Search: “safety”

Absolutely right Gary. LLMs simply don't understand causality at the level needed to make truly data driven decisions. My work combines Caus…

Absolutely right Gary. LLMs simply don't understand causality at the level needed to make truly data driven decisions. My work combines Causal AI (using Pearl's Causal Calculus), knowledge graphs, LLM

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Accuracy Is Not Enough: A Cross-Architecture Audit of Demographic Bias in Deep Knowledge Tracing

DGX agent

arXiv:2609.20249v1 Announce Type: new Abstract: Deep knowledge tracing (DKT) models implicitly decide which students an adaptive system believes have mastered a skill, yet almost all evidence on their

safetyarxiv-cs-lg

18 Sept 2026

Agile-WAM: An Agile Tactile World Action Model for Contact-Rich Robot Control

arXiv:2609.20761v1 Announce Type: cross Abstract: World Action Models (WAMs) advance beyond conventional visuomotor policies by jointly predicting future world states and robot actions, enabling the p

AI Should Facilitate Democratic Deliberation at Scale

arXiv:2609.20059v1 Announce Type: cross Abstract: AI systems can strengthen democracy by supporting deliberation at scale by addressing cognitive, social, platform-design, and market-driven frictions,

AnyViewDex: View-Invariant Dexterous Manipulation from RGB Observations

arXiv:2609.20107v1 Announce Type: new Abstract: Visuomotor policies for multi-fingered dexterous manipulation are highly sensitive to camera viewpoint shifts. To achieve view invariance, recent method

Calibrated RF-Fingerprinting Under Interference With Heterogeneous Transmission Protocols

arXiv:2609.20765v1 Announce Type: new Abstract: Radio Frequency(RF)-Fingerprinting is a spectrum monitoring technique that identifies specific transmitters based on hardware impairments imprinted with

CARE-VI: Conservative Adaptive Reliability Estimation for Value Improvement in Off-Policy Actor-Critic Learning

arXiv:2609.20098v1 Announce Type: new Abstract: Reliable temporal-difference targets are central to off-policy actor-critic learning. Direct value improvement refines the next-state target with altern

CellRFT: Reinforcement Fine-Tuning for Single-Cell Perturbation Modeling

arXiv:2609.19970v1 Announce Type: new Abstract: Predicting cellular responses to perturbations supports the study of gene function, disease mechanisms, and therapeutic strategies. Despite advances in

Compliance for Free: Learning Identifiable Impedance via Bilateral Teleoperation

arXiv:2609.19976v1 Announce Type: new Abstract: Vision-language-action models tell a robot where to move, but not how hard to push. Contact-rich tasks depend on that second quantity, compliance, yet n

CORAL-AUV: CFD Oriented Reinforcement Learning for Autonomous Underwater Vehicles

arXiv:2607.09557v2 Announce Type: replace Abstract: Fine grain control and positioning of autonomous underwater vehicles (AUVs) is critical for sampling, maintenance, and survey applications. Traditio

CoRe: Coherence and Relational Alignment for Multivariate Time Series Forecasting

arXiv:2609.19670v1 Announce Type: new Abstract: Direct forecasting has become a standard paradigm for multivariate time-series forecasting because it predicts the full future horizon in a single pass.

DeliveryGym: An RL Environment for Long-Horizon Embodied Agent Planning with Adaptive Curriculum

arXiv:2609.19801v1 Announce Type: new Abstract: Executable environments enable LLM agents to learn from the consequences of their actions. For embodied agents, those consequences extend beyond whether

DexTouch-WM: Learning Action-Conditioned Tactile World Models from Human Touch for Dexterous Robot Manipulation

arXiv:2609.20649v1 Announce Type: cross Abstract: Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots

Diagnose, Recover, Certify: Task Readiness under Hidden Dynamics Changes

arXiv:2609.20304v1 Announce Type: new Abstract: A deployed control policy can conceal consequential dynamics changes: an actuator may lose effectiveness without affecting the current task when the pol

Don't Mask the Environment: Observation Supervision Changes How Agents Explore Under RL

arXiv:2609.20715v1 Announce Type: cross Abstract: Agent trajectories record what an agent does and what happens next. Yet standard supervised fine-tuning (SFT) applies loss only to agent-authored acti

Dual-Axis Policy Optimization for LLM Agents: Bayesian Feedback Attribution and Trajectory Mass Normalization

arXiv:2609.19830v1 Announce Type: new Abstract: Reinforcement learning for LLM agents involves two distinct optimization di- mensions: how environment feedback is exploited within a trajectory, and ho

Dynamic Generalized Gromov-Wasserstein Optimal Transport

arXiv:2609.20008v1 Announce Type: cross Abstract: Gromov--Wasserstein optimal transport (GW-OT) extends classical optimal transport by introducing structure-aware transport cost. This is particularly

DynaWeightPnP: Toward global real-time 3D-2D solver in PnP without correspondences

arXiv:2409.18457v2 Announce Type: replace Abstract: This paper addresses a special Perspective-n-Point (PnP) problem: estimating the optimal pose to align 3D and 2D shapes in real-time without corresp

Efficient Nash Equilibrium Computation for Cybersecurity Games

arXiv:2609.19399v1 Announce Type: cross Abstract: Computing Nash equilibria of simulation-based cybersecurity games with policy-space response oracles (PSRO) is bottlenecked by payoff estimation: ever

Embedding Models Measure in Peculiar Ways

arXiv:2609.20821v1 Announce Type: new Abstract: Embedding spaces define notions of semantic similarity and distance. We study whether those embeddings reflect physical measurements of mass, distance,

safetyarxiv-cs-cl

even the anti-woke media sure loves this narrative. doesn’t make it true.

even the anti-woke media sure loves this narrative. doesn’t make it true. 'I worked at OpenAI for two years before resigning in 2024. Fears that AI will cause human extinction are real. You should tak

Feeling Terrain Before Crossing: World Models for Off-Road Navigation

arXiv:2609.19863v1 Announce Type: cross Abstract: Navigation world models plan by foresight, predicting the future that each candidate action sequence produces and selecting the best, rather than mapp

Four-byline alert: 🚨 “.. People who have discussed the subject with Mr. Trump .. say his outbursts are rooted in worries that if the artifi…

Four-byline alert: 🚨 “.. People who have discussed the subject with Mr. Trump .. say his outbursts are rooted in worries that if the artificial intelligence boom .. slows down, the market could crash

From Rollout to Reset: A Graph-Based Harness for Autonomous Long-Horizon Manipulation Evaluation

arXiv:2609.19413v1 Announce Type: cross Abstract: Robot manipulation policies are improving quickly, and real-robot evaluation remains the standard evidence for that progress. It still relies on a hum

From Wizard-of-Oz Human-Robot Dialogue Collection to a Taxonomy of Robot Response Decisions: A Retrospective Analysis of Assistive Pilot Interactions

arXiv:2609.19447v1 Announce Type: new Abstract: Robots that follow natural-language instructions in everyday indoor environments must act on incomplete human utterances. Instructions often omit essent

GLAMDRING: Gait Learning And Morphology co-Design via Reinforcement LearnING of CPGs

arXiv:2609.19452v1 Announce Type: cross Abstract: Robots are moving out of the structured factory floor and into unstructured environments such as disaster sites, planetary surfaces, and agricultural

Governance-as-Code: Translating EU AI Act Technical Requirements into Executable Compliance Pipelines for Generative AI Systems

arXiv:2609.20016v1 Announce Type: cross Abstract: The EU AI Act (Regulation 2024/1689) imposes technical obligations on high-risk AI providers, yet Articles 8-15 were drafted for predictive AI and lea

GR2PO: Group Relative Return Policy Optimization for Continuous Robot Control

arXiv:2609.19850v1 Announce Type: new Abstract: Actor-critic architecture has been widely used in continuous robot control. However, they rely on learning a value network, introducing additional compu

Graph-Based Stochastic Power-UCT: Monte-Carlo Graph Search with Power Mean Estimation

arXiv:2609.19956v1 Announce Type: new Abstract: Tree-based Monte-Carlo Tree Search (MCTS) duplicates the same state when it is reached through different trajectories, which can waste simulations in st

HIL-UMI: Bringing Human-in-the-Loop Post-Training of Vision-Language-Action Models to Universal Manipulation Interface

arXiv:2609.20659v1 Announce Type: cross Abstract: Large-scale vision-language-action (VLA) models provide powerful priors for robot manipulation, yet adapting them to a specific deployment remains cha

How Do Agent Harnesses Create Value? Planning Information and Release Control in Stateful LLM Agents

arXiv:2609.20474v1 Announce Type: new Abstract: Agent harnesses supply planning guidance, organize execution, and check completion. We study how these components affect success, erroneous acceptance,

Hybrid Residual Reinforcement Learning for Contact-Rich Robotic Book Insertion

arXiv:2609.19962v1 Announce Type: new Abstract: Placing a grasped book into a tight shelf is a compact but difficult contact-rich control problem: millimetre-scale pose error can turn a geometrically

Improving Cross-embodiment Transfer in Latent Action Models with Action-Similarity Supervision

arXiv:2609.19846v1 Announce Type: cross Abstract: As generalist robot policies gain vision and language from web-scale pretraining, demonstrations remain costly to collect and tied to the robot that r

Improving Generalization and Robustness in Offline Reinforcement Learning via Boundary-Aware Data Augmentation

arXiv:2609.20300v1 Announce Type: new Abstract: Current offline reinforcement learning (ORL) algorithms tend to overfit the training dataset and exhibit poor in-distribution generalization and robustn

Improving Offline Goal-Conditioned Reinforcement Learning via Selective Reward Stimulation

arXiv:2609.19414v1 Announce Type: new Abstract: Goal-conditioned reinforcement learning aims to learn policies that reach specified goals, but remains challenging in offline settings with sparse rewar

Improving Online Reinforcement Learning via Bidirectional Behavior Prior Distillation

arXiv:2609.20268v1 Announce Type: new Abstract: Online reinforcement learning (RL) algorithms frequently exhibit poor sample efficiency and unstable learning dynamics, stemming from systematic critic

INSPECT: Learning Robot View Selection from Assistant Use

arXiv:2609.20615v1 Announce Type: cross Abstract: Robots inspecting an assembly must determine which parts are present and whether they are correctly installed. During egocentric assembly assistance,

It ain’t independent if you are partnering with them and chose the partner.

It ain’t independent if you are partnering with them and chose the partner. We’re partnering with Accenture on independent evaluation of frontier AI—part of our recent commitment to embed evaluators a

It is also possible that every oxygen atom in the room I'm in may migrate to a corner, thereby suffocating me. I think the major takeaway is…

It is also possible that every oxygen atom in the room I'm in may migrate to a corner, thereby suffocating me. I think the major takeaway is that @polynoamial is wasting his time on entirely foolish t

JointMatch: A Unified Heterogeneous Graph Neural Solver for Large-Scale Ride-Sharing Matching

arXiv:2609.20200v1 Announce Type: new Abstract: Ride-sharing platforms must continuously decide which open requests to bundle into shared trips and which idle vehicles should serve them. The dominant

Labeled Incidence Structures for Native Transformer Modeling of Text, Knowledge Graphs, and Hypergraphs

arXiv:2609.20278v1 Announce Type: cross Abstract: Text, knowledge graphs, and hypergraphs all have elements that play distinct roles within relation instances, structure that is lost when data is flat

LapaTrack-3D: 6 DoF pre-operative shape tracking for laparoscopic surgery

arXiv:2609.19954v1 Announce Type: cross Abstract: This work proposes a real-time 6 Degree-of-Freedom (6 DoF) tracking algorithm for monocular laparoscopic surgery. It provides alignment between intra-

Learning and Transferring Closed-Loop Robot Software

arXiv:2609.19906v1 Announce Type: cross Abstract: Closed-loop robot policies require observation processing, state management, and situation-dependent branching, making them costly to design and tune

Learning Foresight without Explicit Trajectories for 3D Diffusion Policies

arXiv:2609.20669v1 Announce Type: cross Abstract: 3D diffusion policies are strong at generating geometrically grounded actions from current observations, but successful manipulation requires not only

Learning Principal-Agent Contracts for Equitable Smallholder Carbon Farming under Moral Hazard and Adverse Selection

arXiv:2609.20404v1 Announce Type: new Abstract: Agricultural soils are a major untapped carbon sink. Carbon farming is emerging as a promising practice for tapping this potential. Smallholder farmers,

Learning Slope-Adaptive Whole-Body Locomotion for Humanoid Robots in Roofing Construction

arXiv:2609.20558v1 Announce Type: new Abstract: Roofing requires workers to coordinate locomotion, balance, and work-related body motions on pitched surfaces, creating a challenging application for hu

LIFD: Anchored Diffusion for 3D-Aware Scene Memory in Robotic Manipulation

arXiv:2609.19796v1 Announce Type: new Abstract: Robotic manipulation under partial observability requires spatial information that extends beyond the current view. Geometry-aware RGB features describe

LSTM-UT and Recurrent-Depth Transformers on Cellular Automata

arXiv:2609.19521v1 Announce Type: new Abstract: Recurrent-depth Transformers apply shared computation repeatedly, but differ in how they retain information across steps. We compare a Block Universal T