safety

EvolveTrade: Experience-Driven Policy Refinement for Self-Evolving LLM Trading Agents

arXiv:2609.17632v1 Announce Type: new Abstract: Large language model (LLM) trading agents can combine market data, news, and executable analysis, but their behavior is often controlled by static hand-

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Exponential Hardness of Off-Policy Evaluation under History-Dependent Logging

DGX agent

arXiv:2609.19135v1 Announce Type: new Abstract: Can a logged dataset visit every hidden state frequently and still be exponentially uninformative about a target policy's value? We show that it can whe

safetyarxiv-cs-lg

17 Sept 2026

FairCompressAgent: An Agentic Framework for Fairness-Aware Model Compression for FPGA Deployment

arXiv:2609.17786v1 Announce Type: new Abstract: Fairness-aware model compression requires selecting methods and configurations that balance accuracy, fairness, and deployment cost. These decisions bec

FairLRF: Achieving Fairness through Sparse Low Rank Factorization

arXiv:2511.16549v2 Announce Type: replace Abstract: As deep learning (DL) techniques become integral to various applications, ensuring model fairness while maintaining high performance has become incr

Faking Good and Faking Bad in LLMs: Response Distortion Across Dark Triad Personality Traits

arXiv:2609.17534v1 Announce Type: new Abstract: Social desirability and impression management are pervasive sources of response distortion in human personality assessment, yet their effects on Large L

FedGuide: Diffusion Prior Alignment and Value Baseline Guidance for Heterogeneous Federated Reinforcement Learning

arXiv:2609.18964v1 Announce Type: new Abstract: Federated Reinforcement Learning (FRL) enables collaborative policy learning across distributed agents with heterogeneous environments. While recent met

Feedback-Modulated Harmonic Policies for Quadruped Locomotion

arXiv:2609.17946v1 Announce Type: new Abstract: Learned quadruped locomotion policies commonly map observations directly to joint-level actions, leaving the periodic structure of locomotion implicit i

Fetch My Beer: Synthetic-to-real Hierarchical Policy for Smooth Pick-and-place

arXiv:2609.18119v1 Announce Type: new Abstract: Many real-world robotic applications require dynamically sensitive manipulation, where success depends not only on reaching a target state but on mainta

Flag Game: A Toy Model for Mechanistic Swarm Interpretability

arXiv:2609.19124v1 Announce Type: new Abstract: Emergent coordinated behaviors of AI agents are starting to present critical safety risks. A key phenomenon driving these behaviors is the rapid formati

ForceDelta-VLA: Distilling Force-Conditioned ActionCorrections for Contact-Rich Manipulation

arXiv:2609.18242v1 Announce Type: new Abstract: Force-aware Vision-Language-Action (VLA) policies improve contact-rich manipulation, but typically combine task-level motion and contact-dependent adjus

From a River in Gilead to the Inference Distributions of Large Language Models: Covert Dialect Bias and Linguistic Profiling at Scale

arXiv:2609.18068v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains such as housing screening. While alignment techniques mitigate explicit

Function-Preserving Data Generation for Zero-Shot Real-to-Sim-to-Real Manipulation

arXiv:2609.18293v1 Announce Type: new Abstract: Robotic data generation is a promising paradigm for scaling robot learning without collecting large-scale real-world data. However, generating geometric

Future of general LLM work (interp/inference/alignment) vs agentic/physical AI (VLA, multimodal) for career [D]

I'm at a crossroads with two grad school options that would take me in somewhat different research directions, and I wanted some general advice on these fields, their growth, and industry alignment. I

safetyr-machinelearning

G-Mamba: Sparse Graph-Guided Mamba for Audio-Visual Speech Enhancement

arXiv:2609.18009v1 Announce Type: cross Abstract: Lightweight audio-visual speech enhancement (AVSE) models face a critical trade-off between computational efficiency and cross-modal alignment accurac

@GaryMarcus @0xkkai The current AI agency architecture based on looping on an LLM core by piling on the same LLM context is a deeply flawed …

Romeo Lupascu has criticized the prevailing AI agency framework, which relies on repeatedly looping an LLM core with identical context. He calls this strategy “deeply flawed” and argues that it should

safetygary-marcus--x

Gated Residual Body-Hand Coordination for Whole-Body Humanoid Teleoperation

arXiv:2609.18763v1 Announce Type: new Abstract: Whole-body humanoid teleoperation commonly combines a motion-tracking policy with a separate dexterous-hand retargeter. However, independently generated

Gradient Descent with Stochastic Subspaces via Persistence of Memory

arXiv:2609.18416v1 Announce Type: cross Abstract: Stochastic subspace methods have gained popularity as gradient descent based techniques for large scale optimisation problems, especially in distribut

Hardware-Free Robotics Laboratories in Mixed Reality

arXiv:2609.18434v1 Announce Type: new Abstract: Teaching robotics relies on screen-based simulation, showing robot motion in an abstract coordinate frame rather than at real scale in the learner's own

How Calibration Content Shapes Attention-Based Reranking

arXiv:2609.17764v1 Announce Type: new Abstract: Attention-based rerankers score documents by aggregating query-to-document attention and subtracting a null-query calibration pass to remove positional

How Dario Amodei's essays on AI safety and ethics help explain some AI fears; his regulatory stance evolved from wariness in January to embracing safety reviews (David Streitfeld/New York Times)

David Streitfeld / New York Times: How Dario Amodei's essays on AI safety and ethics help explain some AI fears; his regulatory stance evolved from wariness in January to embracing safety reviews — Da

safetytechmeme

How Many Labels Does Model Choice Need? Certificates and Budgets for Selective Prediction

arXiv:2609.18622v1 Announce Type: new Abstract: Classifiers can make identical predictions yet require labels to compare their selective performance: confidence ranks weight the same errors differentl

“HUMANZS LAUNCHED THE JOB” Ok, I don’t like the spelling here, but the gist of this Mozilla cybersecurity researcher rings true. The six new…

“HUMANZS LAUNCHED THE JOB” Ok, I don’t like the spelling here, but the gist of this Mozilla cybersecurity researcher rings true. The six new incidents aren’t about the second coming of Skynet, they ar

safetygary-marcus--x

In-Context Robot Learning with VLM Agents

arXiv:2609.19138v1 Announce Type: cross Abstract: Enabling robots to adapt to unfamiliar environments as readily as humans remains a moonshot goal of embodied AI. No finite collection of demonstration

Indicators of resilience for autonomous control systems

arXiv:2609.18264v1 Announce Type: cross Abstract: As modern societies rely more on autonomous systems to facilitate daily life, assuring their safe operation is paramount. Naturally, there are many te

Inside the suddenly explosive world of AI safety

On a sunny July day in Berkeley, California, the country's top AI safety researchers gathered on an unmarked floor of an unmarked building. They had come together for a 'war room' to dissect the high-

safetythe-verge-ai

King Charles III hosts tech leaders, including Jensen Huang, Demis Hassabis, and OpenAI CFO Sarah Friar, to discuss AI risks; Huang calls for AI safety tests (Bloomberg)

Bloomberg: King Charles III hosts tech leaders, including Jensen Huang, Demis Hassabis, and OpenAI CFO Sarah Friar, to discuss AI risks; Huang calls for AI safety tests — Titans of the artificial inte

safetytechmeme

KINO: A Keyframe Interface for VLM Planning and Whole-Body Control in Humanoid Loco-Manipulation

arXiv:2609.18869v1 Announce Type: new Abstract: Humanoid loco-manipulation requires robots to interpret task instructions and scene semantics while executing coordinated whole-body motions. We propose

Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation

arXiv:2412.07255v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate remarkable capabilities in generative tasks but pose potential risks due to their tendency to generat

Large Language Models Versus Physicians in Traditional Chinese Medicine: A Real-World Clinical Case Evaluation

arXiv:2609.17544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical applications, yet their assessment for real-world traditional Chinese medicine

Learning Heterogeneous Preferences

arXiv:2609.17847v1 Announce Type: new Abstract: Learning from human feedback has become a central paradigm for training modern AI systems, where models of human utility are used as reward models in po

Learning Holistic Whole-Body Loco-Manipulation with a Bipedal Mobile Manipulator

arXiv:2609.18930v1 Announce Type: new Abstract: Bipedal loco-manipulation enables robots to interact with objects beyond the nominal workspace of their arms by coordinating locomotion and manipulation

Learning Magnetic Order Classification from Large-Scale Materials Databases

arXiv:2509.05909v3 Announce Type: replace-cross Abstract: The reliable identification of magnetic ground states remains a major challenge in high-throughput materials databases, where density function

Learning to Stack: Cube-Stacking Imitation Learning from Virtual Reality Demonstrations

arXiv:2609.19040v1 Announce Type: new Abstract: Imitation learning is attractive for robot manipulation, but collecting demonstrations remains a bottleneck for multi-stage tasks requiring repeated sce

Lexara-RF: Reference-Free Metrics for Evaluating Conversational Visual Analytics Agents

arXiv:2609.17842v1 Announce Type: cross Abstract: Conversational visual analytics (CVA) agents powered by large language models generate visualizations and natural-language explanations from open-ende

Look Less, Hear Better: Jointly Rewarded GRPO for Streaming ASR

arXiv:2609.18333v1 Announce Type: cross Abstract: Streaming automatic speech recognition (ASR) must be judged jointly on what it transcribes and on how quickly it commits each word. Delayed streams mo

{M}^2Tok: Multi-head Multi-codebook Discrete Action Tokenization for Vision-Language-Action Models

arXiv:2609.18259v1 Announce Type: cross Abstract: Recent advancements have successfully adapted autoregressive language models to process multimodal signals, such as images and actions. Since raw acti

Machine Translation between English and Syriac (East Syriac Dialect) using Statistical Machine Learning

arXiv:2609.18529v1 Announce Type: new Abstract: UNESCO considers the Assyrian (Syriac) language an endangered language. Although Assyrians speak the language worldwide, the speaking population is unce

METALICA: METAdynamics and repLICA exchange for enhanced diffusion sampling

arXiv:2609.17823v1 Announce Type: cross Abstract: Many proteins function through transitions between conformational states, yet rare states are rarely sampled by diffusion models trained on an equilib

Microsoft AI CEO says AI threats are real, and Anthropic is making it worse

Today, I’m talking with Mustafa Suleyman, the CEO of Microsoft AI. As you’re no doubt aware, the biggest story in tech right now is the spiraling debate about AI safety and regulation. It should come

safetythe-verge-ai

Missing Bridges: Composition-Aware Active Imitation Learning

arXiv:2609.18004v1 Announce Type: new Abstract: Active imitation learning reduces expert effort by allowing a learner to request the demonstrations it needs. Existing methods typically select these re

Mixed-Integer Nonlinear Differentiable Predictive Control for Underground Pumped Hydro Energy Storage Systems

arXiv:2609.17964v1 Announce Type: cross Abstract: This paper extends Mixed-Integer Differentiable Predictive Control (MI-DPC) to multi-modal discrete decisions and nonconvex polynomial dynamics arisin

Multi-Session Multimodal Underwater Mapping with Acoustic and Optical Imaging

arXiv:2609.17929v1 Announce Type: new Abstract: Accurate seafloor mapping is essential for marine science, archaeology, and environmental monitoring. However, integrating data from different sensors,

Multitask Reinforcement Learning for Assisting Choice Model Specification

arXiv:2609.18441v1 Announce Type: cross Abstract: Discrete choice model specification is a time-consuming task in which modellers often specify and estimate multiple models while balancing goodness-of

new unredacted filings in the publishers (including my employer) vs OpenAI and Microsoft lawsuit Microsoft's Director of applied science cal…

new unredacted filings in the publishers (including my employer) vs OpenAI and Microsoft lawsuit Microsoft's Director of applied science calls LLM training 'an astonishing theft of unprecedented propo

safetygary-marcus--x

Newer Is Not Fairer: Gender Stereotyping in Text-to-Image AI Across Model Generations

arXiv:2609.18007v1 Announce Type: cross Abstract: Text-to-image generative models are widely used in professional and creative settings, yet how they represent gender across occupations -- and whether

NormLift: From Lifted Features To Semantic Reliability In 3D Gaussian Splatting

arXiv:2609.18898v1 Announce Type: new Abstract: Training-free weighted aggregation is widely used to lift 2D semantic features onto 3D Gaussians for open-vocabulary scene understanding, yet its theore

safetyarxiv-cs-cv

NYT court filing: ChatGPT's head wrote that publishers face an 'existential threat' and a Microsoft executive called AI training 'an astonishing theft' (Financial Times)

Financial Times: NYT court filing: ChatGPT's head wrote that publishers face an “existential threat” and a Microsoft executive called AI training “an astonishing theft” — Lawyers say AI co-founder Gre

safetytechmeme

OpenDexGrasp: Open-vocabulary Task-Oriented Dexterous Grasping

arXiv:2609.18117v1 Announce Type: new Abstract: Dexterous grasp synthesis has advanced rapidly in generating stable and physically plausible hand poses, but real-world manipulation requires grasps tha