Search: “safety”

Unbiased Prevalence Estimation with Multicalibrated LLMs

arXiv:2604.21549v1 Announce Type: new Abstract: Estimating the prevalence of a category in a population using imperfect measurement devices (diagnostic tests, classifiers, or large language models) is

24 Apr 2026

Why Do Language Model Agents Whistleblow?

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

arXiv:2511.17085v3 Announce Type: replace-cross Abstract: The deployment of Large Language Models (LLMs) as tool-using agents causes their alignment training to manifest in new ways. Recent work finds

safetyarxiv-cs-ai

24 Apr 2026

Environmental Understanding Vision-Language Model for Embodied Agent

arXiv:2604.19839v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong perception and reasoning abilities for instruction-following embodied agents. However, despite these a

Explainable AML Triage with LLMs: Evidence Retrieval and Counterfactual Checks

arXiv:2604.19755v1 Announce Type: new Abstract: Anti-money laundering (AML) transaction monitoring generates large volumes of alerts that must be rapidly triaged by investigators under strict audit an

From Fuzzy to Formal: Scaling Hospital Quality Improvement with AI

arXiv:2604.20055v1 Announce Type: new Abstract: Hospital Quality Improvement (QI) plays a critical role in optimizing healthcare delivery by translating high-level hospital goals into actionable solut

From Noise to Signal to Selbstzweck: Reframing Human Label Variation in the Era of Post-training in NLP

arXiv:2510.12817v3 Announce Type: replace-cross Abstract: Human Label Variation (HLV) refers to legitimate disagreement in annotation that reflects the diversity of human perspectives rather than mere

FSFM: A Biologically-Inspired Framework for Selective Forgetting of Agent Memory

arXiv:2604.20300v1 Announce Type: new Abstract: For LLM agents, memory management critically impacts efficiency, quality, and security. While much research focuses on retention, selective forgetting--

Large language models perceive cities through a culturally uneven baseline

arXiv:2604.20048v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to describe, evaluate and interpret places, yet it remains unclear whether they do so from a cultural

MedSkillAudit: A Domain-Specific Audit Framework for Medical Research Agent Skills

arXiv:2604.20441v1 Announce Type: new Abstract: Background: Agent skills are increasingly deployed as modular, reusable capability units in AI agent systems. Medical research agent skills require safe

NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering

arXiv:2602.15353v2 Announce Type: replace-cross Abstract: Large pretrained language models and neural reasoning systems have advanced many natural language tasks, yet they remain challenged by knowled

Semantic Prompting: Agentic Incremental Narrative Refinement through Spatial Semantic Interaction

arXiv:2604.19971v1 Announce Type: cross Abstract: Interactive spatial layouts empower users to synthesize information and organize findings for sensemaking. While Large Language Models (LLMs) can auto

Model Releases

A Functionality-Grounded Benchmark for Evaluating Web Agents in E-commerce Domains

model-releasesarxiv-cs-ai

arXiv:2508.15832v2 Announce Type: replace-cross Abstract: Web agents have shown great promise in performing many tasks on ecommerce website. To assess their capabilities, several benchmarks have been

Assessing VLM-Driven Semantic-Affordance Inference for Non-Humanoid Robot Morphologies

arXiv:2604.19509v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated remarkable capabilities in understanding human-object interactions, but their application to robotic sys

ASVSim (AirSim for Surface Vehicles): A High-Fidelity Simulation Framework for Autonomous Surface Vehicle Research

arXiv:2506.22174v2 Announce Type: replace-cross Abstract: The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway

CAHAL: Clinically Applicable resolution enHAncement for Low-resolution MRI scans

arXiv:2604.18781v1 Announce Type: new Abstract: Large-scale automated morphometric analysis of brain MRI is limited by the thick-slice, anisotropic acquisitions prevalent in routine clinical practice.

Decomposed Trust: Privacy, Adversarial Robustness, Ethics, and Fairness in Low-Rank LLMs

arXiv:2511.22099v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have driven major advances across domains, yet their massive size hinders deployment in resource-constrained sett

Developing a Robotic Surgery Training System for Wide Accessibility and Research

arXiv:2505.20562v2 Announce Type: replace Abstract: Robotic surgery represents a major breakthrough in medical interventions, which has revolutionized surgical procedures. However, the high cost and l

DT2IT-MRM: Debiased Preference Construction and Iterative Training for Multimodal Reward Modeling

arXiv:2604.19544v1 Announce Type: new Abstract: Multimodal reward models (MRMs) play a crucial role in aligning Multimodal Large Language Models (MLLMs) with human preferences. Training a good MRM req

Hierarchically Robust Zero-shot Vision-language Models

arXiv:2604.18867v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) can perform zero-shot classification but are susceptible to adversarial attacks. While robust fine-tuning improves their

Symbolic Quantile Regression for the Interpretable Prediction of Conditional Quantiles

arXiv:2508.08080v2 Announce Type: replace Abstract: Symbolic Regression (SR) is a well-established framework for generating interpretable or white-box predictive models. Although SR has been successfu

Task-Adaptive Admittance Control for Human-Quadrotor Cooperative Load Transportation with Dynamic Cable-Length Regulation

arXiv:2604.18905v1 Announce Type: new Abstract: The collaboration between humans and robots is critical in many robotic applications, especially in those requiring physical human-robot interaction (pH

TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process Rewards

arXiv:2512.07761v3 Announce Type: replace Abstract: Large language models have seen widespread adoption, yet they remain vulnerable to multi-turn jailbreak attacks, threatening their safe deployment.

User Simulation in the Era of Generative AI: User Modeling, Synthetic Data Generation, and System Evaluation

arXiv:2501.04410v2 Announce Type: replace Abstract: User simulation is an emerging interdisciplinary topic with multiple critical applications in the era of Generative AI. It involves creating an inte

Adversarial Arena: Crowdsourcing Data Generation through Interactive Competition

arXiv:2604.17803v1 Announce Type: cross Abstract: Post-training Large Language Models requires diverse, high-quality data which is rare and costly to obtain, especially in low resource domains and for

Arch: An AI-Native Hardware Description Language for Register-Transfer Clocked Hardware Design

arXiv:2604.05983v2 Announce Type: replace-cross Abstract: We present Arch (AI-native Register-transfer Clocked Hardware), a hardware description language for micro-architecture specification and AI-as

BIASEDTALES-ML: A Multilingual Dataset for Analyzing Narrative Attribute Distributions in LLM-Generated Stories

arXiv:2604.17008v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate narrative content, including children's stories, which play an important role in social a

CAPC-CG: A Large-Scale, Expert-Directed LLM-Annotated Corpus of Adaptive Policy Communication in China

arXiv:2510.08986v2 Announce Type: replace Abstract: We introduce CAPC-CG, the Chinese Adaptive Policy Communication (Central Government) Corpus, the first open dataset of Chinese policy directives ann

Deep learning based Non-Rigid Volume-to-Surface Registration for Brain Shift compensation Using Point Cloud

arXiv:2604.17389v1 Announce Type: new Abstract: Soft-tissue deformation remains a major limitation in image-guided neurosurgery, where intra-operative anatomy can deviate substantially from pre-operat

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning

arXiv:2510.00761v5 Announce Type: replace Abstract: Large language model (LLM) unlearning aims to surgically remove the influence of undesired data or knowledge from an existing model while preserving

Dual Alignment Between Language Model Layers and Human Sentence Processing

arXiv:2604.18563v1 Announce Type: new Abstract: A recent study (Kuribayashi et al., 2025) has shown that human sentence processing behavior, typically measured on syntactically unchallenging construct

Emergency Stopping for Liquid-manipulating Robots

arXiv:2604.16667v1 Announce Type: new Abstract: Manipulating open liquid containers is challenging because liquids are highly sensitive to vessel accelerations and jerks. Although spill-free liquid ma

Flow-Opt: Scalable Centralized Multi-Robot Trajectory Optimization with Flow Matching and Differentiable Optimization

arXiv:2510.09204v2 Announce Type: replace-cross Abstract: Centralized trajectory optimization in the joint space of multiple robots allows access to a larger feasible space that can result in smoother

Infrastructure-Centric World Models: Bridging Temporal Depth and Spatial Breadth for Roadside Perception

arXiv:2604.17651v1 Announce Type: new Abstract: World models, generative AI systems that simulate how environments evolve, are transforming autonomous driving, yet all existing approaches adopt an ego

LiDAR-based Crowd Navigation with Visible Edge Group Representation

arXiv:2604.16741v1 Announce Type: new Abstract: Robot navigation in crowded pedestrian environments is a well-known challenge and we explore the practical deployment of group-based representations in

MoCo: A One-Stop Shop for Model Collaboration Research

arXiv:2601.21257v2 Announce Type: replace Abstract: Advancing beyond single monolithic language models (LMs), recent research increasingly recognizes the importance of model collaboration, where multi

Multimodal Policy Internalization for Conversational Agents

arXiv:2510.09474v2 Announce Type: replace Abstract: Modern conversational agents like ChatGPT and Alexa+ rely on predefined policies specifying metadata, response styles, and tool-usage rules. As thes

On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations

arXiv:2604.16518v1 Announce Type: new Abstract: Satellite constellations are transforming space systems from isolated spacecraft into networked, software-defined platforms capable of on-orbit percepti

PoliLegalLM: A Technical Report on a Large Language Model for Political and Legal Affairs

arXiv:2604.17543v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success in general-domain tasks, yet their direct application to the legal domain remains challeng

SemLT3D: Semantic-Guided Expert Distillation for Camera-only Long-Tailed 3D Object Detection

arXiv:2604.18476v1 Announce Type: new Abstract: Camera-only 3D object detection has emerged as a cost-effective and scalable alternative to LiDAR for autonomous driving, yet existing methods primarily

Shepherding UAV Swarm with Action Prediction Based on Movement Constraints

arXiv:2604.17189v1 Announce Type: new Abstract: In this study, we propose a new sheepdog-inspired control method for a swarm of small unmanned aerial vehicles (UAVs), which predicts the swarm behavior

The Provenance Gap in Clinical AI: Evidence-Traceable Temporal Knowledge Graphs for Rare Disease Reasoning

arXiv:2604.17114v1 Announce Type: new Abstract: Frontier large language models generate clinically accurate outputs, but their citations are often fabricated. We term this the Provenance Gap. We teste

Towards Trustworthy Depression Estimation via Disentangled Evidential Learning

arXiv:2604.16579v1 Announce Type: new Abstract: Automated depression estimation is highly vulnerable to signal corruption and ambient noise in real-world deployment. Prevailing deterministic methods p

Train Separately, Merge Together: Modular Post-Training with Mixture-of-Experts

arXiv:2604.18473v1 Announce Type: new Abstract: Extending a fully post-trained language model with new domain capabilities is fundamentally limited by monolithic training paradigms: retraining from sc

Training Language Models to Use Prolog as a Tool

arXiv:2512.07407v2 Announce Type: replace Abstract: Language models frequently produce plausible yet incorrect reasoning traces that are difficult to verify. We investigate fine-tuning models to use P

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation

arXiv:2602.09130v3 Announce Type: replace Abstract: Model compression is increasingly essential for deploying large language models (LLMs), yet existing comparative studies largely focus on pruning an

Contact-Aware Planning and Control of Continuum Robots in Highly Constrained Environments

arXiv:2604.15638v1 Announce Type: new Abstract: Continuum robots are well suited for navigating confined and fragile environments, such as vascular or endoluminal anatomy, where contact with surroundi

20 Apr 2026

How people use Copilot for Health

arXiv:2604.15331v1 Announce Type: cross Abstract: We analyze over 500,000 de-identified health-related conversations with Microsoft Copilot from January 2026 to characterize what people ask conversati

20 Apr 2026

Long-Term Memory for VLA-based Agents in Open-World Task Execution

arXiv:2604.15671v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated significant potential for embodied decision-making; however, their application in complex chemical