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Logic-VLA: A Temporal Logic Conditioned Vision-Language-Action Model

arXiv:2608.20556v1 Announce Type: new Abstract: Vision-language-action (VLA) models can follow natural-language (NL) task instructions, but such instructions may not precisely specify safety-critical

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Lost in Translation: How Universal Ethical Values Fail to Translate Across Global Contexts

DGX agent

arXiv:2608.20490v1 Announce Type: new Abstract: AI ethics frameworks treat values such as fairness, transparency, and accountability as universal and uniformly operationalizable across contexts. We ex

safetyarxiv-cs-ai

24 Aug 2026

Making Deployments Safe at Meta: Health Checks for Continuous Change-Safety

arXiv:2608.20513v1 Announce Type: cross Abstract: Continuous deployment to large scale production systems creates a tension between release velocity and reliability. Every change is a potential reliab

MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation

arXiv:2601.06519v2 Announce Type: replace Abstract: Biomedical retrieval-augmented generation (RAG) can ground LLM answers in medical literature, yet long-form outputs often contain isolated unsupport

MIL-BERT: Classification of Arbitrarily Large Text with Performance and Explanatory Guarantees

arXiv:2608.20636v1 Announce Type: new Abstract: Many text classification decisions are viable based on constituent excerpts alone. Taking inspiration from the field of multiple instance learning, we p

Mind the Style: Impact of Communication Style on Human-Chatbot Interaction

arXiv:2602.17850v2 Announce Type: replace-cross Abstract: Conversational agents increasingly mediate everyday digital interactions, yet the effects of their communication style on user experience and

Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy

arXiv:2608.21325v1 Announce Type: new Abstract: Users increasingly turn to large language models for emotional support, yet little is known about how these models actually conduct a psychotherapy inte

Multi-Modal Traffic Sign Detection with Semantic Attributes for Autonomous Driving

arXiv:2608.20874v1 Announce Type: new Abstract: Reliable traffic sign detection is a prerequisite for the global deployment of autonomous driving systems, where regulatory compliance and road safety d

My AI broadly agrees with Arvind's AI: state-level data center bans have very little impact overall on AI progress. If your concern is AI de…

My AI broadly agrees with Arvind's AI: state-level data center bans have very little impact overall on AI progress. If your concern is AI development, concentration of power, future use, or anything e

safetyethan-mollick--x

Natural Sit-to-Stand Motion Synthesis For Humanoids via Guided Assistance Curricula and Staged Rewards

arXiv:2608.20823v1 Announce Type: new Abstract: A humanoid has infinitely many ways to stand up from sitting while maintaining balance, making sit-to-stand (STS) a challenging control problem. We synt

Neural-Primitive: An Efficient End-to-end Local Planner with Primitive-based Imitation Learning for Autonomous Flight

arXiv:2608.20948v1 Announce Type: cross Abstract: Autonomous flight in unknown cluttered environments is hindered by the computation-quality-memory trilemma of onboard trajectory generation. In this p

No PUN Intended: Plausible Unknown Names for Person-Centred LLM Evaluation

arXiv:2608.21206v1 Announce Type: cross Abstract: Person names are widely used as prompt variables in LLM evaluations of factuality, privacy leakage, bias and abstention, but when a name's evidential

Optimistic Online LQR via Intrinsic Rewards

arXiv:2603.28938v2 Announce Type: replace-cross Abstract: Optimism in the face of uncertainty is a popular approach to balance exploration and exploitation in reinforcement learning. Here, we consider

PhysCaP: Grounding Code-as-Policy Agent with Physics-Informed Exploration

arXiv:2608.21031v1 Announce Type: new Abstract: We present PhysCaP, a Physics-Informed Code-as-Policy agent for active perception in robotic manipulation. While vision-language-action policies excel a

PromptResponse: Optimizing Prompts for LLM Coding Tasks

arXiv:2608.21074v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in research workflows and software development pipelines, yet their output remains sensitive to inp

Rapid Manufacturing of Lightweight Drone Frames Using Single-Tow Architected Composites

arXiv:2509.09024v2 Announce Type: replace Abstract: The demand for lightweight and high-strength composite structures is rapidly growing in aerospace and robotics, particularly for optimized drone fra

RecGen3D: Reconstruction-Guided 3D Generation in a Shared Canonical Space

arXiv:2604.01479v3 Announce Type: replace Abstract: Sparse-view 3D modeling represents a fundamental tension between reconstruction fidelity and generative plausibility. While feed-forward reconstruct

ReCurveflow: A Flow Matching Framework that Learns Curved Reaction Trajectories to Predict Transition State Geometries

arXiv:2608.20869v1 Announce Type: new Abstract: Predicting transition states (TS) in chemical reactions is crucial, as they provide insights into reaction mechanisms. Recent work on TS prediction have

Regression-Based Estimation of Causal Effects in the Presence of Selection Bias and Confounding

arXiv:2503.20546v2 Announce Type: replace-cross Abstract: We consider the problem of estimating the expected causal effect E[Y|do(X)] for a target variable Y when treatment X is set by intervention, f

Reinforcing Multi-Turn Reasoning in LLM Agents via Fine-Grained Reward Structure and Credit Assignment

arXiv:2505.11821v3 Announce Type: replace Abstract: Reinforcement Learning (RL) approaches have been wildly used to enhance the reasoning capabilities of Large Language Model (LLM) agents in long-hori

Rethinking Demonstration Unlearning in Imitation Learning for Robotics

arXiv:2608.20784v1 Announce Type: cross Abstract: Imitation learning for robotics depends on human demonstrations, some of which people may later ask to remove. Retraining without them is the natural

RISE: Adaptive Imagination for World Action Models

arXiv:2608.20430v1 Announce Type: new Abstract: World Action Models (WAMs) improve planning by incorporating future world evolution into action generation, yet existing methods allocate a fixed imagin

Robust Validation to Geometric Perturbations for Autonomous Pose Estimation

arXiv:2608.21066v1 Announce Type: new Abstract: Deploying autonomous systems in safety-critical domains demands guaranteed robustness against physically plausible geometric perturbations rather than a

Routing Before Looking: Query-Adaptive Evidence Acquisition for Long-form Video Understanding

arXiv:2608.20805v1 Announce Type: new Abstract: Long-form video understanding remains challenging for video agents due to the mismatch between query demands and evidence acquisition strategies. Althou

Scalable Distributed Simulation-Based Testing for Automated Driving Systems

arXiv:2608.20904v1 Announce Type: new Abstract: Virtual scenario-based testing is a key enabler for validating automated driving systems (ADS) and intelligent transport systems (ITS). However, executi

Scaling Unsupervised Word Alignment to Documents via Structural Constraints

arXiv:2608.21023v1 Announce Type: new Abstract: Word alignment has traditionally been studied between sentences, but many cross-lingual tasks increasingly require correspondences across full documents

Semantically Compatible Knowledge Distillation for Cross-Domain Object Detection with Vision Foundation Models

arXiv:2608.20916v1 Announce Type: new Abstract: Vision foundation models (VFMs) offer strong generalization capabilities for domain-adaptive object detection (DAOD). However, existing VFM-based method

Six misconceptions about large language models: A minimal model and diagnostic taxonomy

arXiv:2608.20421v1 Announce Type: cross Abstract: Large language models (LLMs) are now embedded in scientific, educational, and governance workflows, with debates centering on their capabilities, mech

Source-Free MT Evaluation Is Not MT Evaluation

arXiv:2608.20925v1 Announce Type: cross Abstract: Reference-based metrics remain the standard choice in machine translation evaluation, partly because quality estimation methods often correlate less w

STAR-OPD: Structured Aspect-Cascade-Aware On-Policy Reward Distillation for ABSA Quadruple Extraction

arXiv:2608.20831v1 Announce Type: cross Abstract: Aspect-based sentiment analysis (ABSA) quadruple extraction requires jointly predicting target, aspect, opinion, and sentiment over reviews that often

Teaching is a Process: The TOSS Framework for Modeling Human Teaching Decisions in Human-Interactive Robot Learning

arXiv:2608.21083v1 Announce Type: new Abstract: Successful Human-Robot Teaching assumes alignment between robot processing needs and human teaching intent. To better understand this alignment, this wo

The Divergence Hypothesis: Unmasking Lexical Interference and Label Bias in Mental Health NLP

arXiv:2608.20353v1 Announce Type: cross Abstract: Computational mental health (CMH) classifiers often degrade under distribution shift because human annotators and distant-supervision pipelines reward

the industry’s preferred way to obscure things is to conflate LLMs with AI, and to ignore the fact that recent contributions have come from …

the industry’s preferred way to obscure things is to conflate LLMs with AI, and to ignore the fact that recent contributions have come from adding things - mostly (neuro)symbolic - to those LLMs (prec

This is one of the most useful writeups I have seen on keeping an LLM judge effective in production. (bookmark it) Netflix runs judges over …

This is one of the most useful writeups I have seen on keeping an LLM judge effective in production. (bookmark it) Netflix runs judges over hundreds of thousands of show-level recommendation explanati

safetydair-ai--x

TLive-Omni: An Omni-Modal Understanding Model for E-Commerce Live Streaming

arXiv:2608.20958v1 Announce Type: new Abstract: E-commerce live streaming requires omni-modal understanding of noisy, temporally extended streams, where product facts are distributed across speech, vi

TopoSurfel: Closing the Loop between Gaussian Surfels and Meshes for Surface Reconstruction

arXiv:2608.20687v1 Announce Type: new Abstract: 3D Gaussian Splatting has achieved remarkable success in novel view synthesis. However, extracting high-fidelity surfaces directly from 3DGS remains cha

Trojaning the Alignment: Stealthy Backdoor Attacks against Graph Foundation Models

arXiv:2608.20991v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) on text-attributed graphs (TAGs) align graph representations with language semantics to support transferable graph learni

ViTacPhys: Physical Property-Aware Grasping from Human Visual-Tactile Demonstrations

arXiv:2608.21355v1 Announce Type: new Abstract: Recent vision-based action models have demonstrated strong capabilities in complex manipulation, but they rarely leverage explicit object physical prope

Volumetric Radiology AI in the Era of Multimodal Large Language Models

arXiv:2608.20549v1 Announce Type: new Abstract: Advances in multimodal large language models (MLLMs) are extending radiological artificial intelligence (AI) beyond task-specific image analysis toward

Who Do Language Models Think Is Competent? A Mechanistic Analysis of Occupational Bias

arXiv:2608.20347v1 Announce Type: cross Abstract: Language models (LMs) often pass behavioral bias evaluations, but it remains unclear whether they no longer represent the underlying associations that

Why2Speak: Faithful Reasoning for Abstaining Action Policies

arXiv:2608.20670v1 Announce Type: new Abstract: Many agentic systems must repeatedly choose between acting and abstaining, making faithful reasoning important for oversight: an explanation is useful o

and yet they expect $2T

Gary Marcus recently posted on Twitter questioning why investors still expect a $2 trillion valuation for AI‑related companies, despite broader market skepticism. The Financial Times has reported that

Olympic-level hypocrisy. Altman will say absolutely anything. Here is he today taking a shot at Dario as if Sam hadn’t done EXACTLY the same…

Olympic-level hypocrisy. Altman will say absolutely anything. Here is he today taking a shot at Dario as if Sam hadn’t done EXACTLY the same thing just a few months earlier. Sam today: “there are some

Sam Altman says AI could end up controlled by a few powerful players, partly because AI fears could push people to trade 'a lot of liberty for safety' (Truman Dickerson/Business Insider)

Truman Dickerson / Business Insider: Sam Altman says AI could end up controlled by a few powerful players, partly because AI fears could push people to trade “a lot of liberty for safety” — OpenAI CEO

safetytechmeme

this would be more credible if Sam had left OpenAI when the board fired him.

this would be more credible if Sam had left OpenAI when the board fired him. 🚨 Sam Altman fires shots at Anthropic >“ai becomes too powerful we can’t control it” >“power gets too centralized… one comp

If the AI comes for us, maybe we can all hide in Venecky.

Gary Marcus notes that multimodal large‑language models are likely to struggle with map interpretation. In a tongue‑in‑cheek post he suggests that by 2026—if AI poses a threat—people could seek refuge

22 Aug 2026

Me, 2023, 2024, 2025…. Multimodal LLMs are going to have problems with maps. 2026: It’s ok, you live in Venecky. Not far Tounesseo.

Me, 2023, 2024, 2025…. Multimodal LLMs are going to have problems with maps. 2026: It’s ok, you live in Venecky. Not far Tounesseo. @GaryMarcus It keeps getting crazier “Mom, did you know that we live

22 Aug 2026

The evaluation resolution has been shown to have a significant impact on the identification of the 'learning rule' that exhibits the most brain-like characteristics at V1. [R]