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Staying on Task: Testing the Foundations of Long-Horizon Agent Reliability

arXiv:2609.38712v1 Announce Type: new Abstract: Long-horizon agentic workflows require models to sustain repeated state-dependent actions all while the context grows, sub-task complexity changes, and

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Steepest Guidance: A Practical and Principled Approach to Inference-Time Alignment of Flow and Diffusion-based Models

DGX agent

arXiv:2609.39091v1 Announce Type: cross Abstract: Inference-time alignment of flow and diffusion-based models is critical for achieving flexible generative modeling. Theoretically, Doob's h-transform

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1 Oct 2026

Stress-Testing LLM Lie Detectors: Role-Play Failures and Spurious Correlations

arXiv:2609.39807v1 Announce Type: cross Abstract: Lie detection probes aim to predict from a language model's internal states whether its output is truthful or dishonest. However, role-play complicate

Strike a Chord! Modal Kinetic Typography

arXiv:2609.38325v1 Announce Type: new Abstract: We introduce modal kinetic typography, which animates a vector glyph to express a semantic concept while keeping it legible. Our key idea is to build mo

TERRA: Terrain-Aware Reconstruction, Retargeting and Control for Musculoskeletal Locomotion

arXiv:2609.38653v1 Announce Type: cross Abstract: Recent advances in musculoskeletal modeling and reinforcement learning have enabled muscle-actuated agents to reproduce increasingly complex human mot

Text-to-3D Policy: Fine-Grained Language-Behavior Alignment for Unseen Specification Generalization

arXiv:2609.39599v1 Announce Type: cross Abstract: 3D visuomotor policies provide a strong foundation for spatially precise manipulation, yet current text-to-3D policies struggle to follow unseen fine-

The Missing Coefficients: Bayesian Pairwise Merging for Model Personalization

arXiv:2609.39055v1 Announce Type: new Abstract: How can we personalize a shared expert library from a user's pairwise choices? Prior work can realize different reward trade-offs by merging reward-spec

The Planning Limits of Latent World Models

arXiv:2609.39235v1 Announce Type: cross Abstract: World models offer a promising way to help robots understand how the physical world evolves and plan complex behaviours through imagination. Yet exist

The System Prompt Illusion: How Instruction Preambles Modify Computation in Language Models

arXiv:2609.38205v1 Announce Type: new Abstract: System prompts are the primary lever practitioners use to control language model behavior, yet what they actually do to the computation inside the trans

Tool-Policy Co-Design for Powder Weighing in Laboratory Automation

arXiv:2609.39797v1 Announce Type: new Abstract: Autonomous powder weighing is one of many bottlenecks in laboratory automation due to the complex, non-linear dynamics of heterogeneous materials. Robot

Towards Optimal Inventory Control under Censored Demand: A Biased Sample-Average Approximation Approach

arXiv:2609.39397v1 Announce Type: cross Abstract: We study data-driven multi-period lost-sales inventory control under censored demand, where a stockout reveals only that demand exceeded the stocking

Towards Universal Wasserstein Barycenters through Flow Matching

arXiv:2609.38547v1 Announce Type: cross Abstract: Defining a weighted mean over probability measures under probability metrics is a central tool in probabilistic machine learning. Under the Wasserstei

Training-Free Affinity Fusion of Neural and Embedding-Based Speaker Diarization

arXiv:2609.39162v1 Announce Type: cross Abstract: Speaker diarization systems based on speaker embeddings and neural diarization exploit complementary forms of speaker information, but their intermedi

Trust Is Not a Score: Runtime Assurance Contracts for High-Risk AI Agents

arXiv:2609.39717v1 Announce Type: new Abstract: Benchmarks, audits, and agent protocols describe performance, permissions, and repair, but not how observed evidence should change an agent's authority

Understanding Off- vs On-Policy Distillation: A Tale of Distinct Training Objectives

arXiv:2609.38666v1 Announce Type: cross Abstract: On-policy distillation (OPD) learns from teacher feedback on student-generated responses and has shown promise in reducing forgetting relative to supe

Unveiling the Value of Motion for Cinematic Camera Trajectories

arXiv:2609.38683v1 Announce Type: cross Abstract: Cinematic camera motion is a fundamental storytelling tool, defined not only by where the camera is positioned in the scene, but also by how it moves

VERA: Verifiable Feasibility Representations with Counterfactual Credit for Constrained Multi-Agent Control

arXiv:2609.38889v1 Announce Type: new Abstract: Constrained multi-agent control requires more than predicting rewarding actions: an action can cease to be executable as contact windows, shared capacit

WEIRDO: WEak resIdual Regularized DOob's h-transform diffusion alignment

arXiv:2609.39531v1 Announce Type: cross Abstract: We study the problem of estimating the guidance that steers the distribution learned by a diffusion generative model toward a tilted target q_0 propto

What to Attend, What to Keep: Skill-Conditioned Visuotactile Representation with Progress-Guided Event Memory

arXiv:2609.38494v1 Announce Type: cross Abstract: Robotic manipulation integrates vision, touch, and language, whose importance shifts across stages: vision guides reaching, while touch, through its e

When Clipping Reverses Correction: Failure Dynamics of Pointwise Forward-KL On-Policy Self-Distillation

arXiv:2609.38995v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own generated responses using feedback from the same model conditioned on privileged informat

When Instructions Retrieve Trajectories: Diagnosing and Mitigating Generalization Failures in VLA Models

arXiv:2609.39971v1 Announce Type: cross Abstract: Vision-language-action (VLA) models can exceed 90% success on in-distribution tasks and withstand nuisance changes that preserve the required action,

When Order Matters: First-Speaker Bias and Mitigation through Personality in Sequential Multi-Agent Debate

arXiv:2609.38964v1 Announce Type: new Abstract: Multi-agent debate (MAD) is often used to improve large language model (LLM) reasoning, but sequential debate is rarely a neutral aggregator of agents'

Whose Voice Survives the Summary? A Voice-Retention Audit of LLM Employee Listening

arXiv:2609.38818v1 Announce Type: new Abstract: Organizations increasingly route employee feedback to leaders through large language model (LLM) summaries, an unaudited layer that silences already-spo

World-as-Graph: Relational World Modeling Through Latent Space Graphs

arXiv:2609.38927v1 Announce Type: cross Abstract: World models aim to learn representations of real-world environments and predict their future evolution. Recent object-centric world models have made

Zero-Compute Cross-Lingual Transferability Estimation Using Typological Feature Proxies

arXiv:2609.39640v1 Announce Type: cross Abstract: Cross-lingual transfer describes how knowledge in a source language benefits a target language. Measuring it quantitatively requires broad multilingua

A Comprehensive View of Fairness through Distributional Stability

arXiv:2609.37061v1 Announce Type: cross Abstract: We view fairness as a property of distributional stability. Rather than assessing a predictor under a fixed data distribution, we study how its predic

A Proposed Rubric for Evaluating Expressed Clinical Reasoning in Large Language Model Responses

arXiv:2609.37788v1 Announce Type: cross Abstract: Rubrics support the structured evaluation of language models. We propose a rubric for assessing expressed clinical reasoning in model responses, drawi

A Spectral Theory of Distortion in LLM Graph Reconstruction: Sharp Bounds and Empirical Characterization

arXiv:2609.38161v1 Announce Type: new Abstract: Evaluations of graph reconstruction by language models typically report a single aggregate distance between the original and the reconstructed graph. We

ABC: Advantage-Based Control Variates for Reinforcement Learning with Verifiable Rewards

arXiv:2609.36058v1 Announce Type: new Abstract: Recent progress in reinforcement learning with verifiable rewards (RLVR) has highlighted the effectiveness of simple critic-free policy-gradient methods

Achieving an O(1/N) Optimality Gap in Average-Reward Weakly-Coupled MDPs

arXiv:2609.38132v1 Announce Type: new Abstract: We study average-reward weakly-coupled Markov decision processes (WCMDPs), where a WCMDP consists of N smaller MDPs, called arms, that share multiple pe

Action Chunking Proximal Policy Optimization with Feedback Correction

arXiv:2609.36250v1 Announce Type: cross Abstract: Action chunking provides temporal abstraction in reinforcement learning by selecting short action sequences instead of individual actions, but many ex

actr: aligning thoughts and responses for multilingual safety in reasoning llms

arXiv:2609.37054v1 Announce Type: new Abstract: Ensuring the safety of reasoning large language models (LLMs) across languages is essential for their reliable deployment. However, when exposed to jail

AdaTutoRank: Learning to Rerank Document Sets via Adaptive Tutoring Optimization for RAG and Deep Research

arXiv:2609.32472v2 Announce Type: replace Abstract: Document rerankers determine what evidence reaches the downstream model in RAG and deep research, yet mainstream rerankers select by relevance match

Adversarial Training for Pixel Diffusion

arXiv:2609.38170v1 Announce Type: new Abstract: Pixel diffusion models generate RGB images directly, avoiding the bottleneck of an autoencoder, yet their outputs still systematically underrepresent fi

Adversarially Robust Geometric Safety Certificates for Nonholonomic Robots Against Maneuvering Obstacles

arXiv:2609.37126v1 Announce Type: new Abstract: Safe navigation against obstacles that can actively maneuver within bounded capabilities remains challenging: robust control barrier function methods ty

AdvMT: Adversarial Motion Transformer for Long-term Human Motion Prediction

arXiv:2401.05018v3 Announce Type: replace Abstract: Human motion prediction is a crucial capability for advanced robotic systems that interact with humans. In facilities with dynamic human-robot colla

All You Need Is Low Fidelity: Zero-Shot Sim-to-Real of Learned Robotic Fish Control

arXiv:2609.36993v1 Announce Type: new Abstract: Complex tasks for underwater robots remain limited by the capabilities of their controllers. Learning a better one for a soft, underactuated robotic fis

Altered Thoughts, Altered Actions: Reasoning Chain as Control Surface for a Vision-Language-Action Policy

arXiv:2603.12717v2 Announce Type: replace-cross Abstract: Vision-language-action policies map camera images and natural-language instructions to a robot's motor actions. Some of these policies are des

An Empirical Study and Assessment of EU AI Act Compliance Checkers

arXiv:2609.36228v1 Announce Type: new Abstract: The EU AI Act introduces extensive compliance requirements for organizations that develop, deploy, or integrate AI systems. Many of these requirements a

An interview with OpenAI Chief Research Officer Mark Chen on the Hugging Face incident, slowing AI development, shifting 5%-10% of compute to safety, and more (Will Douglas Heaven/MIT Technology Review)

Will Douglas Heaven / MIT Technology Review: An interview with OpenAI Chief Research Officer Mark Chen on the Hugging Face incident, slowing AI development, shifting 5%-10% of compute to safety, and m

safetytechmeme

Announcing our first open-weights world-action model, Praxis-1. It turns out that, unsurprisingly, you can get predictably better robotics p…

safetycristobal-valenzuela--x

Announcing our first open-weights world-action model, Praxis-1. It turns out that, unsurprisingly, you can get predictably better robotics policy performance by scaling third-person video. It’s been f

Applying Language Models in Clinical Medicine: Recent Trends and Perspectives

arXiv:2609.34780v2 Announce Type: replace Abstract: The use and applicability of artificial intelligence (AI) in medical research and clinical practice has received increasing attention in the literat

Asymptotic Universal Alignment: A New Alignment Framework via Test-Time Scaling

arXiv:2601.08777v2 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) to serve users with heterogeneous and potentially conflicting preferences is a central challenge for per

Audience-Bound Persistent Memory: Authorization Across the Memory Lifecycle

arXiv:2609.36373v1 Announce Type: cross Abstract: A personal language agent that acts for its owner across private and shared conversations can learn a fact from one audience and later place it in the

Authority Bias in Language Models: Source Deference and User Agreement Are Not Interchangeable

arXiv:2609.37616v1 Announce Type: cross Abstract: Language models tend to agree with whatever a user asserts, and post-training increasingly targets this sycophancy so that models evaluate claims on t

Automated Evaluation of Multi-Turn Dialogues in In-Car Conversational Assistants

arXiv:2609.35812v1 Announce Type: new Abstract: In-car conversational assistants (ICAs) are increasingly integrated into vehicles to support route planning, vehicle control, and information access. En

Automated Screw Planning for Reduced Pelvic Fractures Based on Statistical Shape Models and Deep Learning

arXiv:2609.36847v1 Announce Type: new Abstract: Percutaneous iliosacral screw fixation is an important minimally invasive treatment for unstable pelvic fractures. Because the sacroiliac region has com

Back2Struct: Making Structured Images Editable Again

arXiv:2609.37016v1 Announce Type: new Abstract: Structured images, such as diagrams, charts, and flowcharts, are inherently symbolic and can be compactly represented in an editable format, yet in prac