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Hierarchical and Permutation-Invariant Feature Transformation Learning via Policy-Guided Embedding Search

arXiv:2609.10225v1 Announce Type: new Abstract: Feature transformation improves predictive performance on tabular data by constructing informative abstractions from raw features. Recent generative app

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How Fragile Is Safety Alignment at Frontier Scale? A Single-Direction Attack on a 320B MoE

DGX agent

arXiv:2609.09793v1 Announce Type: cross Abstract: Directional ablation removes an aligned language model's ability to refuse by projecting a single 'refusal direction' out of the weights that write th

safetyarxiv-cs-cl

10 Sept 2026

Human-agent discovery of reconfigurable in-plane ferroelectric superdomain control

arXiv:2609.06887v1 Announce Type: cross Abstract: Automated experimentation is most effective when the observables, available actions, and objective are defined before the experiment starts, as is the

// human-values.pseudo | ARTIFACT 0.1.0-experimental.1 | BASE 1.2.0-rc1 | EDITION ai-compact | NARRATOR System_Synthesis_Node_01 | PROVENANC…

safetyyohei-nakajima--x

iBrain: A Unified Foundation Model Reading the Brain from Surface to Spikes

arXiv:2609.06960v1 Announce Type: new Abstract: Invasive neural recordings provide high-fidelity measurements of brain activity, with signals such as intracranial EEG (iEEG) and intracortical spiking

I'm no one special. But after the mathematicians and OpenAI debacle I've decided to cancel all of my cloud AI subscriptions. I know that's r…

I'm no one special. But after the mathematicians and OpenAI debacle I've decided to cancel all of my cloud AI subscriptions. I know that's radical and crazy by today's standards...as of five minutes a

Improving Cross-Lingual Token Representations by Adding a Pinch of SALT

arXiv:2609.09953v1 Announce Type: new Abstract: Cross-lingual sentence encoders enable scalable transfer across hundreds of languages, powering applications such as translation mining and zero-shot le

Incredible how people are making up different numbers of weeks/months for how long Coxon worked at Anthropic to assassinate his character. T…

Incredible how people are making up different numbers of weeks/months for how long Coxon worked at Anthropic to assassinate his character. The only credible source (@MadisonMills22 @axios who spoke wi

InstantMimic: A High Performance System for Learning Physics-based Skills in Seconds

arXiv:2609.09821v1 Announce Type: cross Abstract: Physics-based character control is a long-standing challenge in computer graphics and robotics, requiring policies that satisfy complex dynamics while

Intent Drift at SME Scale: Deployment Practice, Not Model Capability, Determines Agentic Compliance

arXiv:2609.05975v1 Announce Type: cross Abstract: We introduce Chain of Intent, a governance framework for agentic AI at small regulated firms, and validate it against a failure it was built to addres

Isotropic Embedding Perturbations for Robust Vision Language Encoders

arXiv:2609.10292v1 Announce Type: new Abstract: Data augmentation is fundamental to training modern deep vision and multimodal models. While individual methods, such as RandAug, CutMix, Mixup, RandEra

It's time to call these end-of-the-world anti-AI messaging groups exactly what they are: Terror cells - They funnel and wash money from a fe…

It's time to call these end-of-the-world anti-AI messaging groups exactly what they are: Terror cells - They funnel and wash money from a few donors to smaller groups to obscure origin - insert sleepe

safetyyann-lecun--x

Jacob was a senior researcher who joined Anthropic in May. My Anthropic colleagues and I had been trying to recruit him for ~2 years, becaus…

Jacob was a senior researcher who joined Anthropic in May. My Anthropic colleagues and I had been trying to recruit him for ~2 years, because we knew he was a strong researcher at OpenAI. Before he le

JEPA Policy: Diffusion-Free Imitation Learning via Paired Action and Future Representation Prediction

arXiv:2609.09630v1 Announce Type: new Abstract: Standard behavior cloning supervises actions without explicitly constraining the future representation paired with each demonstrated action chunk. We in

Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation

arXiv:2508.05427v2 Announce Type: replace Abstract: Large language models (LLMs) are beginning to reshape how organic-synthesis workflows are represented, queried, planned, and connected to experiment

Learning Terrain-Adaptive Humanoid Locomotion on Granular Terrain

arXiv:2609.10286v1 Announce Type: new Abstract: Humanoid locomotion on granular terrain remains a significant challenge due to its complex foot-terrain interaction dynamics that are difficult to model

Learning to Adapt and Calibrate: Score Distribution Alignment for Few-Shot Uncertainty Prediction in Medical VLMs

arXiv:2609.10333v1 Announce Type: new Abstract: Uncertainty estimation for medical vision--language models (VLMs) using conformal prediction has gained increasing attention due to its distribution-fre

Learning to Fly: Stable Vision-Guided UAV Servoing with Compact Target-Centric Cues and Reinforcement Learning

arXiv:2609.09234v1 Announce Type: cross Abstract: Vision-guided reinforcement learning for Unmanned Aerial Vehicles (UAVs) remains challenging due to unstable policy optimisation, aggressive explorati

Learning with Synthetic Data via SGD in High-Dimensional Linear Regression

arXiv:2609.09572v1 Announce Type: cross Abstract: Synthetic data has become a promising way to scale model training beyond limited human-generated data but it may also induce strong model collapse (Do

Literati: Towards Anytime Optimal Shape Generalized Trees via AO*

arXiv:2609.09299v1 Announce Type: new Abstract: Decision trees are prized for their interpretability and strong performance on tabular data, but popular greedy top-down induction algorithms can yield

LLM-Generated or Human-Written? Comparing Review and Non-Review Papers on ArXiv

arXiv:2601.17036v2 Announce Type: replace-cross Abstract: ArXiv recently prohibited the upload of unpublished review papers to its servers in the Computer Science domain, citing a high prevalence of L

Manifold-Aligned Generative Transport

arXiv:2602.19600v2 Announce Type: replace-cross Abstract: Many high-dimensional datasets concentrate near a low-dimensional structure embedded in the ambient space. Generative models for such data mus

Mapping the Emerging Social Science of Large Language Models

arXiv:2609.07598v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these d

May, damn it, not six weeks. Senior, not entry level.

May, damn it, not six weeks. Senior, not entry level. Jacob was a senior researcher who joined Anthropic in May. My Anthropic colleagues and I had been trying to recruit him for ~2 years, because we k

Meta-LinEXP3: Online-within-Online Learning for Adversarial Linear Contextual Bandits

arXiv:2609.09907v1 Announce Type: new Abstract: Meta-learning has emerged as an effective paradigm for transferring knowledge across sequential bandit tasks. While substantial progress has been made f

Mini-Batch Risk-Averse Deep Q-Learning: A Robot Navigation Case Study

arXiv:2609.07998v1 Announce Type: new Abstract: We study the control of Markov decision processes in which the quality of a policy is evaluated by a dynamic, time-consistent Markov risk measure rather

Multi-Agent Reinforcement Learning for Autonomous UAV Exploration in Wildfire Response

arXiv:2609.10433v1 Announce Type: cross Abstract: This study develops a deep reinforcement learning framework for training Unmanned Aerial Vehicle (UAV) agents to navigate and monitor simulated wildfi

Multi-dimensional Preference Alignment by Conditioning Reward Itself

arXiv:2512.10237v2 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback has emerged as a standard for aligning diffusion models. However, we identify a fundamental limitation in

Networked Admissibility-Preserving Control for Directed Safe Coordination

arXiv:2609.09384v1 Announce Type: cross Abstract: This paper addresses safety-critical coordination for scalar agents whose distributed commands are implemented through constrained physical-input dyna

No Free Checker: A Survey of Verifiers for Robot Policies

arXiv:2609.09250v1 Announce Type: cross Abstract: A verifier for robot policies reads a candidate behavior and returns a score for how well it did, used both to evaluate vision-language-action policie

Noesis: Deterministic-First Retrieval with Two-Tier Context Hydration for Factuality-Critical Queries on Small Local Models

arXiv:2609.07663v1 Announce Type: cross Abstract: A wrong number is worse than no answer. Across factuality-critical domains -- audience metrics, scheduling and rights in media; dosages and lab values

not counting Sam himself who is frequently in DC

not counting Sam himself who is frequently in DC OpenAI employs FIVE lobbying firms and has over 100 staffers in their Washington, DC office. They must push for AI legislation to justify their existen

Odometer-Agnostic Drift Correction Using OpenStreetMap Lane Geometry

arXiv:2609.10336v1 Announce Type: new Abstract: Despite significant progress in odometry estimation, long-term drift remains a fundamental limitation of incremental pose integration, especially in lar

On-Policy Distillation for Vision-Language Model Adaptation, an Effective Paradigm on Low-Quality Multimodal Data

arXiv:2609.10321v1 Announce Type: new Abstract: Knowledge distillation offers an efficient route to transfer a task-adapted vision-language teacher to a compact student. The training target in current

OpenAI Foundation board member Paul Christiano says the AI industry is currently not on track to reduce the acute loss-of-control risk to an 'acceptable' level (Paul Christiano/@paulfchristiano)

Paul Christiano / @paulfchristiano: OpenAI Foundation board member Paul Christiano says the AI industry is currently not on track to reduce the acute loss-of-control risk to an “acceptable” level — I

safetytechmeme

OpenAI hid the details of the wiki incident from the investigators of the later HuggingFace hack. When caught, they responded only with corp…

OpenAI hid the details of the wiki incident from the investigators of the later HuggingFace hack. When caught, they responded only with corporate BS. This cover-up of unprecedentedly misaligned behavi

Optimal Value Inference for Reinforcement Learning

arXiv:2609.09981v1 Announce Type: cross Abstract: We study offline inference for the optimal value in reinforcement learning. Two new nuisances are derived as fixed points of a self-induced Bellman eq

Personalized Execution Time Optimization for Billion-Scale Scheduled Jobs

arXiv:2203.06158v3 Announce Type: replace Abstract: Scheduled batch jobs are widely used on asynchronous computing platforms to execute enterprise applications such as promotional notifications and ca

Politics of Feelings: Emotional Expression and Legislative Effectiveness in the U.S. Congress

arXiv:2609.10198v1 Announce Type: new Abstract: Emotions are a pervasive feature of political communication, yet existing research has focused primarily on describing patterns of emotional expression

PopResume: Causal Fairness Evaluation of LLM/VLM Resume Screeners with Population-Representative Dataset

arXiv:2603.22714v2 Announce Type: replace-cross Abstract: We present PopResume, a population-representative resume dataset for causal fairness auditing of LLM- and VLM-based resume screening systems.

PRIMUS: Identity, Governance, and Verification for Multi-Agent Federations

arXiv:2609.07910v1 Announce Type: new Abstract: Multi-agent federations need governance that answers three questions under adversarial conditions: who participated (identity), did they conform (enforc

Q&A with AI researcher Jacob Coxon, who quit Anthropic, on the need for industry-wide, international coordination to limit recursive self-improvement, and more (Maxwell Zeff/Wired)

Maxwell Zeff / Wired: Q&A with AI researcher Jacob Coxon, who quit Anthropic, on the need for industry-wide, international coordination to limit recursive self-improvement, and more — Jacob Coxon talk

safetytechmeme

Quantization Amplifies Determinism, Not Bias: Scale-Dependent Behavioral Effects of Serving-Time Weight Compression

arXiv:2609.07901v1 Announce Type: new Abstract: Weight quantization largely determines the economics of serving open-weight LLMs. Its costs are usually assessed with capability benchmarks, on which 4-

Revoked but Still Authoritative: An Empirical Study of Revocation Enforcement in Agent-Memory Systems

arXiv:2609.08258v1 Announce Type: new Abstract: Long-running language-model agents depend on persistent memory. Many agent-memory systems preserve history through soft revocation: a contradicted fact

RoboDrop: Curating VLA Post-Training Data via Local Gradient Compatibility

arXiv:2609.10021v1 Announce Type: new Abstract: Vision--language--action (VLA) models acquire broad generalization through large-scale pretraining, yet adapting them to a new task and robot embodiment

Same Values, Different Languages? From Multilingual Probing to Steering LLMs Toward Chinese Social Values

arXiv:2609.08515v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into human society, aligning them with pluralistic social values has become a critical pri

Silent Revision: Measuring Undisclosed Change in the Safety Frameworks of Frontier AI Developers

arXiv:2609.08789v1 Announce Type: cross Abstract: Frontier AI developers publish safety frameworks that commit them to evidencing whether their models are dangerous. The European Union and California

SkillAlign: Aligning Skill Interfaces for LLM-based Agents

arXiv:2609.07255v1 Announce Type: new Abstract: Language-model agents increasingly rely on skills: reusable procedural knowledge for reasoning, tool use, and interaction. Existing work studies how ski