Search: “safety”

CoST: Semantic-Aware Urban Understanding via Spatial-Temporal Alignment

arXiv:2608.21041v1 Announce Type: cross Abstract: Geospatial representation learning from satellite imagery is a fundamental problem for large-scale urban analysis and real-world applications. Despite

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Decoupling Policy Extraction for Offline Reinforcement Learning

DGX agent

arXiv:2608.20909v1 Announce Type: new Abstract: Offline RL methods commonly jointly train the actor and critic, where the critic is used to guide the actor toward higher-value actions. This coupled le

safetyarxiv-cs-lg

24 Aug 2026

Deep Models, Shallow Alignment: Uncovering the Granularity Mismatch in Neural Decoding

arXiv:2601.21948v2 Announce Type: replace Abstract: Neural visual decoding is a central problem in brain-computer interface research, aiming to reconstruct human visual perception and to elucidate the

Demonstration-Guided Humanoid Stand-Up on an Emulated Deformable Surface

arXiv:2608.20852v1 Announce Type: new Abstract: This paper presents a reference-guided reinforcement learning framework to generate stand-up motion for a 29-DOF Unitree G1 humanoid on deformable soft

Difficulty-Aware Semantic-ID Optimization for Generative Recommendation

arXiv:2608.20611v1 Announce Type: new Abstract: Semantic-ID-based generative recommendation casts retrieval and ranking as autoregressive generation over hierarchical item identifiers. A common recipe

Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation

arXiv:2505.16222v2 Announce Type: replace Abstract: With the growing use of large language models(LLMs) as evaluators, their application has expanded to code evaluation tasks, where they assess the co

Driving with DINO: Vision Foundation Features as a Unified Bridge for Sim-to-Real Generation in Autonomous Driving

arXiv:2602.06159v3 Announce Type: replace Abstract: Driven by the emergence of Controllable Video Diffusion, existing Sim2Real methods for autonomous driving video generation typically rely on explici

Efficient Inference for Inverse Reinforcement Learning and Dynamic Discrete Choice Models

arXiv:2512.24407v2 Announce Type: replace Abstract: In many sequential decision-making problems, researchers observe actions but not the rewards that drive behavior, yet still wish to evaluate and com

EmotionDialogCN: A Spontaneous Multimodal Dataset for Mandarin Emotional Dialogue

arXiv:2608.20905v1 Announce Type: new Abstract: Face-to-face audiovisual interaction is central to human communication, conveying rich emotional and social cues. However, existing multimodal dialogue

EndoLIFT: Language-Disambiguated Latent-Conditioned Rectified Flow for Bidirectional Endoscopic Control

arXiv:2608.20478v1 Announce Type: new Abstract: Routine gastrointestinal endoscopy is intrinsically bidirectional: the instrument is advanced to reach target anatomy and later withdrawn or retroflexed

Evaluating Skills, Not Just Agents: Agentic Continuous Evaluation of Skills

arXiv:2608.20614v1 Announce Type: new Abstract: Enterprise agent programs are moving from prototypes into production, where reusable skills, tools, and workflow packages must be reviewed with evidence

ForeTime-VLA: Causal Future-Token Distillation from a World Action Model for Conveyor-Belt Manipulation

arXiv:2608.20735v1 Announce Type: new Abstract: Manipulating moving objects requires a policy to anticipate contact events, yet vision-language-action (VLA) policies are commonly fine-tuned from the c

GAP-SAM: A Global Artifact Prior for Generalizable AI-Generated Image Manipulation Localization

arXiv:2608.20929v1 Announce Type: new Abstract: AI-generated image manipulation localization identifies edited pixels, but its OOD performance lags behind image-level detection partly because pixel su

Generating Multi-view Adversarial Examples for Visual Geometry Grounded Transformer

arXiv:2608.20748v1 Announce Type: new Abstract: The Visual Geometry Grounded Transformer (VGGT) enables unified feed-forward 3D reconstruction from multi-view images. However, deploying such a high-pe

Geometric Regularization for Long-Tailed Semi-Supervised Learning via Gaussian Feature Bridges

arXiv:2608.20710v1 Announce Type: new Abstract: Real-world semi-supervised learning (SSL) often encounters significant challenges with long-tailed label distributions and noisy pseudo-labels, which hi

Is Multimodal Speculative Decoding Ready for Diffusion-Based Parallel Drafting? A Survey and Empirical Diagnosis

arXiv:2608.20743v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by allowing a lightweight drafter to propose future tokens while a target model verifies them

Kinematic Knowledge Maps for Pattern Alignment: Structured Latent Representational Learning in Multimodal Gait Analysis

arXiv:2608.20969v1 Announce Type: new Abstract: Multimodal clinical AI is limited by weakly aligned inputs and the absence of domain-specific interpretable representations, particularly when learning

Koala Gripper: Co-designing Robotic Grippers and Data-Capture Devices for Scaling Dexterous Manipulation Learning

arXiv:2608.20546v1 Announce Type: new Abstract: As the demand for larger manipulation datasets grows, handheld robotic gripper data collection and the associated gripper designs become more vital. Cur

Latent Ordinal Evidence, Misaligned Outputs: Inference-Time Ordinal Lens Alignment for Multimodal LLMs

arXiv:2608.20999v1 Announce Type: new Abstract: Multimodal LLMs apply the language model interface to visual inputs, where ordinal regression tasks such as age estimation, image quality assessment, an

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

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

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

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

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

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

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

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

safetygary-marcus--x

Model Releases

The Intrinsic Dimension of Prompts in Internal Representations of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2501.10573v2 Announce Type: replace Abstract: We study the geometry of token representations at the prompt level in large language models through the lens of intrinsic dimension. Viewing transfo

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