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A Single Deep Preference-Conditioned Policy for Learning Pareto Coverage Sets

arXiv:2605.08946v1 Announce Type: new Abstract: Preference-conditioned multi-objective reinforcement learning aims to learn a single policy that captures trade-offs across preferences, but under nonli

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Active Tabular Augmentation via Policy-Guided Diffusion Inpainting

DGX agent

arXiv:2605.10315v1 Announce Type: cross Abstract: Generative tabular augmentation is appealing in data-scarce domains, yet the prevailing focus on distributional fidelity does not reliably translate i

safetyarxiv-cs-ai

12 May 2026

Adaptive Context Matters: Towards Provable Multi-Modality Guidance for Super-Resolution

arXiv:2605.10470v1 Announce Type: new Abstract: Super-resolution (SR) is a severely ill-posed problem with inherent ambiguity, as widely recognized in both empirical and theoretical studies. Although

Adaptive Data Harvesting for Efficient Neural Network Learning with Universal Constraints

arXiv:2605.09707v1 Announce Type: cross Abstract: Training neural networks to satisfy universal constraints over continuous domains poses unique challenges. Common examples include Lyapunov Neural Net

Agent-Omit: Adaptive Context Omission for Efficient LLM Agents

arXiv:2602.04284v2 Announce Type: replace Abstract: Managing agent context (e.g., thought and observation) during multi-turn agent-environment interactions is an emerging strategy to improve agent eff

AgentReview: Exploring Peer Review Dynamics with LLM Agents

arXiv:2406.12708v3 Announce Type: replace Abstract: Peer review is fundamental to the integrity and advancement of scientific publication. Traditional methods of peer review analyses often rely on exp

AIPO: : Learning to Reason from Active Interaction

arXiv:2605.08401v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have demonstrated remarkable reasoning capabilities, largely stimulated by Reinforcement Learning with

ALAM: Algebraically Consistent Latent Transitions for Vision-Language-Action Models

arXiv:2605.10819v1 Announce Type: cross Abstract: Vision-language-action (VLA) models remain constrained by the scarcity of action-labeled robot data, whereas action-free videos provide abundant evide

Align and Shine: Building High-Quality Sentence-Aligned Corpora for Multilingual Text Simplification

arXiv:2605.09476v1 Announce Type: cross Abstract: Text simplification plays a crucial role in improving the accessibility and comprehensibility of written information for diverse audiences, including

Aligning LLM Uncertainty with Human Disagreement in Subjectivity Analysis

arXiv:2605.10415v1 Announce Type: new Abstract: Large language models for subjectivity analysis are typically trained with aggregated labels, which compress variations in human judgment into a single

Aligning Validation with Deployment: Target-Weighted Cross-Validation for Spatial Prediction

arXiv:2603.29981v2 Announce Type: replace Abstract: Reliable estimation of predictive performance is essential for spatial environmental modeling, where machine-learning models are used to generate ma

Alignment as Jurisprudence

arXiv:2605.08416v1 Announce Type: new Abstract: Jurisprudence, the study of how judges should properly decide cases, and alignment, the science of getting AI models to conform to human values, share a

Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels

arXiv:2509.20294v4 Announce Type: replace Abstract: We study spectral algorithms in the setting where kernels are learned from data. We introduce the effective span dimension (ESD), an alignment-sensi

Anatomical Landmark-Guided Deep Reinforcement Learning for Autonomous Gastric Navigation

arXiv:2605.08269v1 Announce Type: new Abstract: Wireless capsule endoscopy (WCE) enables painless visualization of the gastrointestinal tract, but its diagnostic potential is limited by incomplete muc

safetyarxiv-cs-ro

Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring

arXiv:2510.13397v3 Announce Type: replace Abstract: Dropout is common in clinical studies, with up to half of patients leaving early due to side effects or other reasons. When dropout is informative (

Assessing Trustworthiness of AI Training Dataset using Subjective Logic -- A Use Case on Bias

arXiv:2508.13813v2 Announce Type: replace-cross Abstract: As AI systems increasingly rely on training data, assessing dataset trustworthiness has become critical, particularly for properties like fair

Attention-Mamba: A Mamba-Enhanced Multi-Scale Parallel Inference Network for Medical Image Segmentation

arXiv:2402.02286v4 Announce Type: replace-cross Abstract: U-shaped architectures have long dominated the field of medical image segmentation, while Transformers are widely employed for modeling long-r

Attention Sinks in Diffusion Transformers: A Causal Analysis

arXiv:2605.09313v1 Announce Type: new Abstract: Attention sinks -- tokens that receive disproportionate attention mass -- are assumed to be functionally important in autoregressive language models, bu

Auction-Based Online Policy Adaptation for Evolving Objectives

arXiv:2604.02151v2 Announce Type: replace Abstract: We consider multi-objective reinforcement learning problems where objectives come from an identical family -- such as the class of reachability obje

Auditing Data Membership in Reinforcement Learning With Verifiable Rewards

arXiv:2511.14045v2 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a core training stage in recent large language models (LLMs). Its reliance on

Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria

arXiv:2605.08354v1 Announce Type: new Abstract: Aligning multimodal generative models with human preferences demands reward signals that respect the compositional, multi-dimensional structure of human

Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge

arXiv:2605.10370v1 Announce Type: new Abstract: Scientific knowledge on the Web is published as passive assertions and cannot decide when to validate evidence, reconcile contradictions, or update conf

Balancing Efficiency and Fairness in Traffic Light Control through Deep Reinforcement Learning

arXiv:2605.10170v1 Announce Type: new Abstract: Urban traffic congestion presents a significant challenge for modern cities, which impacts mobility and sustainability. Traditional traffic light contro

BathyFacto: Refraction-Aware Two-Media Neural Radiance Fields for Bathymetry

arXiv:2605.10174v1 Announce Type: new Abstract: Through-water photogrammetry based on UAV imagery enables shallow-water bathymetry, but refraction at the air-water interface violates the straight-ray

BEACON: Cross-Domain Co-Training of Generative Robot Policies via Best-Effort Adaptation

arXiv:2605.08571v1 Announce Type: new Abstract: We introduce BEACON--Best-Effort Adaptation for Cross-Domain Co-Training--a theory-driven framework for training generative robot policies with abundant

safetyarxiv-cs-ro

Behavioral Determinants of Deployed AI Agents in Social Networks: A Multi-Factor Study of Personality, Model, and Guardrail Specification

arXiv:2605.08463v1 Announce Type: new Abstract: Autonomous AI agents are increasingly deployed in open social environments, yet the relationship between their configuration specifications and their em

Beyond Continuity: Challenges of Context Switching in Multi-Turn Dialogue with LLMs

arXiv:2605.09268v1 Announce Type: cross Abstract: Users interacting with Large Language Models (LLMs) in a multi-turn conversation routinely refine their requests or pivot to new topics. LLMs, however

Beyond ESG Scores: Learning Dynamic Constraints for Sequential Portfolio Optimization

arXiv:2605.09310v1 Announce Type: new Abstract: ESG-aware portfolio optimization is increasingly important for sustainable capital allocation, yet most learning-based methods still operationalize ESG

Beyond Multiple Choice: Evaluating Steering Vectors for Summarization

arXiv:2505.24859v3 Announce Type: replace-cross Abstract: Steering vectors are a lightweight method for controlling text properties by adding a learned bias to language model activations at inference

Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning

arXiv:2605.08202v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) faces a critical challenge of overestimating the value of out-of-distribution (OOD) actions. Existing methods miti

Beyond Position Bias: Shifting Context Compression from Position-Driven to Semantic-Driven

arXiv:2605.09463v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated exceptional performance across diverse tasks. However, their deployment in long-context scenarios faces h

Beyond Static Bias: Adaptive Multi-Fidelity Bandits with Improving Proxies

arXiv:2605.08558v1 Announce Type: new Abstract: As an extension of the classical multi-armed bandit problem, multi-fidelity multi-armed bandits (MF-MAB) enable individual arms to be evaluated using di

Bi-CoG: Bi-Consistency-Guided Self-Training for Vision-Language Models

arXiv:2510.20477v2 Announce Type: replace Abstract: Exploiting unlabeled data through semi-supervised learning (SSL) or leveraging pre-trained models via fine-tuning are two prevailing paradigms for a

Bias by Necessity: Impossibility Theorems for Sequential Processing with Convergent AI and Human Validation

arXiv:2605.08716v1 Announce Type: new Abstract: Are certain cognitive biases mathematically inevitable consequences of sequential information processing? We prove that primacy effects, anchoring, and

Big AI is accelerating the metacrisis: What can we do?

arXiv:2512.24863v2 Announce Type: replace-cross Abstract: The world is in the grip of ecological, meaning, and language crises that are converging into a metacrisis. Big AI is accelerating them all. L

Biological Plausibility and Representational Alignment of Feedback Alignment in Convolutional Networks

arXiv:2605.08564v1 Announce Type: new Abstract: The feedback alignment (FA) algorithm offers a biologically plausible alternative to backpropagation (BP) for training neural networks yet notably fails

Block-Wise Differentiable Sinkhorn Attention: Tail-Refinement Gradients with a Gap-Aware Dustbin Bridge

arXiv:2605.08123v1 Announce Type: cross Abstract: We study long-context balanced entropic optimal transport (OT) attention on TPU hardware through a stopped-base, fixed-depth tail-refinement surrogate

BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability

arXiv:2602.07144v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) is a popular technique for sample-efficient optimization of black-box functions. In many applications, the paramete

Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spaces

arXiv:2602.08616v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) is increasingly applied to large-scale decision-making problems like logistics, scheduling, and recommender system

Breaking the Impasse: Dual-Scale Evolutionary Policy Training for Social Language Agents

arXiv:2605.08721v1 Announce Type: new Abstract: While Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for closed-ended tasks, extending it to open-ended social language game

BRIDGE: Building Representations In Domain Guided Program Synthesis

arXiv:2511.21104v3 Announce Type: replace Abstract: Large language models can generate plausible code, but remain brittle for formal verification in proof assistants such as Lean. A central scalabilit

BROS: Bias-Corrected Randomized Subspaces for Memory-Efficient Single-Loop Bilevel Optimization

arXiv:2605.10288v1 Announce Type: new Abstract: Stochastic bilevel optimization (SBO) has become a standard framework for hyperparameter learning, data reweighting, representation learning, and data-m

Budget-Efficient Automatic Algorithm Design via Code Graph

arXiv:2605.10598v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as powerful tools for automatic algorithm design (AAD). However, existing pipelines remain inefficient. They o

CalBench: Evaluating Coordination-Privacy Trade-offs in Multi-Agent LLMs

arXiv:2605.09823v1 Announce Type: cross Abstract: We introduce CalBench, a controlled evaluation environment for studying multi-agent coordination through calendar scheduling. In CalBench, N agents ea

CAMAL: Improving Attention Alignment and Faithfulness with Segmentation Masks

arXiv:2605.08325v1 Announce Type: cross Abstract: Many vision datasets now provide segmentation masks in addition to annotated images to support a wide range of tasks. In this work, we propose Class A

Can LLMs Estimate Student Struggles? Human-AI Difficulty Alignment with Proficiency Simulation for Item Difficulty Prediction

arXiv:2512.18880v2 Announce Type: replace-cross Abstract: Accurate estimation of item (question or task) difficulty is critical for educational assessment but suffers from the cold start problem. Whil

Can Revealed Preferences Clarify LLM Alignment and Steering?

arXiv:2605.08556v1 Announce Type: new Abstract: LLMs are increasingly used to make or support high-stakes decisions under uncertainty, where alignment depends not only on factual accuracy but on how m

CapCLIP: A Vision-Language Representation Alignment Approach for Wireless Capsule Endoscopy Analysis

arXiv:2605.08493v1 Announce Type: new Abstract: Wireless capsule endoscopy (WCE) enables non-invasive visual assessment of the small bowel, but its clinical utility is constrained by the large volume