Search: “safety”

Robust Estimation of Sparse Numerical Vectors under Local Differential Privacy

arXiv:2607.27815v1 Announce Type: cross Abstract: Local differential privacy (LDP) protocols are vulnerable to poisoning attacks. Existing research have proposed efficient defense strategies for singl

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SCOPE: Supply-Chain Operations through Coupled Policies for End-to-End Coordination

DGX agent

arXiv:2607.28488v1 Announce Type: cross Abstract: Can supply-chain AI move beyond isolated decision modules toward unified operational planning? A complete replenishment plan specifies which products

safetyarxiv-cs-lg

31 Jul 2026

ServerlessT2I: Efficient Text-to-Image Workflow Serving on a Serverless Platform

arXiv:2607.26566v1 Announce Type: cross Abstract: Text-to-image (T2I) workflows are increasingly deployed on serverless platforms because users often compose customized workflows and invoke them inter

SimpleWikiSearch: A Clean Offline Wikipedia Environment for Agentic Search

arXiv:2607.26070v1 Announce Type: cross Abstract: Large language model (LLM)-based agentic search systems are often evaluated as if the underlying LLM were the only component that matters, yet their m

SkillSight: Calibrating Generic Content Bias for Skill Retrieval

arXiv:2607.18785v2 Announce Type: replace Abstract: As large language model agents gain access to increasingly large skill libraries, retrieving the right skill becomes critical to reliable capability

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation

arXiv:2607.27890v1 Announce Type: new Abstract: Visuomotor policies have advanced on manipulation tasks where the target object stays static during execution, but real deployments break this assumptio

safetyarxiv-cs-ro

Strategies for Milestone-driven Start-ups in Multi-activity Settings

arXiv:2607.27563v1 Announce Type: new Abstract: New venture start-ups need to ``survive'' through multiple stages of reaching milestone targets. We investigate the strategies for start-ups in a milest

SVR: Self-Verifying Refinement via Joint Verdict-Confidence Reinforcement Learning for Adaptive Test-Time Compute

arXiv:2607.28457v1 Announce Type: cross Abstract: Scaling test-time computation can improve language-model reasoning, but uniform budgets waste computation on easy inputs, while verifier-guided refine

TAPO: Transition-Aware Policy Optimization for LLM Agents

arXiv:2607.27973v1 Announce Type: new Abstract: Recently, Reinforcement Learning (RL) has emerged as a crucial paradigm for the post-training of Large Language Model (LLM) agents. However, existing me

Temporal Concentration from Rollout Errors: Implicit Preference Optimization for Text-to-Video Diffusion

arXiv:2607.28058v1 Announce Type: new Abstract: Recent advances in preference alignment for diffusion-based video generation, particularly via Direct Preference Optimization (DPO), have significantly

The Confidence Manifold: Geometric Structure of Correctness Representations in Language Models

arXiv:2602.08159v2 Announce Type: replace-cross Abstract: When a language model asserts that 'the capital of Australia is Sydney,' does it know this is wrong? Models assert misconceptions with the sam

The Easy Trap: Why LLMs Underestimate Misconception-Driven Difficulty

arXiv:2607.26067v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for estimating item difficulty in educational assessment. However, it remains unclear whether such

The Kinetics of Training: A Driven-Nucleation Rate Law for Emergence, Plasticity Loss, and Circuit Control in Language Models

arXiv:2607.27281v1 Announce Type: new Abstract: A capability appears in a language model when the last parts of its circuit align in one stochastic attempt, and getting all but one right is worth noth

this is the whole problem in a nutshell. LLM-centered systems just can’t be trusted to follow hard constraints, we absolutely must find alte…

this is the whole problem in a nutshell. LLM-centered systems just can’t be trusted to follow hard constraints, we absolutely must find alternatives that can, or we are screwed. Anybody remember this

safetygary-marcus--x

UniCross: Unified Cross-Skill Dexterous Manipulation Synthesis

arXiv:2607.28198v1 Announce Type: cross Abstract: Many dexterous manipulation tasks require the object to remain securely held throughout the interaction. From the perspective of hand-object relationa

Unifying Adversarially Robust Model Experts in Vision-Language Models

arXiv:2607.27897v1 Announce Type: new Abstract: Vision-language models (VLMs), such as CLIP, are vulnerable to adversarial attacks, posing a serious problem for real-life applications and deployment.

VAD: Attributing Visual Evidence for Target Reconstruction in Multimodal On-Policy Distillation

arXiv:2607.28590v1 Announce Type: cross Abstract: Multimodal on-policy distillation (OPD) transfers fine-grained visual knowledge by supervising student-generated trajectories with a privileged-view t

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards

arXiv:2511.23310v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as an effective paradigm for post-training large language models, yet the de

When Does Explicit View Routing Work? A Controlled Study of Multi-View Graph-Text Alignment

arXiv:2607.27530v1 Announce Type: new Abstract: Graph-text retrieval typically maps a graph and its description to a single embedding, even when a query concerns only one semantic aspect, such as a cl

World Action Planner: Generalizable Decision-Making with Action-Conditioned World Models

arXiv:2607.27599v1 Announce Type: cross Abstract: Building generalizable agents for diverse applications remains a fundamental challenge. While imitation learning-based policies succeed in specific tr

safetyarxiv-cs-ro

A Persona-based Rate Action Index

arXiv:2607.26545v1 Announce Type: cross Abstract: We propose an index for predicting the U.S. Federal Open Market Committee (FOMC) decision to hike/hold/cut the current federal funds target rate based

AgentGFM: A Graph Foundation Model with Node-Agent Information-Flow Control

arXiv:2607.26533v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) aim to learn transferable knowledge from multi-domain graphs and adapt to unseen scenarios. As a fundamental source of re

AgentSnare: Learning to Delay, Divert, and Defuse Autonomous Penetration Agents

arXiv:2607.26998v1 Announce Type: cross Abstract: Large language model (LLM) agents automate penetration testing through an observation-action loop, selecting actions based on observations returned by

AlloyDB adds group authentication to secure enterprise scale and AI agents

Database security traditionally relies on a fragile balance between the granular control developers need and the administrative overhead of managing thousands of individual database passwords. Between

safetygoogle-cloud-ai

Anatomy Contextualized Adaption of CT Foundation Models

arXiv:2607.27154v1 Announce Type: new Abstract: CT vision-language foundation models have demonstrated promising performance across downstream tasks, but are typically trained with whole-volume repres

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time

arXiv:2607.26647v1 Announce Type: new Abstract: While text-to-image diffusion models achieve impressive visual quality, they frequently struggle to maintain precise alignment with complex compositiona

CASIAL: Geometric Distortion Robust Image Watermarking

arXiv:2607.26729v1 Announce Type: new Abstract: Deep learning-based watermarking has shown strong robustness against non-geometric distortions, yet its performance under geometric transformations rema

CG-World: A Large-Scale World-State Dataset and Protocol for World Models

arXiv:2607.26452v1 Announce Type: cross Abstract: World models must learn the joint dynamics of states, actions, events, and observations, yet existing video, robotics, and simulation datasets usually

CheckVLA: Execution-Time Verification with Action-Conditioned World Model for Long-Horizon Mobile Manipulation

arXiv:2607.26789v1 Announce Type: new Abstract: Vision-language-action (VLA) policies commonly execute long-horizon mobile manipulation through open-loop action chunks, issuing multiple actions withou

safetyarxiv-cs-ro

Model Releases

Choosing Where and How to Moderate: End-to-End Trade-offs in Filter Placement and Response Rewriting

model-releasesarxiv-cs-cl

arXiv:2607.26200v1 Announce Type: new Abstract: Content-moderation classifiers are usually evaluated in isolation, but deployment requires choosing where to intervene and what follows a flag. We evalu

CineWeaver: Training-Free Reference-Controllable Multi-Shot Long Video Generation for Cinematic Storytelling

arXiv:2607.26529v1 Announce Type: new Abstract: Cinematic video generation is challenging for text-to-video diffusion models due to concurrent requirements on multi-shot generation, fine-grained contr

Collaborative Weighting with Pessimistic Critic for Mitigating Overestimation in Off-Policy Reinforcement Learning

arXiv:2607.26509v1 Announce Type: new Abstract: Deep off-policy reinforcement learning algorithms for continuous control typically rely on neural value function approximation to guide policy improveme

Data Fusion and Contrastive Alignment for Unconstrained IR Molecular Structure Elucidation

arXiv:2607.26164v1 Announce Type: new Abstract: Automated molecular structure elucidation from infrared (IR) spectroscopy data has seen significant advancements in recent years, but its broad applicab

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models

arXiv:2607.26891v1 Announce Type: new Abstract: Sequence labeling is a fine-grained information extraction task, yet existing large language model-based approaches suffer from insufficient domain alig

DistillAlign: Coordinating Mode Covering and Mode Seeking in Autoregressive Video Distillation

arXiv:2607.26811v1 Announce Type: new Abstract: Existing autoregressive video distillation methods commonly adopt a Distribution Matching Distillation (DMD)-based multi-stage pipeline. However, they t

Do Methods Support the Claims? Intra-Paper Verification for Peer Review

arXiv:2607.26066v1 Announce Type: new Abstract: The growing volume of scientific submissions has motivated interest in using large language models (LLMs) to assist peer review. Existing automated nove

Do Unified Multimodal Models Think in One Space? A Lens Through Cross-Branch Steering

arXiv:2607.26411v1 Announce Type: new Abstract: Unified multimodal models (UMMs) aim to integrate understanding and generation within a single architecture, yet it remains unclear whether these capabi

Do You Really Need to Pretrain Q-Functions for Online RL Fine-Tuning?

arXiv:2607.27203v1 Announce Type: new Abstract: Pre-training followed by fine-tuning has become the dominant recipe for learning performant policies, and in value-based reinforcement learning (RL) thi

Dual Inversion for Text-to-Image Diffusion Models: From Both Prompt and Noise Perspectives

arXiv:2607.26735v1 Announce Type: new Abstract: Prompt inversion, as a typical reverse engineering technique, enables text-to-image (T2I) diffusion models to generate the desired target images without

Early Verdicts, Better Budgets: Sequential Adaptive Rollout Allocation for Compute-Efficient RLVR

arXiv:2607.26253v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is bottlenecked by rollout generation, yet many sampled prompts produce saturated groups (all resp

Eddeep: a deep-learning framework for fast eddy-current distortion correction in diffusion MRI

arXiv:2607.26292v1 Announce Type: new Abstract: Diffusion MRI (dMRI) relies on diffusion-weighted echo-planar imaging, which is highly susceptible to eddy-current-induced geometric distortions. These

Evaluating Regional Bias in LLMs From Abstract Stereotype to Concrete Social Decision-Making

arXiv:2607.27022v1 Announce Type: new Abstract: Regional bias in large language models (LLMs) may shape both perceptions of regional groups and decisions about individuals from different regions. Yet

FPSGen: Flexible Point Cloud Scene Generation with BEV-Supported Transport Flows

arXiv:2607.26645v1 Announce Type: new Abstract: Existing point-based generative methods for outdoor scenes primarily focus on LiDAR-conditioned completion. During training, noisy point clouds are cons

From Found to Designed: Concepts as a Design Axis for Large Language Models

arXiv:2607.26825v1 Announce Type: new Abstract: Large language models (LLMs) encode rich concept-like information, but represent it implicitly through distributed statistical associations rather than

From Unsupervised Subgroups to Hypothetical State-Intervention Policies: An Evaluation of Selected Subgrouping Methods in Observational Health Data

arXiv:2607.26521v1 Announce Type: new Abstract: Conventional subgroup analyses can yield unstable and difficult-to-interpret conclusions, especially in observational biomedical data where each individ

Graph Signal Diffusion Models for Wireless Resource Allocation

arXiv:2604.05175v2 Announce Type: replace-cross Abstract: We consider constrained ergodic resource optimization in wireless networks with graph-structured interference. We train a diffusion model poli

Heterogeneous Element-Aware Cross-Version Differencing of Scientific Documents via Layout-Aware Alignment and Structure-Aware Reasoning

arXiv:2607.14117v2 Announce Type: replace Abstract: Cross-version differencing of scientific documents is essential in scholarly publishing and technical documentation, but remains challenging because

HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models

arXiv:2607.26515v1 Announce Type: new Abstract: We present, to our knowledge, the first end-to-end FP4 RL post-training, in which both the rollout and training policies, including their forward and ba