safety

SafeTune: A Unified Faithful Library for Auditing and Repairing Safety Drift in Fine-Tuned LLMs

arXiv:2609.22153v1 Announce Type: new Abstract: Methods for addressing safety drift in fine-tuned Large Language Models (LLMs) are scattered across incompatible implementations, lifecycle stages, and

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Safety Control of a Hyper-redundant Robot via Adaptive Weighted Control Barrier Functions

DGX agent

arXiv:2609.24062v1 Announce Type: new Abstract: Hyper-redundant robots are well suited for confined-space manipulation due to their high dexterity, but safe operation in cluttered environments remains

safetyarxiv-cs-ro

22 Sept 2026

Safety-Critical Control under Uncertainty via Adaptive Conformal Quantile Prediction Intervals

arXiv:2609.23280v1 Announce Type: new Abstract: Safety-critical control under uncertainty requires uncertainty representations that are both statistically valid (for certifiable performance) and compa

Scale-Vector Alignment: A Scale-Aware Framework for Spatially Resolved Morphological Similarity in Astronomical Images

arXiv:2609.24304v1 Announce Type: cross Abstract: Astronomical maps made with different tracers are not expected to have identical morphology. Excitation, optical depth, chemistry, radiation, and ISM

Scaling Sim-to-Real VLA Reinforcement Learning with Generative 3D Worlds

arXiv:2603.18532v3 Announce Type: replace-cross Abstract: The strong performance of large vision-language models (VLMs) trained with reinforcement learning (RL) has motivated similar approaches for fi

SCULPT-VLA: Learning Structured Control through Staged Action Grounding

arXiv:2609.23275v1 Announce Type: new Abstract: Vision-language-action (VLA) policies increasingly incorporate structured intermediate supervision beyond action labels. Yet specifying what an intermed

See Selectively, Act Adaptively: Dual-Level Structural Decomposition for Bimanual Robot Manipulation

arXiv:2606.13279v2 Announce Type: replace Abstract: In bimanual robotic manipulation, task-relevant visual information varies with the task stage and context, while the interaction of the two arms shi

Seeing Through Conflicts: Improving Instruction Hierarchy Alignment in Vision-Language Models

arXiv:2609.22234v1 Announce Type: new Abstract: Instruction hierarchy (IH) alignment teaches language models to prioritize higher-level instructions when inputs conflict. While studied primarily in te

Selective Commitment for Language-Guided Object Retrieval under Partial Observability

arXiv:2609.23131v1 Announce Type: new Abstract: Language-guided object retrieval under partial observability requires deciding whether to gather more evidence, interact with the scene, grasp a candida

SenCache: Accelerating Diffusion Model Inference via Sensitivity-Aware Caching

arXiv:2602.24208v2 Announce Type: replace Abstract: Diffusion models achieve state-of-the-art video generation quality, but their inference remains expensive due to the large number of sequential deno

Shared Execution-Clock Drifting Policy for Dynamic Precision Manipulation

arXiv:2609.23305v1 Announce Type: new Abstract: Manipulation under time constraints requires both accurate actions and an execution rhythm that matches the evolving scene. This becomes critical when a

Simulating fault tolerance with stage skipping in pipeline-parallel training [R]

Our most recent work at Templar explores fault tolerance in Crucible, our distributed pre-training platform. The goal is to keep healthy workers training when another pipeline stage goes offline. Cruc

safetyr-machinelearning

Simultaneous Forward and Inverse Human-in-the-Loop Optimization

arXiv:2609.22630v1 Announce Type: new Abstract: Subjective user experience is important to human-robot interaction, but the outcomes users value, and how those preferences vary across individuals and

SmallSatSim: A GPU-Accelerated Microgravity Robotics Toolkit for Planning, Control, and Policy Learning

arXiv:2603.14598v2 Announce Type: replace Abstract: Microgravity rendezvous and close proximity operations (RPO) is a growing area of interest for applications spanning in-space assembly and manufactu

Smoothness as a Constraint for Stable Humanoid Locomotion

arXiv:2609.24552v1 Announce Type: new Abstract: Embodied AI systems, particularly humanoid robots deployed in real world scenarios require whole-body control policies that are both task-responsive and

Some Dialects Are More Equal Than Others: Non-Prestigious Arabic Dialectal Bias in LLMs

arXiv:2609.23955v1 Announce Type: new Abstract: Previous work on Egyptian Arabic in NLP has focused largely on the prestigious Cairene Egyptian Arabic (CEA) dialect, resulting in a lack of representat

SPACE: Semantic Projection and Alignment of CLIP Embeddings for Domain Adaptation

arXiv:2609.23248v1 Announce Type: new Abstract: A fundamental challenge in deploying vision models is domain shift, which arises when training and test data follow different distributions, leading to

Spiking Neural Network Actor-Critic Proximal Policy Optimization Control for Autonomous UAV Navigation Through Constrained Openings in Civil Infrastructure and Buildings

arXiv:2609.23643v1 Announce Type: new Abstract: Autonomous navigation of unmanned aerial vehicles in constrained three-dimensional environments has been a challenge in the robotics domain. The applica

Splat-CBF: Safe Next-Best-View Control in 3D Gaussian-Splat Maps

arXiv:2609.23100v1 Announce Type: new Abstract: Where to look and how to move? A robot navigating an unmapped environment must do both at once, and the two goals pull against each other. The regions m

Stable and Efficient Real-World Online VLA Post-Training via Asynchronous Replay-Anchored Policy Improvement

arXiv:2609.22888v1 Announce Type: new Abstract: Online post-training of vision-language-action (VLA) models requires efficient use of robot interaction and reliable policy improvement from continually

StenoVLA-3D: 3D-Aware Reasoning VLA for Navigation Through Gastrointestinal Stenoses

arXiv:2609.24187v1 Announce Type: cross Abstract: Autonomous endoscopic navigation requires the policy model to predict actions from texture-poor monocular observations, make safe control decisions, a

Strategic Classification Has a Missing Lever: Audit Risk

arXiv:2609.22534v1 Announce Type: cross Abstract: Strategic classification studies how a decision maker should choose a classifier when the agents being classified can adjust their features in respons

STRIDER: Stepping-Enabled Multi-Gait Hierarchical 3D Loco-Manipulation Framework for Humanoid Robots

arXiv:2609.23483v1 Announce Type: new Abstract: Humanoid loco-manipulation faces two prominent limitations: controllers using continuous velocity commands cannot precisely regulate individual foothold

Summarize, Judge, Refine: Decoupled Content Understanding and Policy Learning for Multimodal Content Moderation

arXiv:2609.22094v1 Announce Type: new Abstract: Content moderation systems traditionally entangle multimodal understanding with policy-specific classification, requiring full pipeline retraining for e

SupportCal: Label-Free Calibration of Post-Trained LLMs via Reference Support and Corroboration

arXiv:2609.24303v1 Announce Type: cross Abstract: Post-training often improves task performance but can degrade confidence calibration, leaving post-trained language models (PoLMs) more overconfident

TAC-Time: Texts as Channels For Multimodal Time Series Forecasting

arXiv:2609.24156v1 Announce Type: new Abstract: Most existing time series forecasting methods rely solely on numerical observations, overlooking rich contextual information from auxiliary texts. Recen

Tactile-JEPA: Topology-Aware Self-Supervised Representation Learning for Distributed Tactile Sensors

arXiv:2609.24385v1 Announce Type: new Abstract: Tactile sensing is an essential modality for robots performing contact-rich, dexterous manipulation, particularly under visual occlusion. While pre-trai

Task aware Dynamic Movement Primitives for failure detection and recovery in contact rich manipulation

arXiv:2609.23151v1 Announce Type: cross Abstract: Assembly remains a challenging robotic manipulation task in presence of tight tolerances and complex contact interactions. While Learning from Demonst

Teacher Should Think Ahead: Adaptive Continuations for Reliable On-Policy Distillation

arXiv:2609.22254v1 Announce Type: new Abstract: On-policy distillation (OPD) is a promising approach for transferring knowledge between language models, where a student receives dense token-level supe

Testing the Construct Validity of a Functional Valence Axis in LLM Agents

arXiv:2609.22850v1 Announce Type: new Abstract: Contrastive activation directions are often interpreted from what they decode or how strongly they steer behavior. But what evidence is sufficient to id

The Answer-Basin Representation Hypothesis: We Are Not Probing or Steering Concepts

arXiv:2609.24821v1 Announce Type: new Abstract: The Linear Representation Hypothesis associates high-level concepts with directions in language models, but it remains unclear how these concept-related

The Bairong System for MLC-SLM 2026: Dynamic Question-Aware Evidence Routing for Multilingual Conversational Speech Understanding

arXiv:2609.22214v1 Announce Type: new Abstract: Long multilingual conversational spoken question answering requires systems to balance long-range transcript semantics with sparse acoustic and speaker-

The Copy Ceiling: An Input-Exposure Control for Ontology-Grounded Generation over Curated Corpora

arXiv:2609.24885v1 Announce Type: new Abstract: When a language model answers from a curated corpus via graph-based retrieval, a large grounding uplift does not establish reasoning over the retrieved

The Evidence Ladder for Reinforcement Learning in Healthcare: From Retrospective Policies to Trusted Interventions

arXiv:2609.23374v1 Announce Type: new Abstract: Reinforcement learning (RL) offers a natural language for healthcare decisions whose conse- quences unfold over time, yet most reported progress remains

The longer the AI psychodrama goes on, the more it’s clear we are dealing with a conventional business bubble. What’s different this time is…

The longer the AI psychodrama goes on, the more it’s clear we are dealing with a conventional business bubble. What’s different this time is the lengths to which the companies will go to put off the r

safetygary-marcus--x

Think Like a World Model, Act Like a VLA: Distilling World-Model Representations into Compact Robot Policies

arXiv:2609.24682v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models map observations to actions with no objective that accounts for how the world responds, so their robustness is bou

Touch2Robot: Robot Touch in the Human Demonstration Loop

arXiv:2609.24660v1 Announce Type: new Abstract: Human demonstrations offer a scalable way to collect manipulation data, but their contacts may be unstable or infeasible when transferred to a robot han

Toward Fairness in Machine Learning Models for Predicting Treatment Retention and Premature Discontinuation in Medication for Opioid Use Disorder

arXiv:2609.22113v1 Announce Type: new Abstract: Persistent low retention and completion rates in medications for opioid use disorder (MOUD) have driven the use of machine learning (ML) models to predi

Transductive Off-policy Proximal Policy Optimization

arXiv:2406.03894v2 Announce Type: replace Abstract: Proximal Policy Optimization (PPO) is a popular model-free reinforcement learning algorithm, esteemed for its simplicity and efficacy. However, due

Transformer-Based Warm-Starting for Feasible and Optimal Terminal Approach to Tumbling Objects with Space Manipulators

arXiv:2606.17317v2 Announce Type: replace Abstract: Autonomous capture of a tumbling object with a space manipulator requires trajectory generation under real-time onboard constraints. However, couple

TreeSpark: Calibrated, Load-Adaptive Draft Trees for Semi-Autoregressive Speculative Decoding

arXiv:2609.22098v1 Announce Type: new Abstract: Speculative decoding accelerates language-model inference by letting a cheap drafter propose tokens that the target model verifies in parallel. Recent b

Tutoring Large Language Models to be Domain-adaptive, Precise and Safe

arXiv:2609.23071v1 Announce Type: cross Abstract: This thesis proposes a framework for 'responsible intelligence' to address AI's critical challenges in safety, ethics, and cultural sensitivity. It ad

UniPoint: Unified Point-Level Sensor Fusion for Humanoid Locomotion Across Challenging Terrains

arXiv:2609.23666v1 Announce Type: new Abstract: Open-world deployment requires humanoid robots to cross highly heterogeneous terrain safely, with perception that simultaneously provides wide coverage,

Unlocking Pretrained Vision Transformers for Time Series Classification

arXiv:2506.08641v3 Announce Type: replace-cross Abstract: Adapting vision models for time series analysis is compelling, yet all existing approaches are falling short of dedicated time series foundati

Uranus: Building the Next-Generation Simulation Infrastructure for Embodied AI

arXiv:2609.24815v1 Announce Type: new Abstract: Scalable simulation is essential for robot data generation, policy training, evaluation, and safe iteration, yet real-world interaction is costly and co

Verti-WM: A Physics-Aided Exteroceptive World Model for Off-Road Reinforcement Learning

arXiv:2609.23118v1 Announce Type: new Abstract: Reinforcement learning for off-road navigation requires extensive vehicle-terrain interaction data, which are costly to collect in high-fidelity simulat

VISTA: Video-Injected Stylized Text-to-Animation

arXiv:2609.23817v1 Announce Type: new Abstract: We present VISTA, a two-stage framework for generating stylized 3D human motion by fusing structural content from text prompts with expressive style fro

Visuomotor Robotic Pruning in Planar Orchards Using Hybrid Reinforcement Learning

arXiv:2609.24906v1 Announce Type: new Abstract: Dormant tree pruning is labor-intensive yet essential for maintaining modern high-productivity fruit orchards. In this work, we focus on pruning of mode