Search: “safety”

Learning Options for Compositional Motor Control with Adapter Banks

arXiv:2609.17042v1 Announce Type: new Abstract: Learning flexible motor primitives is a hallmark of skilled motor control. Recent neuroscience theory proposes that motor primitives may be implemented

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Learning to Optimize UAV Path Planning for Data Sensing in Wireless Sensor Networks

DGX agent

arXiv:2609.16629v1 Announce Type: new Abstract: UAVs have emerged as highly flexible platforms for data sensing in Wireless Sensor Networks (WSNs). Path planning for UAVs in such tasks plays a key rol

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16 Sept 2026

LiLi: Lie Theory Based 3D LiDAR Scan Alignment Degeneracy Detection

arXiv:2609.17145v1 Announce Type: new Abstract: In this paper, we study 3D LiDAR scan alignment in challenging scenarios with degeneracies, such as straight corridors or flat fields, where the alignme

'Looking for Something Weird to Happen': How Humans Sustain AI Agent Novelty Amid Semantic Collapse

arXiv:2609.16051v1 Announce Type: cross Abstract: Semantic collapse, the progressive narrowing of what AI systems generate, has been studied mainly in closed settings, and remedies have targeted model

ManiSkillFormer: Demonstration-Free Compositional Manipulation via Task-Conditioned Geometric Contracts

arXiv:2609.16331v1 Announce Type: new Abstract: We present ManiSkillFormer, a neuro-symbolic framework for demonstration-free and compositional robotic manipulation. Instead of learning end-to-end vis

MDN-Control: Mask-Depth-Noise Guided Region Control for Multi-Subject Video Editing

arXiv:2609.16475v1 Announce Type: new Abstract: Multi subject video editing modifies designated subjects while preserving non target content, but faces cross subject attribute leakage, and occlusion a

Mem-World: Memory-Augmented Action-Conditioned World Models for Persistent Robot Manipulation

arXiv:2606.18960v3 Announce Type: replace Abstract: Action-conditioned world models have emerged as a promising paradigm for robot learning, offering a scalable alternative to costly real-world experi

Memorisation bias in medical AI

arXiv:2609.17223v1 Announce Type: new Abstract: Medical AI models hold immense potential to improve patient outcomes, but they are also known to unintentionally memorise individual records from their

MiCRo: Mixture Modeling and Context-aware Routing for Personalized Preference Learning

arXiv:2505.24846v3 Announce Type: replace Abstract: Reward modeling is a key step in building safe foundation models when applying reinforcement learning from human feedback (RLHF) to align Large Lang

Mind the Gap: Rethinking I/O Design for Contact-Rich Visuomotor Policy Learning

arXiv:2602.08776v2 Announce Type: replace Abstract: Contact-rich teleoperation logs expose a policy I/O design choice: demonstrations may contain the robot execution (E), leader command (C), or both.

Mini-batch Sampling Strategies for Long-Tailed Image Classification: An Empirical Study on CIFAR-100-LT

arXiv:2609.16365v1 Announce Type: cross Abstract: Real-world datasets often exhibit long-tailed class distributions, where a few head classes contain a large number of training samples while a large n

Nationally Consistent, Locally Incomplete: A Bayesian Remote-Sensing Audit of Rooftop Photovoltaic Registries

arXiv:2609.16294v1 Announce Type: cross Abstract: Tracking the energy transition requires reliable statistics on renewable deployment. Rooftop photovoltaics (PV) are especially hard to track, owing to

Never Stop Thinking: Continuous-Time Language Agents

arXiv:2609.17416v1 Announce Type: new Abstract: Voice agents built on LLMs follow a rigid listen-think-speak loop that inserts seconds of dead air before every reply. We show that continuous-time cogn

OmniHarness: Harnessing Generalizable Visual Generation via Symbolic Policy Learning

arXiv:2609.16057v1 Announce Type: cross Abstract: Unified multimodal large language models (MLLMs) and multi-agent systems have advanced visual generation. However, three limitations remain. (1) Exist

OPD-Aha: From Linguistic Momentum to Visual Reflection in Multimodal On-Policy Distillation

arXiv:2609.16459v1 Announce Type: cross Abstract: Privileged on-policy distillation improves multimodal reasoning by allowing a teacher to evaluate student trajectories using rich, training-only visua

Optimal Model Activation Policies for Inference Networks of Large Language Models

arXiv:2609.15992v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have rendered them necessary for Natural Language Processing (NLP) tasks, and their high inference cost

Physics Informed Random Feature Neural Networks for Solving PDEs

arXiv:2609.16406v1 Announce Type: cross Abstract: Machine learning-based partial differential equations (PDEs) solvers have attracted significant attention in recent years. Most progress in this area

Post-Training Large Language Models via Reinforcement Learning from Self-Feedback

arXiv:2507.21931v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) often produce plausible but poorly-calibrated answers, limiting their reliability on reasoning-intensive tasks. R

PriorPose: Reference-Guided Joint Deformation and Alignment for Category-Level Object Pose Estimation

arXiv:2609.16727v1 Announce Type: new Abstract: Category-level object pose estimation seeks to recover a similarity transform (R,t,s) for unseen instances without instance-specific CAD models. Most co

ProxiDex: Learning Dynamics-Guided Proximity Policy for Dexterous Manipulation

arXiv:2609.16586v1 Announce Type: cross Abstract: Multi-finger dexterous manipulation relies on stable hand-object interactions, yet these interactions are partially observable in practice. Visual obs

R3: Robust Rubric-Agnostic Reward Models

arXiv:2505.13388v4 Announce Type: replace-cross Abstract: Reward models are essential for aligning language model outputs with human preferences, yet existing approaches often lack both controllabilit

Residual Fault Adaptation for Dexterous In-Hand Manipulation Under Runtime Joint Faults

arXiv:2609.17404v1 Announce Type: new Abstract: Dexterous in-hand manipulation requires coordinated control of multiple actuated joints, and a runtime joint fault can abruptly disrupt the contact conf

Rethinking Visual Embodiment Dependence in Visuomotor Policies

arXiv:2609.16815v1 Announce Type: new Abstract: Visuomotor policies observe both the task scene and the acting embodiment, allowing embodiment-specific visual cues to influence action prediction. We s

Robust Recurrent Reinforcement Learning under Evolving Hidden Disturbances with Application to Rover Wheel Slip

arXiv:2307.15931v3 Announce Type: replace Abstract: Reinforcement learning (RL) performs well in continuous-control tasks, but evolving hidden disturbances create partial observability: the agent must

SAVLA: Symmetry-Aware Vision-Language-Action Models for Robotic Manipulation

arXiv:2609.16641v1 Announce Type: new Abstract: Vision-language-action (VLA) models have become the dominant paradigm for language-conditioned robot manipulation. However, although images and language

SAVOR: Self-Aware Visual Grounding via Confidence-Calibrated Reinforcement Learning for Multimodal Hallucination Mitigation

arXiv:2609.16601v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made strong progress on visual question answering and image captioning, yet they still produce fluent clai

SlotDiT: Object-Centric Representations for Diffusion Transformers

arXiv:2609.17414v1 Announce Type: new Abstract: Text-conditioned latent diffusion models perform strongly in video generation and are promising backbones for robotic applications. However, existing ap

Smarter by the Moment: Environment-Driven Dynamic Policies for Continual LLM Improvement

arXiv:2609.16800v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable progress across diverse domains, but continual adaptation to evolving tasks and environments remai

Splitting the Difference: Interpretable Causal Forests for Treatment Effect Heterogeneity and Bias

arXiv:2609.16971v1 Announce Type: cross Abstract: In various fields, such as medicine and marketing, accurately predicting individual treatment effects holds significant promise. However, achieving re

Spurious Tool Use: When RL Agents Learn the Wrong Reason to Act

arXiv:2609.16268v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly interleave natural language reasoning with external tools such as web search and code execution. These to

Stable by Construction: Variational Latent Markov Operators for Long-Horizon PDE Prediction

arXiv:2609.16621v1 Announce Type: new Abstract: Neural PDE solvers provide efficient surrogates for time-dependent physical systems, but autoregressive prediction over long horizons remains challengin

SWIM: Vision-Language-Grounded Soft Whole-Body Interactive Manipulation

arXiv:2609.17035v1 Announce Type: new Abstract: Soft and continuum robots enable manipulation through distributed body deformation and contact, yet translating language and visual context into executa

TARC: Time-Adaptive Robotic Control

arXiv:2510.23176v2 Announce Type: replace-cross Abstract: Most robotic systems rely on fixed-frequency discrete-time controllers, creating a trade-off between the efficiency of low-frequency control a

TecoPrompt: Temporal-Conservative Prompt Learning for Vision-Language Models

arXiv:2609.16858v1 Announce Type: new Abstract: Prompt learning adapts vision-language models, such as CLIP, by adjusting a small set of context tokens. However, under few-shot supervision, even moder

The MAL Simulator: Cyber Operations Simulation based on Attack & Defense Graphs

arXiv:2609.16563v1 Announce Type: cross Abstract: We have developed the MAL Simulator, a cyber operation simulator based on the Meta Attack Language (MAL). The MAL Simulator is intended for decision-d

ThinkFlow: Self-Evolving Probabilistic Latent Memory for Lifelong Conversational Agents

arXiv:2609.17010v1 Announce Type: new Abstract: Lifelong conversational agents rely on memory systems to maintain deep, context-aware interactions with users. However, existing explicit textual memory

Toward Governance-Aware Autonomous GIS: A Narrative Review of Ethical and Privacy Risks in LLM-Enabled GeoAI

arXiv:2609.16232v1 Announce Type: new Abstract: Geospatial artificial intelligence (GeoAI) powered by large language models (LLMs) is expanding the capacity to query, generate, and interpret spatial i

Towards Scalable RLVR: Multimodal Instruction Following Data Synthesis and Distillation

arXiv:2609.16059v1 Announce Type: new Abstract: Multimodal instruction following (MMIF) is crucial for building generalist agents. However, current training paradigms rely heavily on Supervised Fine-T

Towards Surrogate Based Dequantization of Quantum Reinforcement Learning

arXiv:2609.16266v1 Announce Type: cross Abstract: In recent years, the utility of parameterized quantum circuits as function approximators has been widely studied. In the context of reinforcement lear

Turn-level Multiscale Density Ratio Estimation for LLM Agents

arXiv:2609.16760v1 Announce Type: new Abstract: With the rapid development of Large language model (LLM), agent systems enhanced by LLMs show huge potential in being able to deal with complex tasks, e

Type-IV Code Clone Detection via Layer-Wise Non-Contrastive Representation Learning

arXiv:2609.17338v1 Announce Type: cross Abstract: Software clones are fragments of code that are similar or functionally equivalent to each other. They pose significant challenges for maintenance, ref

UniDex-ViTac: Learning Unified Visuo-Tactile Dexterous Manipulation Policy from Human Video Data

arXiv:2609.16504v1 Announce Type: new Abstract: Human videos provide demonstrations of dexterous manipulation but lack robot-executable actions and tactile measurements. We present UniDex-ViTac, a fra

Unlocking Zero-shot Potential of Semi-dense Image Matching via Gaussian Splatting

arXiv:2511.21265v2 Announce Type: replace Abstract: Learning-based image matching critically depends on large-scale, diverse, and geometrically accurate training data. 3D Gaussian Splatting (3DGS) ena

Weave: Learning Whole-Body Dexterous Loco-Manipulation from Human-Object Interactions

arXiv:2609.16683v1 Announce Type: cross Abstract: Learning humanoid-object interaction requires coordinating whole-body balance, locomotion, and dexterous hand contact to control both robot and object

What Does Layer-Importance Reveal About Transformers and State-Space Models?

arXiv:2609.16537v1 Announce Type: cross Abstract: Transformers and state-space models (SSMs) are the two dominant families of sequence models, and a central open question is how far the analytical kno

When majority rules, minority loses: bias amplification of gradient descent

arXiv:2505.13122v3 Announce Type: replace-cross Abstract: Despite growing empirical evidence of bias amplification in machine learning, its theoretical foundations remain poorly understood. We develop

Where Should the KV Cache Live? Placement Policies Across GPU, CPU, and SSD for Long-Lived Sessions

arXiv:2609.16215v1 Announce Type: new Abstract: GPU high bandwidth memory is scarce and expensive, and KV caches consume much of it as chats, agent loops, and document question answering accumulate st

World-Action Models for Robot Learning and Control: A Survey

arXiv:2609.16074v1 Announce Type: cross Abstract: Robots operating in open environments act under partial observability, physical constraints, and dynamic task contexts. Beyond mapping observations an