Search: “safety”

Generalizable VLA Finetuning via Representation Anchoring and Language-Action Alignment

arXiv:2607.13429v1 Announce Type: cross Abstract: Finetuning a pretrained vision-language model (VLM) on robot demonstrations via behavior cloning (BC) has become the standard recipe for vision-langua

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GNN-DIP: Neural Corridor Selection for Decomposition-Based Motion Planning

DGX agent

arXiv:2603.12361v2 Announce Type: replace Abstract: Motion planning through narrow passages remains a core challenge: sampling-based planners rarely place samples inside these narrow but critical regi

safetyarxiv-cs-ro

16 Jul 2026

Groc-PO: Grounded Context Preference Optimization for Truthful Multimodal LLMs

arXiv:2607.13712v1 Announce Type: cross Abstract: Despite the rapid progress of Multimodal Large Language Models (MLLMs), they still suffer from untruthfulness issues, such as visual hallucinations, c

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation

arXiv:2607.09776v2 Announce Type: replace-cross Abstract: When adapting Vision Language Action (VLA) models to downstream tasks, multiple rounds of post-training are often required to progressively ad

Human4K: A Large-Scale 4K Multi-View Mocap Dataset for Whole-Body 3D Human Reconstruction

arXiv:2607.13646v1 Announce Type: cross Abstract: Recent advances in 3D human reconstruction have improved overall performance, yet current models still fail in the most challenging real-world scenari

Introducing Human-Centeredness in AI-Assisted Lexicography

arXiv:2607.11808v2 Announce Type: replace-cross Abstract: This paper proposes a human-centered artificial intelligence (HCAI) framework for AI-assisted lexicography. While generative AI offers signifi

Inverse-LLaVA: Rethinking Multimodal Alignment via Text-to-Vision Mapping

arXiv:2508.12466v2 Announce Type: replace-cross Abstract: Traditional multimodal learning approaches rely on alignment pre-training to bridge vision and language modalities, typically by projecting vi

Joint On-and-Off Policy Learning for Vision-and-Language Navigation

arXiv:2607.13461v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) necessitates an embodied agent to navigate in the physical world by adhering to natural language instructions. Rece

LAPO: Leave-One-Turn Attribution for Self-Generated Process Rewards in Multi-Turn Search Reasoning

arXiv:2607.13501v1 Announce Type: new Abstract: Reinforcement learning for multi-turn search reasoning typically relies on terminal outcome rewards, which cannot distinguish useful, redundant, and har

Learning Red Agent Policy from Observations for Neurosymbolic Autonomous Cyber Agents

arXiv:2606.18223v2 Announce Type: replace-cross Abstract: With sophisticated cyber-attacks becoming increasingly prevalent, modern networks require intelligent autonomous cyber-defense agents trained

Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies

arXiv:2604.00830v3 Announce Type: replace-cross Abstract: Test-Time Learning (TTL) enables language agents to iteratively refine their performance through repeated interactions with the environment at

Marker-free deformable registration and fusion for augmented reality-guided positive margin localization during tumor resection surgery

arXiv:2607.13343v1 Announce Type: new Abstract: Positive margins in head and neck oncologic surgery require mapping specimen-side pathology findings to the patient resection bed. This is challenging b

MASPRM: Multi-Agent System Process Reward Model

arXiv:2510.24803v3 Announce Type: replace-cross Abstract: Inference-time search over multi-agent systems (MAS) wastes compute when it cannot identify which agent's intermediate message advanced progre

Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents

arXiv:2607.13591v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approach

Mind the Gap: Action Rebinding Attacks against Android GUI Agents

arXiv:2601.12349v3 Announce Type: replace-cross Abstract: Large multimodal model powered GUI agents are emerging as high-privilege operators on mobile platforms, entrusted to perceive screen content a

Music-to-Dance Generation via Atomic Movements

arXiv:2607.13978v1 Announce Type: cross Abstract: Music-driven dance generation aims to produce human motion that is both rhythmically synchronized and semantically consistent with music. While recent

Non-Expansive Two-Time-Scale Stochastic Approximation: A Fixed-Schedule One-Quarter Barrier and Bias-Corrected Acceleration

arXiv:2607.13414v1 Announce Type: cross Abstract: Non-expansive two-time-scale stochastic approximation is governed by a slow stochastic Krasnoselskii--Mann fixed-point iteration rather than by contra

NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache

arXiv:2505.18231v3 Announce Type: replace-cross Abstract: Large Language Model (LLM) inference is typically memory-intensive, especially when processing large batch sizes and long sequences, due to th

On the Sublinear Regret of Continuous K-Max Bandits

arXiv:2502.13467v2 Announce Type: replace Abstract: The K-Max combinatorial multi-armed bandit problem arises in applications such as recommendation and distributed decision making, where the reward i

Optimal and Efficient Contextual Combinatorial Semi-bandits with General Function Approximation

arXiv:2607.13686v1 Announce Type: new Abstract: We study the contextual combinatorial semi-bandit (CCSB) problem with general reward function approximation. At each round, the learner observes a conte

OrDA: Orthogonal Disentanglement of Access Habits Framework for Homepage Marketing Block Recommendations

arXiv:2607.13420v1 Announce Type: new Abstract: Clicks on homepage marketing blocks are driven by a dual-mechanism of content interest and access habits. However, habitual clicks often create Pseudo-P

PhysClaw-0: A Symbiotic Agentic System for Robot Autonomy via Language Corrections

arXiv:2607.14047v1 Announce Type: new Abstract: Autonomous data collection governs the volume and quality of real-world trajectories for manipulation policy learning. Existing pipelines reduce human e

Pretraining in Actor-Critic Reinforcement Learning for Locomotion

arXiv:2510.12363v4 Announce Type: replace-cross Abstract: The pretraining-finetuning paradigm has facilitated numerous transformative advancements in artificial intelligence research in recent years.

Price of Fairness in Bandits: A Tight Minimax Characterization

arXiv:2607.13402v1 Announce Type: cross Abstract: In bandit problems, standard regret-minimizing algorithms treat exploration as an amortized cost, which can expose early participants to unfair ex-ant

Privacy Preserving Recommender Systems Balancing Personalization with Privacy

arXiv:2607.13328v1 Announce Type: cross Abstract: Personalized recommendation systems are central to modern e-commerce and retail platforms, but they typically rely on centralized storage of detailed

PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference

arXiv:2607.13428v1 Announce Type: new Abstract: Positive-Unlabeled (PU) learning aims to achieve high-accuracy binary classification with limited labeled positive examples and numerous unlabeled ones.

RADAR: Closed-Loop Robotic Data Generation via Semantic Planning and Autonomous Causal Environment Reset

arXiv:2603.11811v2 Announce Type: replace-cross Abstract: The acquisition of large-scale physical interaction data, a critical prerequisite for modern robot learning, is severely bottlenecked by the p

Reverse to Advance: Teleoperation-Cost Effective Hard Policy Learning from Reversed Easy Tasks

arXiv:2607.13455v1 Announce Type: new Abstract: High-quality teleoperation datasets are costly to collect, particularly for hard tasks. We observe that many tasks exhibit directional asymmetry: comple

SARFA: Segment Anything with Radiomic Feature Alignment

arXiv:2607.13323v1 Announce Type: new Abstract: The Segment Anything Model (SAM) has demonstrated strong generalizability across a variety of segmentation tasks. However, SAM often struggles in situat

SCOPE-RL: Optimizing Reasoning Paths Before and After Success

arXiv:2607.11506v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) optimizes LLMs using sparse verifiable final-answer rewards. This sparse anchor reliably verif

ShortOPD: Recovering Pruned LLMs with Short-to-Long On-Policy Distillation

arXiv:2607.13124v1 Announce Type: cross Abstract: Structured pruning is a hardware-friendly way to compress LLMs, but it is mostly validated on multiple-choice recognition tasks, while the same compre

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning

arXiv:2607.13931v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) drives multimodal reasoning, but answer-level correctness does not guarantee that a vision-languag

Structured Reinforcement Learning for Bayesian Persuasion : Application to Intelligent Interactive Driving

arXiv:2607.13576v1 Announce Type: new Abstract: Interactive driving, wherein an intelligent lead vehicle equipped with real-time traffic data coordinates route choices of connected vehicles, offers a

The Cafe in Amsterdam: When the Incumbent Becomes the Oracle

arXiv:2607.13393v1 Announce Type: cross Abstract: A field can reformulate its computations freely exactly where its demand is stated independently of any incumbent implementation, and finds itself una

The SIGReg Objective as Variational Free Energy: A Theoretical Active-Inference Account of JEPA World Models

arXiv:2607.13612v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) are the dominant design for latent world models, yet they are usually justified by empirical performa

ThinkBLOX: 3D Indoor Scene Generation with Progressive Reasoning

arXiv:2607.13539v1 Announce Type: new Abstract: While traditional graphics methods often synthesize 3D indoor scenes autoregressively or hierarchically, recent vision-language model (VLM)-based genera

Track and Caption Any Motion: Open-Vocabulary Spatiotemporal Captioning via Trajectory-Conditioned Generation

arXiv:2512.10607v2 Announce Type: replace Abstract: We present TCAM (Track and Caption Any Motion), a generative framework that watches a video and with no text query and no region prompt decides what

Vision-Based Obstacle Separation for Strawberry Harvesting in Clusters Using Hierarchical Reinforcement Learning

arXiv:2607.13799v1 Announce Type: new Abstract: Selective harvesting in clustered strawberry environments is challenging because ripe fruits are often occluded by surrounding unripe fruits, making dir

Where Should RL Post-Training Compute Go? Model Size, Search, Learning, and Feedback

arXiv:2607.13389v1 Announce Type: new Abstract: Reinforcement Learning (RL) post-training is increasingly used to adapt foundation models for reasoning, planning, and feedback-driven robot-learning pi

AAAI-26 Dual Submissions: Novel Challenges

arXiv:2607.11918v1 Announce Type: cross Abstract: Dual submissions, in which identical or substantially similar papers are simultaneously submitted to one or more archival venues, without cross-citati

Accuracy and Normalized Accuracy under Length Bias: Analysis, Guidelines, and a Bayesian Alternative

arXiv:2607.12767v1 Announce Type: new Abstract: Multiple-choice benchmarks that rank candidate completions by conditional log-probability suffer from a length bias: because log-probabilities sum over

Auditable Context-Aware HFMD Forecasting with Structured LLM Agents

arXiv:2511.23276v2 Announce Type: replace Abstract: Effective HFMD surveillance requires forecasts capturing both time-series patterns and contextual drivers such as school calendars, weather, and pol

Beyond Coordinate Gauge: An Audited Protocol for Detecting Donor-Specific Functional Fingerprints after Neural Collapse

arXiv:2607.11967v1 Announce Type: cross Abstract: Independently trained neural networks have no shared neuron-index reference frame, so comparing them requires accounting for coordinate freedom. Neura

Beyond Parallel Tracking: Interactive Multi-Feature Fusion Drives Semantic Reconstruction from Non-invasive Brain Recordings

arXiv:2607.12071v1 Announce Type: new Abstract: Continuous semantic reconstruction from non-invasive neural recordings remains limited by the representational mismatch between semantic feature spaces

safetyarxiv-cs-cl

Calculating Mutual Information between a Reward Maximizer and its Environment

arXiv:2602.12963v2 Announce Type: replace Abstract: An important question in the field of AI is the extent to which successful behaviour requires an internal representation of the world. In this work,

Calibrated Selective Prediction Using Deep Ensembles for ROI-Based Thyroid Nodule Ultrasound Classification Under Dataset Shift: A Retrospective Evaluation

arXiv:2607.12075v1 Announce Type: cross Abstract: Background: Deep learning models can classify thyroid nodules on ultrasound, but reliable clinical decision support also requires calibrated probabili

Calibration-First Reward-Component Auditing for Reinforcement Learning Control in Smart Greenhouses

arXiv:2607.11959v1 Announce Type: new Abstract: Greenhouse reinforcement learning can test climate-control ideas at a speed and scale that is difficult to achieve with crop experiments alone. For smar

Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction

arXiv:2607.12835v1 Announce Type: new Abstract: Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, whe

safetyarxiv-cs-cl