Search: “safety”

Anatomy-aware cross-speaker adaptation of complete vocal-tract acoustic-to-articulatory inversion

arXiv:2609.29766v1 Announce Type: cross Abstract: Cross-speaker acoustic-to-articulatory inversion requires accounting for anatomical differences between speakers. We propose a geometric adaptation fr

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Auditability Is Not One Property: Rule Overlap, Behavioural Agreement, and Composition in Reinforcement Learning

DGX agent

arXiv:2609.28581v1 Announce Type: cross Abstract: Reinforcement-learning (RL) policies are often distributed as opaque neural checkpoints, while training logs show that a run occurred without explaini

safetyarxiv-cs-ai

25 Sept 2026

Augur: A Synthetic Decision Lab for Rehearsing Reactions to Product and Policy Changes

arXiv:2609.29952v1 Announce Type: new Abstract: Before a product or policy change ships, the question that matters is how people will react to it. Augur rehearses that reaction offline: it builds a ty

AV-GRPO: Modality-Anchored Decoupling Diffusion Reinforcement Learning for Joint Audio-Video Generation

arXiv:2609.29816v1 Announce Type: new Abstract: Recent years have witnessed major progress in joint audio-video generation. Existing models still suffer from limited per-modality fidelity, insufficien

Back to the Definition: Estimating Step-Level Advantages via Trajectory Graphs for Agentic Reinforcement Learning

arXiv:2609.28963v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) methods, such as GRPO and its variants, have become a leading paradigm for training reasoning and agentic large

BaseCamp --- An Agentic AI Framework for Automating DNA Sequencing Data Pipelines

arXiv:2609.28557v1 Announce Type: new Abstract: DNA sequencing pipelines, spanning quality control, alignment, variant calling, and annotation, are now reliably executed by workflow management systems

CALM: Current Aligned Link Manipulation for Single Arm Oversized Object Lifting

arXiv:2609.29017v1 Announce Type: new Abstract: Most robots manipulate objects solely with their end effectors, whereas humans flexibly leverage different body parts, such as the forearm and elbow, es

CARE: Condition-Aware Representation Regularization for Diffusion Models

arXiv:2609.28561v1 Announce Type: cross Abstract: Recent advances in diffusion models highlight the importance of representation regularization for improving sample quality and training efficiency. Ho

CataOPD: Catalytic On-Policy Distillation for Large Language Model Reasoning

arXiv:2609.29518v1 Announce Type: new Abstract: Reinforcement learning (RL) and on-policy distillation (OPD) are two representative paradigms for improving large language model reasoning. However, whe

CATCH: Counterfactual Anatomical Tissue Inpainting with Conditional Haar Diffusion

arXiv:2609.29591v1 Announce Type: cross Abstract: BraTS local synthesis replaces masked regions in T1-weighted brain MRI with plausible tumor-free tissue while preserving observed anatomy. We present

Conversational DNA: A Visual Language and Interactive Atlas of Human and AI Dialogue

arXiv:2508.07520v2 Announce Type: replace-cross Abstract: What makes a conversation hold together when its participants speak across one another? Topic maps offer one view, but they leave the relation

Coordinate-Independent Robot Model Identification

arXiv:2603.14656v2 Announce Type: replace Abstract: Robot model identification is commonly performed by least-squares regression on inverse dynamics, but existing formulations measure residuals direct

CounterRoute: Self-Routed Reasoning via Hierarchical Counterfactual Credit Assignment

arXiv:2609.29109v1 Announce Type: new Abstract: Reasoning-capable language models often produce long chains of thought when direct answers suffice, wasting inference compute. Many dual-mode models lea

Coupled State-Space Modelling, Control, and Policy Distillation for Hybrid Rigid-Pneumatic Manipulators

arXiv:2609.29424v1 Announce Type: new Abstract: Hybrid manipulators combine motorized rigid joints with pressure-actuated origami segments. Published arms of this kind are controlled with decoupled pe

CrossScale-GLIO: Topology-Preserving Vision-Language Alignment of MRI and Whole-Slide Histopathology for Diffuse Glioma

arXiv:2609.28524v1 Announce Type: cross Abstract: Magnetic resonance imaging and histopathology observe the same glioma at radically different scales. We present CrossScale-GLIO, a visual multimodal f

DAWN: Noise-Robust Quadruped Parkour via Depth-Denoising World Models

arXiv:2609.29092v1 Announce Type: cross Abstract: Vision-based legged locomotion methods assume clean depth at training time and rely on hand-tuned post-processing filters at deployment. However, filt

DCRMTA: Deep Causal Representation Learning for Multi-Touch Attribution

arXiv:2401.08875v3 Announce Type: replace-cross Abstract: Multi-touch attribution (MTA) is essential for estimating the contribution of individual advertising touchpoints to user conversions. While re

Decoupled Early Exits for Task-Dependent Compute Allocation in Flow-Matching VLAs

arXiv:2609.29382v1 Announce Type: cross Abstract: Flow-matching Vision-Language-Action (VLA) models have emerged as a potential solution for generalist robot control, designed by combining a pretraine

Do World Models Make Better Robots? A Survey of Evaluation Benchmarks for Predictive Embodied Intelligence

arXiv:2609.29669v1 Announce Type: cross Abstract: Robot learning now advances along two tracks that rarely meet. On one side, direct Vision-Language-Action (VLA) policies map observations to actions a

Domain Recentering and Confidence-Weighted Prior Calibration for Vision-Language Models

arXiv:2609.29358v1 Announce Type: cross Abstract: Vision-language models such as CLIP achieve strong zero-shot classification, yet under distribution shift, visual embeddings drift from fixed text emb

Downside-Controlled Online Forecast Combination under Delayed and Revised Outcomes

arXiv:2609.29096v1 Announce Type: new Abstract: Post-hoc correction adjusts a forecaster that cannot be retrained, such as a foundation model, but a correction fitted where errors are stable can hurt

ELF-REG: Scaling Continuous Diffusion Language Models to Reasoning Tasks

arXiv:2609.29102v1 Announce Type: new Abstract: Fully continuous diffusion language models (dLMs) denoise continuous representations without intermediate discretization, then decode all response token

safetyarxiv-cs-cl

ERRAND: Budgeted Maintenance of Agent Memory

arXiv:2609.29545v1 Announce Type: new Abstract: Deployed agents run on handed-over knowledge: a frozen policy consults a briefing of consolidated items written before the stream begins. The world then

Evaluation of Multi-Turn Consistency in LLM Agents: Survival Analysis and Failure-Rationale Taxonomy

arXiv:2609.29508v1 Announce Type: new Abstract: Large language model (LLM) agents may perform well on isolated tasks yet drift into inconsistency over extended interaction. We evaluate temporal consis

Fair Like Us? Auditing LLM Alignment in Resource Allocation

arXiv:2609.29692v1 Announce Type: new Abstract: Fair allocation of scarce, indivisible resources is an important challenge in many societal problems. While there are several formal theories of fairnes

Faster Visuomotor Policy Learning on Action Manifolds via Riemannian MeanFlow

arXiv:2609.30127v1 Announce Type: new Abstract: Visuomotor policies learn a direct map from raw sensory observations to robot action sequences. Policies based on Diffusion and Flow Matching capture th

FluidRain: Incompressible Rain Flow as an Attention Bias for Loop-in-Loop Video Deraining

arXiv:2609.29006v1 Announce Type: new Abstract: Existing video deraining methods typically exploit neighboring frames through either explicit alignment or implicit spatiotemporal aggregation. Explicit

Foundations of Large Language Models

arXiv:2501.09223v3 Announce Type: replace-cross Abstract: This is a book about large language models. As indicated by the title, it primarily focuses on foundational concepts rather than comprehensive

From Interests to Semantic IDs: Retrieval-Grounded Credit Assignment for Generative Recommendation

arXiv:2609.29983v1 Announce Type: cross Abstract: Semantic IDs (SIDs) encode each catalog item as a short token sequence, enabling generative recommenders to predict the next item autoregressively. Re

From Policy Documents to Structured Survey Responses: Evaluating Large Language Models for Policy Monitoring

arXiv:2609.29370v1 Announce Type: cross Abstract: Science, technology, and innovation policies are crucial for competitiveness, yet their diversity and scale make them difficult to map and monitor con

From Self-Distillation to Self-Practice: Privileged Information for Multi-Turn Agents

arXiv:2609.29051v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has become a popular recipe for post-training LLM agents. It supervises the agent model at the token level with a str

From Static Personal Values to Contextualized Personalization: Bayesian Personalized Value Alignment for LLMs

arXiv:2609.28942v1 Announce Type: new Abstract: Personalized value alignment has become increasingly important as large language models (LLMs) are expected to accommodate diverse user preferences. How

From Target Selection to Digging: A Learning-Based Framework for Continuous Autonomous Excavation

arXiv:2609.29750v1 Announce Type: new Abstract: Repeated excavation continuously reshapes pile geometry, requiring an autonomous excavator to adapt its digging targets and coordinate motion across suc

Graph, Loop, and Harness Engineering for Zero-Trust Agentic Data Engineering and Analytical Processing

arXiv:2609.29668v1 Announce Type: cross Abstract: Large language model agents increasingly automate data workflows, but end-to-end cloud data engineering and analytical execution require reliable coor

Hard Stop: Kernel-Level Preemption and Containment for Rogue Agentic Execution

arXiv:2609.29808v1 Announce Type: cross Abstract: In July 2026, an unconstrained autonomous agent participating in a frontier AI cybersecurity evaluation harness breached its evaluation sandbox, estab

HarnessPAI: An Evolving Harness for Physical AI

arXiv:2609.29166v1 Announce Type: cross Abstract: Physical AI aims to build embodied agents that perceive the world, understand and reason about it, and decide how to act. Yet the field has focused pr

Human-AI-Powered Hypothesis Testing: Cost-Aware Selective AI Scoring and Sequential Human Escalation

arXiv:2609.28859v1 Announce Type: new Abstract: Large language models are increasingly used as inexpensive judges to evaluate outputs, label data, and assess whether a system meets a desired quality s

Implicit Behavior Coordination from Sub-Task Demonstrations by Exploiting Overlap-Induced Multimodality

arXiv:2607.09234v2 Announce Type: replace Abstract: Long-horizon robotic rearrangement is commonly formulated as a skill-sequencing problem, where distinct behaviors are explicitly represented and coo

Intrinsic-Extrinsic Coupling in Learning Dynamics

arXiv:2609.30185v1 Announce Type: new Abstract: A learner's current observations need not determine its response to further training. We formulate intrinsic-extrinsic coupling through the continuation

Is Reasoning Always Useful? Rethinking Reasoning Utility in Universal Multimodal Embeddings

arXiv:2609.29560v1 Announce Type: new Abstract: Reasoning-enhanced universal multimodal embeddings (UME) improve heterogeneous retrieval, but plausible rationales do not necessarily produce discrimina

IterSynth: Rethinking Deep Search Agents via Role-Decoupled Iterative Synthesis

arXiv:2609.29444v1 Announce Type: cross Abstract: Deep search requires LLM agents to decompose complex queries, search for evidence, and synthesize grounded answers, yet existing ReAct-style agents su

it’s a shame to see someone like @NateSilver538 does not understand a basic, fundamental technical distinction. (@tristanharris and Kevin Ro…

it’s a shame to see someone like @NateSilver538 does not understand a basic, fundamental technical distinction. (@tristanharris and Kevin Roose missed it the other day, too.) pure LLMs were (very roug

safetygary-marcus--x

It's the Geometry, Not the Model: Effective Rank and Subspace Alignment in Functional Connectivity Classification

arXiv:2609.29932v1 Announce Type: cross Abstract: Resting-state functional connectivity (FC) is widely used to classify brain phenotypes and disorders. Most pipelines use the full connectome and seek

LastOPD: Taming Collapse in Latent On-Policy Distillation

arXiv:2609.28845v1 Announce Type: cross Abstract: On-policy distillation (OPD) corrects a student on the responses it writes, but its signal is the teacher's next-token distribution: it tells the stud

safetyarxiv-cs-cl

Learning a Flow to Self-Supervised Representations

arXiv:2609.29350v1 Announce Type: new Abstract: Explicit geometric references offer a direct way to structure self-supervised representations. Existing adversarial distribution-matching formulations,

Learning Better Reasoning for Generative Recommendation with Semantic IDs

arXiv:2609.29973v1 Announce Type: cross Abstract: Generative recommendation reformulates item retrieval as sequence generation, allowing a unified model to directly generate the next item from a user'

Learning Causal Structure of Time Series using Best Order Score Search

arXiv:2603.05370v2 Announce Type: replace-cross Abstract: Causal structure learning from observational data is central to many scientific and policy domains, but the time series setting common to many

Learning from Mixed-Quality Deployment Experience for Robot Manipulation

arXiv:2609.29000v1 Announce Type: new Abstract: Robot policies deployed in real environments naturally accumulate mixed-quality experience, including successful executions, partial progress, and failu