Search: “safety”

UMo: Unified Sparse Motion Modeling for Real-Time Co-Speech Avatars

arXiv:2605.14731v1 Announce Type: cross Abstract: Speech-driven gestures and facial animations are fundamental to expressive digital avatars in games, virtual production, and interactive media. Howeve

Unbiased and Second-Order-Free Training for High-Dimensional PDEs

DGX agent

arXiv:2605.14643v1 Announce Type: new Abstract: Deep learning methods based on backward stochastic differential equations (BSDEs) have emerged as competitive alternatives to physics-informed neural ne

safetyarxiv-cs-lg

15 May 2026

UniTriGen: Unified Triplet Generation of Aligned Visible-Infrared-Label for Few-Shot RGB-T Semantic Segmentation

arXiv:2605.14626v1 Announce Type: new Abstract: RGB-T semantic segmentation requires strictly aligned VIS-IR-Label triplets; however, such aligned triplet data are often scarce in real-world scenarios

V2M-Zero: Zero-Pair Time-Aligned Video-to-Music Generation

arXiv:2603.11042v2 Announce Type: replace-cross Abstract: Generating music that temporally aligns with video events is challenging for existing text-to-music models, which lack fine-grained temporal c

Very thoughtful post on the role and success of open source, including potential applications for AVs and AI. Long, but worth the read. -- '…

Very thoughtful post on the role and success of open source, including potential applications for AVs and AI. Long, but worth the read. -- 'Open source is no longer just how good software gets built.

safetyclem-delangue--x

VGGT-Omega

arXiv:2605.15195v1 Announce Type: new Abstract: Recent feed-forward reconstruction models, such as VGGT, have proven competitive with traditional optimization-based reconstructors while also providing

Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation

arXiv:2602.02994v2 Announce Type: replace Abstract: Reinforcement learning has emerged as a principled post-training paradigm for Temporal Video Grounding (TVG) due to its on-policy optimization, yet

Vision-Core Guided Contrastive Learning for Balanced Multi-modal Prognosis Prediction of Stroke

arXiv:2605.14710v1 Announce Type: cross Abstract: Deep learning and multi-modal fusion have demonstrated transformative potential in medical diagnosis by integrating diverse data sources. However, acc

Vision-LLMs for Spatiotemporal Traffic Forecasting

arXiv:2510.11282v2 Announce Type: replace Abstract: Accurate spatiotemporal traffic forecasting is a critical prerequisite for proactive resource management in dense urban mobile networks. While large

Warp-as-History: Generalizable Camera-Controlled Video Generation from One Training Video

arXiv:2605.15182v1 Announce Type: new Abstract: Camera-controlled video generation has made substantial progress, enabling generated videos to follow prescribed viewpoint trajectories. However, existi

“we are below rock bottom now”. Trump admin continues to piss away America’s scientific lead for no good reason. @elonmusk stands by, does n…

“we are below rock bottom now”. Trump admin continues to piss away America’s scientific lead for no good reason. @elonmusk stands by, does nothing. NEW: A serious staffing shortage — of the Trump admi

safetygary-marcus--x

XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations

arXiv:2511.02776v2 Announce Type: replace Abstract: Recent progress in large-scale robotic datasets and vision-language models (VLMs) has advanced research on vision-language-action (VLA) models. Howe

safetyarxiv-cs-ro

140,000 fake citations in 2025 alone😠

Gary Marcus highlighted a concerning problem in 2025 where approximately 140,000 fabricated citations were identified, likely referring to false or hallucinated references generated by AI systems in a

safetygary-marcus--x

A_3B_2: Adaptive Asymmetric Adapter for Alleviating Branch Bias in Vision-Language Image Classification with Few-Shot Learning

arXiv:2605.13161v1 Announce Type: new Abstract: Efficient transfer learning methods for large-scale vision-language models (e.g., CLIP) enable strong few-shot transfer, yet existing adaptation methods

Achieving epsilon^{-2} Sample Complexity for Single-Loop Actor-Critic under Minimal Assumptions

arXiv:2605.13639v1 Announce Type: new Abstract: In this paper, we establish last-iterate convergence rates for off-policy actor--critic methods in reinforcement learning. In particular, under a single

Active Sensing with Meta-Reinforcement Learning for Emitter Localization from RF Observations

arXiv:2605.12569v1 Announce Type: cross Abstract: Global navigation satellite system (GNSS) interference poses a serious threat to reliable positioning, especially in indoor and multipath-rich environ

Adam-SHANG: A Convergent Adam-Type Method for Stochastic Smooth Convex Optimization

arXiv:2605.12878v1 Announce Type: cross Abstract: We propose Adam-SHANG, a Lyapunov-guided Adam-type method that couples momentum, adaptive preconditioning, and a curvature-aware correction through a

Adaptive mine planning under geological uncertainty: A POMDP framework for sequential decision-making

arXiv:2605.13702v1 Announce Type: new Abstract: Strategic mine production scheduling under geological uncertainty is conventionally formulated as a stochastic optimization problem in which a fixed ext

Adaptive Smooth Tchebycheff Attention for Multi-Objective Policy Optimization

arXiv:2605.12771v1 Announce Type: cross Abstract: Multi-objective reinforcement learning in robotic domains requires balancing complex, non-convex trade-offs between conflicting objectives. While line

AdaptNC: Adaptive Nonconformity Scores for Conformal Prediction under Distribution Shift

arXiv:2602.01629v2 Announce Type: replace Abstract: Rigorous uncertainty quantification is essential for the safe deployment of autonomous systems in unconstrained environments. Conformal Prediction (

Addressing Finite-Horizon MDPs via Low-Rank Tensor Value Approximation

arXiv:2501.10598v3 Announce Type: replace Abstract: We study the problem of learning optimal policies in finite-horizon Markov Decision Processes (MDPs) using low-rank reinforcement learning (RL) meth

Aligning Forest and Trees in Images & Long Captions for Visually Grounded Understanding

arXiv:2602.02977v2 Announce Type: replace-cross Abstract: Vision-language models such as CLIP often struggle to faithfully understand long, detail-rich captions, relying on dominant scene cues while o

Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration

arXiv:2605.13744v1 Announce Type: new Abstract: Image restoration is an inherently ill posed inverse problem. Equivariant networks that embed geometric symmetry priors can mitigate this ill posedness

AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation

arXiv:2605.13724v1 Announce Type: cross Abstract: Few-step video generation has been significantly advanced by consistency distillation. However, the performance of consistency-distilled models often

Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional Attributions

arXiv:2602.02560v2 Announce Type: replace-cross Abstract: Lung cancer remains the leading cause of cancer mortality, driving the development of automated screening tools to alleviate radiologist workl

Beyond Anthropomorphism: Exploring the Roles of Perceived Non-humanity and Structural Similarity in Deep Self-Disclosure Toward Generative AI

arXiv:2605.13574v1 Announce Type: cross Abstract: This study investigates deep self-disclosure toward generative AI by examining perceived non-humanity and structural similarity as psychological facto

BlitzGS: City-Scale Gaussian Splatting at Lightning Speed

arXiv:2605.13794v1 Announce Type: cross Abstract: We present BlitzGS, a distributed 3DGS framework that reduces active Gaussian workload for fast city-scale reconstruction. BlitzGS manages this worklo

Block-wise Adaptive Caching for Accelerating Diffusion Policy

arXiv:2506.13456v2 Announce Type: replace Abstract: Diffusion Policy has demonstrated strong visuomotor modeling capabilities, but its high computational cost renders it impractical for real-time robo

Bridging Domain Gaps with Target-Aligned Generation for Offline Reinforcement Learning

arXiv:2605.13054v1 Announce Type: cross Abstract: Cross-domain offline reinforcement learning aims to adapt a policy from a source domain to a target domain using only pre-collected datasets, where en

CA-GCL: Cross-Anatomy Global-Local Contrastive Learning for Robust 3D Medical Image Understanding

arXiv:2605.13544v1 Announce Type: new Abstract: Fine-grained Vision-Language Pre-training (FVLP) demonstrates significant potential in 3D medical image understanding by aligning anatomy-level visual r

Causal Fine-Tuning under Latent Confounded Shift

arXiv:2410.14375v3 Announce Type: replace Abstract: Adapting to latent confounded shift remains a core challenge in modern AI. This setting is driven by hidden variables that induce spurious correlati

Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling

arXiv:2605.13646v1 Announce Type: cross Abstract: End-to-end autonomous driving, which bypasses traditional modular pipelines by directly predicting future trajectories from sensor inputs, has recentl

Centralized Adaptive Sampling for Reliable Co-Training of Independent Multi-Agent Policies

arXiv:2508.01049v2 Announce Type: replace Abstract: Independent on-policy policy gradient algorithms are widely used for multi-agent reinforcement learning (MARL) in cooperative and no-conflict games,

Characterizing Universal Object Representations Across Vision Models

arXiv:2605.13675v1 Announce Type: new Abstract: Deep neural networks trained with different architectures, objectives, and datasets have been reported to converge on similar visual representations. Ho

ChatSR: Multimodal Large Language Models for Scientific Formula Discovery

arXiv:2406.05410v3 Announce Type: replace Abstract: Current multimodal large language models (MLLMs) are mainly focused on the understanding and processing of perceptual modalities such as images and

CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problem

arXiv:2605.13638v1 Announce Type: cross Abstract: A quantum compiler is a critical piece in the quantum computing pipeline since it allows an abstract quantum circuit to be run on a physical quantum c

Constraints-of-Thought: A Framework for Constrained Reasoning in Language-Model-Guided Search

arXiv:2510.08992v3 Announce Type: replace Abstract: While researchers have made significant progress in enabling large language models (LLMs) to perform multi-step planning, LLMs struggle to ensure th

Context Matters: Auditing Gender Bias in T2I Generation through Risk-Tiered Use-Case Profiles

arXiv:2605.13113v1 Announce Type: cross Abstract: Text-to-image (T2I) generative models are increasingly used to produce content for education, media, and public-facing communication, and are starting

Control where your AI agents can browse with Chrome enterprise policies on Amazon Bedrock AgentCore

In this post, you will configure Chrome enterprise policies to restrict a browser agent to a specific website, observe the policy enforcement through session recording, and demonstrate custom root CA

safetyaws-ml-blog

COSMIC: Concurrent Optimization of Structure, Material, and Integrated Control for robotic systems

arXiv:2605.12654v1 Announce Type: new Abstract: Replicating and surpassing the autonomy of natural organisms remains a long-standing goal in robotics. Yet most robotic systems have their structure, ma

safetyarxiv-cs-ro

Counterfactual Reasoning for Causal Responsibility Attribution in Probabilistic Multi-Agent Systems

arXiv:2605.13077v1 Announce Type: cross Abstract: Responsibility allocation -- determining the extent to which agents are accountable for outcomes -- is a fundamental challenge in the design and analy

CRAFT: Clinical Reward-Aligned Finetuning for Medical Image Synthesis

arXiv:2605.12650v1 Announce Type: new Abstract: Foundation diffusion models can generate photorealistic natural images, but adapting them to medical imaging remains challenging. In medical adaptation,

CROP: Expert-Aligned Image Cropping via Compositional Reasoning and Optimizing Preference

arXiv:2605.12545v1 Announce Type: cross Abstract: Aesthetic image cropping aims to enhance the aesthetic quality of an image by improving its composition through spatial cropping. Previous methods oft

Data Agent: Learning to Select Data via End-to-End Dynamic Optimization

arXiv:2603.07433v2 Announce Type: replace-cross Abstract: Dynamic Data selection aims to accelerate training by prioritizing informative samples during online training. However, existing methods typic

Decision Support for Marketplace Policies under Incomplete Evidence: From Replay to Launch Readiness

arXiv:2605.12840v1 Announce Type: cross Abstract: Marketplace platforms routinely evaluate pricing and allocation policies using logged observational data, yet strong offline performance does not impl

Decoupling Exploration and Policy Optimization: Uncertainty Guided Tree Search for Hard Exploration

arXiv:2603.22273v4 Announce Type: replace Abstract: The process of discovery requires active exploration -- the act of collecting new and informative data. However, efficient autonomous exploration re

Delightful Distributed Policy Gradient

arXiv:2603.20521v2 Announce Type: replace-cross Abstract: Distributed reinforcement learning trains on data from stale, buggy, or mismatched actors, producing actions with high surprisal (negative log

Differentiable Evolutionary Reinforcement Learning

arXiv:2512.13399v2 Announce Type: replace Abstract: Crafting effective reward signals remains a central challenge in Reinforcement Learning (RL), especially for complex reasoning tasks. Existing autom