Search: “framework”

Well-Posed KL-Regularized Control via Wasserstein and Kalman-Wasserstein KL Divergences

arXiv:2602.02250v2 Announce Type: replace-cross Abstract: Kullback-Leibler (KL) divergence regularization is widely used in reinforcement learning, but it becomes infinite under support mismatch and c

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When and How Much to Imagine: Adaptive Test-Time Scaling with World Models for Visual Spatial Reasoning

DGX agent

arXiv:2602.08236v2 Announce Type: replace-cross Abstract: Despite rapid progress in MLLMs, visual spatial reasoning remains unreliable when correct answers depend on how a scene would appear under uns

model-releasesarxiv-cs-ai

2 Jun 2026

When Meaning Travels: A Granular Lens on Hybrid-MoE's Role in Idiomatic Understanding for Language Models

arXiv:2606.01671v1 Announce Type: new Abstract: In the contemporary epoch of multilingual education, learning idioms provides a fascinating gateway towards creativity, cultural values, historical cont

safetyarxiv-cs-cl

When Safe Skills Collide: Measuring Compositional Risk in Agent Skill Ecosystems

arXiv:2606.00448v1 Announce Type: cross Abstract: LLM agents increasingly rely on community-contributed skills that expand an agent's operational capability set. We study a core safety problem in agen

When Single Answer Is Not Enough: Rethinking Single-Step Retrosynthesis Benchmarks for LLMs

arXiv:2602.03554v2 Announce Type: replace-cross Abstract: Recent progress has expanded the use of large language models (LLMs) in drug discovery, including synthesis planning. However, objective evalu

Where to Look: Can Foundation Models Reach a Target Viewpoint Through Active Exploration?

model-releasesarxiv-cs-cv

arXiv:2606.01247v1 Announce Type: new Abstract: Humans can reproduce the viewpoint specified by a target image through active head and body motion, yet spatial intelligence in foundation models has la

Where to Refine, When to Stop: Rethinking Redundancy via Latent Discrepancy for Efficient Visual Autoregressive Generation

arXiv:2606.00310v1 Announce Type: new Abstract: Visual Autoregressive (VAR) models deliver high-quality image generation but suffer from significant inference latency at high resolutions. Recent accel

Who Annotates in NLP? A Large-scale Assessment of Human Annotation Reporting between 2018 and 2025

arXiv:2606.02255v1 Announce Type: cross Abstract: Human annotation is the empirical foundation of much NLP research, from dataset construction to model evaluation, but papers often leave unclear who p

researcharxiv-cs-ai

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications

arXiv:2606.00133v1 Announce Type: new Abstract: World models, internal simulators that learn the structure and dynamics of an environment, have emerged as a central paradigm in the pursuit of artifici

safetyarxiv-cs-lg

World-Task Factorization for Robot Learning

arXiv:2606.02027v1 Announce Type: cross Abstract: Robot learning must produce policies that generalize to new combinations of constraints, teammates, and environments. To achieve this, we must structu

safetyarxiv-cs-lg

WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching

model-releasesarxiv-cs-cv

arXiv:2603.06331v2 Announce Type: replace Abstract: Diffusion-based world models have shown strong potential for unified world simulation, but the iterative denoising remains too costly for interactiv

Worlds Within Words: Translating Culture in Ancient Chinese Texts with Multi-Agent Coordination

arXiv:2606.01276v1 Announce Type: new Abstract: Large language model (LLM)-based machine translation has advanced cross-cultural communication, yet it still struggles with culture-loaded words (CLWs)

XAI-SOH-FL: Enhancing SOH-FL with Adaptive Aggregation and Explainable AI for Intrusion Detection in Heterogeneous IoT

arXiv:2606.00134v1 Announce Type: cross Abstract: Intrusion Detection Systems (IDS) in Internet of Things (IoT) environments face significant challenges due to data heterogeneity, lack of labeled data

Zero-Shot Multi-Animal Tracking in the Wild

arXiv:2511.02591v2 Announce Type: replace Abstract: Multi-animal tracking is crucial for understanding animal ecology and behavior, yet remains challenging due to variations in habitat, motion pattern

Zero-Shot Off-Policy Learning

arXiv:2602.01962v2 Announce Type: replace-cross Abstract: Off-policy learning methods seek to derive an optimal policy directly from a fixed dataset of prior interactions. This objective presents sign

Agents

A Behavioural and Representational Evaluation of Goal-Directedness in Language Model Agents

arXiv:2602.08964v2 Announce Type: replace-cross Abstract: Understanding an agent's goals helps explain and predict its behaviour, yet there is no established methodology for reliably attributing goals

agentsarxiv-cs-ai

A Lecture Note on Offline RL and IRL, Part II: Foundations of Inverse Reinforcement Learning and Dynamic Discrete Choice Models

arXiv:2605.30843v1 Announce Type: new Abstract: In the forward reinforcement-learning problem, the reward is fixed and known; the learner is asked to find a good policy or value function. Here we turn

safetyarxiv-cs-lg

A Perturbation Approach to Unconstrained Linear Bandits

arXiv:2603.28201v2 Announce Type: replace Abstract: We revisit the standard perturbation-based approach of Abernethy et al. (2008) in the context of unconstrained Bandit Linear Optimization (uBLO). We

A Visually Impaired Assistance Benchmark for VLM-as-a-Judge Evaluation

arXiv:2605.31351v1 Announce Type: new Abstract: AI-based Visually Impaired Assistance (VIA) remains challenging, largely due to the high cost of human evaluation. The VLM-as-a-Judge paradigm may offer

AbstainGNN: Teaching Graph Neural Networks to Abstain for Graph Classification

model-releasesarxiv-cs-lg

arXiv:2605.30786v1 Announce Type: new Abstract: Graph classification is a core task in graph data mining with widespread real-world applications. Recent advances in graph neural networks (GNNs) have l

Active Timepoint Selection for Learning Measure-Valued Trajectories

arXiv:2605.30625v1 Announce Type: cross Abstract: Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data

safetyarxiv-cs-ai

Adaptive NAD: Online and Self-adaptive Unsupervised Network Anomaly Detector

model-releasesarxiv-cs-lg

arXiv:2410.22967v5 Announce Type: replace Abstract: The widespread usage of the Internet of Things (IoT) has raised the risks of cyber threats; thus, developing Anomaly Detection Systems (ADSs) that c

AdaptR1: Reinforcement Learning Based Adaptive Interleaved Thinking in Multi-hop Question Answering

arXiv:2605.31062v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable performance in complex reasoning tasks through Chain-of-Thought (CoT) prompting. However, this app

researcharxiv-cs-cl

Applications

AdvScene: Rethinking Adversarial Patch Evaluation Through Scene Robustness

arXiv:2605.30578v1 Announce Type: cross Abstract: Adversarial patches are physical patterns attached to real objects to mislead AI vision systems. Their real-world risk is not determined by a single s

applicationsarxiv-cs-cv

AI for Monitoring and Classifying Data Used in Research Literature

arXiv:2605.30582v1 Announce Type: new Abstract: While platforms like Google Scholar and Semantic Scholar track citations for academic papers, no comparable infrastructure exists for monitoring dataset

researcharxiv-cs-cl

Anchoring LLM Gender Bias to Human Baselines: A Cross-Lingual Audit

arXiv:2605.30804v1 Announce Type: new Abstract: We audit six large language models (LLMs) for gender stereotyping across English, Korean, Chinese, and Japanese. Three were developed primarily for Engl

Agents

Answer-Set-Programming-based Abstractions for Reinforcement Learning

arXiv:2605.31444v1 Announce Type: new Abstract: Reinforcement Learning (RL) enables autonomous agents to learn policies from experience, but realistic problems often involve enormous state spaces, mak

agentsarxiv-cs-ai

Tutorials

Appropriateness of Empathy in AI: A Signal-Cost Perspective

arXiv:2605.31340v1 Announce Type: cross Abstract: The appropriateness of empathy in AI has emerged as a critical concern, as excessive empathy risks seeming manipulative while insufficient empathy app

tutorialsarxiv-cs-ai

AR Forcing: Towards Long-Horizon Robot Navigation World Model

arXiv:2605.31314v1 Announce Type: new Abstract: The diffusion based robot navigation world models are typically trained using parallel supervision, while autoregressive inference is employed during pa

researcharxiv-cs-ro

Assign and Add: A Mechanistic Study of Compositional Arithmetic

arXiv:2605.31497v1 Announce Type: new Abstract: Large language models are able to compose skills in order to perform complex tasks, many of which might not have been seen during training. The details

Asymptotically Optimal Sequential Testing with Markovian Data

arXiv:2602.17587v2 Announce Type: replace-cross Abstract: We study one-sided and alpha-correct sequential hypothesis testing for data generated by an ergodic, finite-state Markov chain. The null hypot

Local Ai

Augmented Lagrangian Predictive Coding

arXiv:2605.31022v1 Announce Type: new Abstract: Predictive coding (PC) is a local-learning alternative to backpropagation (BP), training deep networks via local energy-minimization dynamics rather tha

local-aiarxiv-cs-lg

Authentication of Copy Detection Patterns via Cross-Camera Dual-Synthetic Referencing

arXiv:2605.31292v1 Announce Type: new Abstract: Copy Detection Patterns (CDPs) are structures printed on physical objects to enable cost-effective authentication. Verification is achieved by comparing

BackSplit: The Importance of Sub-dividing the Background in Biomedical Lesion Segmentation

arXiv:2511.19394v2 Announce Type: replace Abstract: Segmenting small lesions in medical images remains notoriously difficult. Most prior work tackles this challenge by either designing better architec

Bayesian Inference with Shaped Deep Non-linear MLPs

arXiv:2605.30860v1 Announce Type: cross Abstract: A central aim of deep learning theory is to characterize how neural networks make predictions in the regime of simultaneously large model and training

Agents

Before Parc Ferme: RL-Time Pruning for Efficient Embodied LLMs in Autonomous Driving

arXiv:2605.31256v1 Announce Type: new Abstract: Embodied Large Language Models (LLMs) are increasingly used as reasoning modules in robotic control pipelines to improve human-robot interaction, but th

agentsarxiv-cs-ro

Benchmarking Machine Learning Uncertainty Quantification Methodologies for Predicting Turbine Gas Temperature Degradation

arXiv:2605.30585v1 Announce Type: cross Abstract: Effective prognostics and health management of modern engines relies on accurate turbine gas temperature predictions and robust uncertainty quantifica

safetyarxiv-cs-ai

Local Ai

Best-Arm Identification-Based Trust Region Selection for Bayesian Optimization on Multimodal Functions

arXiv:2605.31050v1 Announce Type: new Abstract: Gaussian process-based Bayesian optimization (BO) is a popular approach for expensive black-box optimization, but its performance often degrades on comp

local-aiarxiv-cs-lg

Beyond Classification: Dynamic Adapter Routing for Continual Multimodal Retrieval

arXiv:2605.31229v1 Announce Type: cross Abstract: While retrieval is a core function of vision-language models, continually updating these models for retrieval tasks remains critically underexplored.

researcharxiv-cs-ai

Applications

Beyond Memorization: Assessing Semantic Generalization in Large Language Models Using Phrasal Constructions

arXiv:2501.04661v3 Announce Type: replace-cross Abstract: The web-scale of pretraining data has created an important evaluation challenge: to disentangle linguistic competence on cases well-represente

applicationsarxiv-cs-ai

Beyond Static Dialogues: Benchmarking Realistic, Heterogeneous, and Evolving Long-Term Memory

arXiv:2605.31086v1 Announce Type: new Abstract: In existing memory benchmarks for Large Language Models (LLMs), the evaluated dialogue sessions often lack long-term semantic consistency, and the under

Beyond Tokens: Enhancing RTL Quality Estimation via Structural Graph Learning

arXiv:2508.18730v2 Announce Type: replace Abstract: Estimating the quality of register transfer level (RTL) designs is crucial in the electronic design automation (EDA) workflow, as it enables instant

BlueFin: Benchmarking LLM Agents on Financial Spreadsheets

arXiv:2605.30907v1 Announce Type: cross Abstract: We present BlueFin, a benchmark that tasks large language model (LLM) agents with synthesis, manipulation, and comprehension tasks over spreadsheet wo

Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression

arXiv:2602.08885v5 Announce Type: replace-cross Abstract: Symbolic regression (SR) aims to discover interpretable analytical expressions that accurately describe observed data. Amortized SR promises t

Building Generalization Into Behavior Generation Via Adaptive Compositions of Regularities

arXiv:2605.31110v1 Announce Type: new Abstract: Generalization in robotics requires prior knowledge about how the world is structured, yet this structure changes from one situation to the next. This p

safetyarxiv-cs-ro

Calibrated Preference Learning: The Case of Label Ranking

arXiv:2605.30447v1 Announce Type: cross Abstract: Calibration, the alignment of predicted probabilities with true outcome frequencies, is essential for reliable decision-making. While extensively stud

CameraNoise: Enabling Faithful Camera Control in Video Diffusion through Geometry-Flow-Guided Noise Warping

arXiv:2605.30774v1 Announce Type: new Abstract: Precise camera pose control is critical for video diffusion, yet maintaining geometric consistency remains a challenge. Existing methods that directly i

Can Subgraph Explanations Be Weaponized to Steal Graph Neural Networks?

model-releasesarxiv-cs-lg

arXiv:2605.30470v1 Announce Type: new Abstract: Graph Machine Learning as a Service (GMLaaS) platforms increasingly implement explainability interfaces to meet regulatory transparency requirements. Ho