language Description

arXiv:2605.07064v1 Announce Type: new Abstract: How to achieve vision-language (VL) tracking using natural language descriptions from a video sequence extbf{without relying on any bounding-box ground

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Less Random, More Private: What is the Optimal Subsampling Scheme for DP-SGD?

arXiv:2605.07072v1 Announce Type: new Abstract: Poisson subsampling is the default sampling scheme in differentially private machine learning, largely because its unstructured randomness yields tracta

Tutorials

LKV: End-to-End Learning of Head-wise Budgets and Token Selection for LLM KV Cache Eviction

arXiv:2605.06676v1 Announce Type: cross Abstract: Long-context inference in Large Language Models (LLMs) is bottlenecked by the linear growth of Key-Value (KV) cache memory. Existing KV cache compress

tutorialsarxiv-cs-cl

LLMs are not (consistently) Bayesian: Quantifying internal (in)consistencies of LLMs' probabilistic beliefs

arXiv:2605.06915v1 Announce Type: new Abstract: Modern AI systems are being deployed in complex domains such as medicine, science, and law, where it is important that they not only produce correct ans

Agents

LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling

arXiv:2605.08083v1 Announce Type: new Abstract: Test-time scaling (TTS) has become an effective approach for improving large language model performance by allocating additional computation during infe

agentsarxiv-cs-cl

MAGIQ: A Post-Quantum Multi-Agentic AI Governance System with Provable Security

arXiv:2605.06933v1 Announce Type: new Abstract: Our computing ecosystem is being transformed by two emerging paradigms: the increased deployment of agentic AI systems and advancements in quantum compu

MaPPO: Maximum a Posteriori Preference Optimization with Prior Knowledge

arXiv:2507.21183v5 Announce Type: replace-cross Abstract: As the era of large language models (LLMs) unfolds, Preference Optimization (PO) methods have become a central approach to aligning LLMs with

MAVEN: Multi-Agent Verification-Elaboration Network with In-Step Epistemic Auditing

arXiv:2605.07646v1 Announce Type: cross Abstract: While explicit reasoning trajectories enhance model interpretability, existing paradigms often rely on monolithic chains that lack intermediate verifi

McNdroid: A Longitudinal Multimodal Benchmark for Robust Drift Detection in Android Malware

model-releasesarxiv-cs-lg

arXiv:2605.06894v1 Announce Type: cross Abstract: Machine learning (ML) in real-world systems must contend with concept drift, adversarial actors, and a spectrum of potential features with varying cos

MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text

arXiv:2605.06903v1 Announce Type: cross Abstract: Large language models are now embedded in everyday writing workflows, making reliable AI-generated text detection important for academic integrity, co

MicroBi-ConvLSTM: An Ultra-Lightweight Efficient Model for Human Activity Recognition on Resource Constrained Devices

model-releasesarxiv-cs-cv

arXiv:2602.06523v2 Announce Type: replace Abstract: Human Activity Recognition (HAR) on resource constrained wearables requires models that balance accuracy against strict memory and computational bud

Mind the Gap: Geometrically Accurate Generative Reconstruction from Disjoint Views

arXiv:2605.07550v1 Announce Type: new Abstract: 3D vision systems are fundamentally constrained by their reliance on visual overlap: reconstruction methods require it for geometric alignment, while ge

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Miner:Mining Intrinsic Mastery for Data-Efficient RL in Large Reasoning Models

arXiv:2601.04731v2 Announce Type: replace Abstract: Current critic-free RL methods for large reasoning models suffer from severe inefficiency when training on positive homogeneous prompts (where all r

Mixture of Masters: Sparse Chess Language Models with Player Routing

arXiv:2602.04447v2 Announce Type: replace-cross Abstract: Modern chess language models are dense transformers trained on millions of games played by thousands of high-rated individuals. However, these

researcharxiv-cs-ai

More Thinking, More Bias: Length-Driven Position Bias in Reasoning Models

arXiv:2605.06672v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning and reasoning-tuned models such as DeepSeek-R1 are commonly assumed to reduce shallow heuristic biases by thinking care

Multi-environment Invariance Learning with Missing Data

arXiv:2601.07247v2 Announce Type: replace-cross Abstract: Learning models that can handle distribution shifts is a key challenge in domain generalization. Invariance learning, an approach that focuses

Multi-Environment POMDPs with Finite-Horizon Objectives

arXiv:2605.07537v1 Announce Type: new Abstract: Partially Observable Markov Decision Processes (POMDPs) are systems in which one agent interacts with a stochastic environment, and receives only partia

Multi-Modal Multi-Agent Reinforcement Learning for Radiology Report Generation

arXiv:2603.16876v2 Announce Type: replace-cross Abstract: We propose MARL-Rad, a multi-modal multi-agent reinforcement learning framework for radiology report generation that trains the entire agentic

Multi-Objective Constraint Inference using Inverse reinforcement learning

arXiv:2605.06951v1 Announce Type: new Abstract: Constraint inference is widely considered essential to align reinforcement learning agents with safety boundaries and operational guidelines by observin

Multimodal Latent Reasoning via Hierarchical Visual Cues Injection

arXiv:2602.05359v2 Announce Type: replace Abstract: The advancement of multimodal large language models (MLLMs) has enabled impressive perception capabilities. However, their reasoning process often r

Multimodal Stepwise Clinically-Guided Attention Learning for Pathological Complete Response Prediction in Breast Cancer

arXiv:2605.07561v1 Announce Type: new Abstract: Pathological complete response (pCR) is a key prognostic factor in breast cancer patients undergoing neoadjuvant therapy, strongly associated with long-

Multispectral Indices for Wildfire Management

arXiv:2309.01751v3 Announce Type: replace-cross Abstract: The increasing frequency and severity of wildfires necessitates advanced methods for effective surveillance and management, as traditional gro

Narrow Secret Loyalty Dodges Black-Box Audits

arXiv:2605.06846v1 Announce Type: cross Abstract: Recent work identifies secret loyalties as a distinct threat from standard backdoors. A secret loyalty causes a model to covertly advance the interest

NCL-UoR at SemEval-2026 Task 5: Embedding-Based Methods, Fine-Tuning, and LLMs for Word Sense Plausibility Rating

model-releasesarxiv-cs-cl

arXiv:2603.08256v2 Announce Type: replace Abstract: Word sense plausibility rating requires predicting the human-perceived plausibility of a given word sense on a 1-5 scale in the context of short nar

Neurosymbolic Imitation Learning with Human Guidance: A Privileged Information Approach

arXiv:2605.07166v1 Announce Type: new Abstract: Imitation learning is widely used for learning to act in complex environments. While pure neural-based methods handle high dimensional data effectively,

No Forgetting Learning: Buffer-free Continual Learning Classification

arXiv:2503.04638v3 Announce Type: replace Abstract: Most Continual Learning (CL) methods maintain performance on earlier tasks by storing exemplars in a replay buffer, introducing memory overhead that

NPMixer: Hierarchical Neighboring Patch Mixing for Time Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2605.07476v1 Announce Type: new Abstract: Multivariate time series forecasting remains a challenge due to the complexity of local temporal dynamics and global dependencies across multiple variab

OmicsLM: A Multimodal Large Language Model for Multi-Sample Omics Reasoning

arXiv:2605.06728v1 Announce Type: cross Abstract: Interpreting transcriptomic data is one of the most common analytical tasks in modern biology. Yet most current models either consume expression profi

Local Ai

On the Tradeoffs of On-Device Generative Models in Federated Predictive Maintenance Systems

arXiv:2605.07860v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a promising paradigm for preserving client data ownership and control over distributed Internet of Things (IoT)

local-aiarxiv-cs-ai

OphEdit: Training-Free Text-Guided Editing of Ophthalmic Surgical Videos

arXiv:2605.07695v1 Announce Type: new Abstract: High-fidelity surgical video generation can greatly improve medical training and the development of AI, adapting these generative models for precise vid

Optimizing Language Models for Crosslingual Knowledge Consistency

arXiv:2603.04678v2 Announce Type: replace-cross Abstract: Large language models are known to often exhibit inconsistent knowledge. This is particularly problematic in multilingual scenarios, where mod

PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents

arXiv:2605.07039v1 Announce Type: new Abstract: Large language models have become drivers of evolutionary search, but most systems rely on a fixed, prompt-elicited policy to sample next candidates. Th

PAIR-Former: Budgeted Relational Multi-Instance Learning for Functional miRNA Target Prediction

arXiv:2602.00465v3 Announce Type: replace-cross Abstract: Functional miRNA--mRNA targeting is a large-bag prediction problem where each transcript yields a heavy-tailed pool of candidate target sites

Tutorials

PAMPOS: Causal Transformer-based Trajectory Prediction for Attack-Agnostic Misbehavior Detection in V2X Networks

arXiv:2605.06833v1 Announce Type: cross Abstract: Misbehavior detection in Vehicle-to-Everything (V2X) networks is a second line of defense against insider falsification attacks that cryptographic mec

tutorialsarxiv-cs-ai

PathPainter: Transferring the Generalization Ability of Image Generation Models to Embodied Navigation

model-releasesarxiv-cs-ro

arXiv:2605.07496v1 Announce Type: new Abstract: Bird's-eye-view (BEV) images have been widely demonstrated to provide valuable prior information for navigation. Given the global information provided b

Physics-Based Benchmarking Metrics for Multimodal Synthetic Images

arXiv:2511.15204v3 Announce Type: replace-cross Abstract: Current state of the art measures like BLEU, CIDEr, VQA score, SigLIP-2 and CLIPScore are often unable to capture semantic or structural accur

Physics-based Digital Twins for Integrated Thermal Energy Systems Using Active Learning

arXiv:2605.06756v1 Announce Type: new Abstract: Real-time supervisory control of thermal energy distribution systems requires digital twins that are accurate, interpretable, and uncertainty-aware, yet

Hardware

Physics-Based Flow Matching for Full-Field Prediction of Silicon Photonic Devices

arXiv:2605.06929v1 Announce Type: cross Abstract: Designing photonic integrated circuits requires accurate electromagnetic field simulations, which remain computationally expensive even for simple dev

hardwarearxiv-cs-lg

PolarVLM: Bridging the Semantic-Physical Gap in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.07574v1 Announce Type: new Abstract: Mainstream vision-language models (VLMs) fundamentally struggle with severe optical ambiguities, such as reflections and transparent objects, due to the

Local Ai

Predictive but Not Plannable: RC-aux for Latent World Models

arXiv:2605.07278v1 Announce Type: cross Abstract: A latent world model may achieve accurate short-horizon prediction while still inducing a latent space that is poorly aligned with planning. A key iss

local-aiarxiv-cs-ai