Search: “safety”

Consequential Behaviour and Representational Fairness in the Validation of Synthetic Research

arXiv:2609.27690v1 Announce Type: new Abstract: Researchers in industry and academia use synthetic survey respondents powered by large language models as substitutes for human samples. These synthetic

safetyarxiv-cs-cl

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Controlled Attribute-Specific Summarization of Interrogative Dialogues

DGX agent

arXiv:2609.28004v1 Announce Type: cross Abstract: Effective summarization of interrogative dialogues is a critical task in forensic and investigative settings, requiring high factual accuracy, coheren

safetyarxiv-cs-ai

24 Sept 2026

COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluation

arXiv:2609.26853v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have achieved remarkable results across various benchmarks, their alignment with normative values often results in

CRISP: Compositional Relations as Invariant Structural Priors for Domain Generalization

arXiv:2605.06043v2 Announce Type: replace Abstract: Domain generalization requires identifying stable representations that support reliable classification across domains. Domains may differ in low-lev

Cross-Modal Contrastive Learning from Histopathology and CT for Automated Renal Cell Carcinoma Grading

arXiv:2609.26920v1 Announce Type: cross Abstract: Background: Clear cell renal cell carcinoma (ccRCC) exhibits substantial clinical heterogeneity, and accurate grade assessment is essential for risk s

CS-WCP: Robust Conformal Sets for LLM-Judge Traffic Shifts with Uncertain Group Proportions

arXiv:2609.27955v1 Announce Type: new Abstract: Prediction sets built from an LLM judge can undercover when deployment traffic changes the prevalence of task or policy groups. Weighted conformal predi

Curriculum Learning with GNN-based Reinforcement Learning for Job Shop Scheduling

arXiv:2609.28085v1 Announce Type: cross Abstract: The job shop scheduling problem is a challenging combinatorial optimization problem, and recent reinforcement learning approaches using graph neural n

DAVIS: A Depth-Only End-to-End Active-Vision Framework for Humanoid Soccer Skills

arXiv:2609.28175v1 Announce Type: new Abstract: Humanoid soccer contact skills require more than producing high-impact foot-ball contacts: the robot must close the loop over perception, approach, alig

DCRL: Decoupling and Coupling Reinforcement Learning via Policy-Reward Manifold Alignment

arXiv:2609.27572v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as a key paradigm for improving the reasoning capabilities of large language models (LLMs). However, existing

Diff-RF: Mutually Reinforced Image Registration and Fusion via Degradation-Aware Learning

arXiv:2609.28235v1 Announce Type: new Abstract: Image registration and fusion aim to establish spatial correspondences from misaligned multi-modal source images, and integrate complementary informatio

Discrete optimal transport is a strong audio adversarial attack

arXiv:2509.14959v4 Announce Type: replace-cross Abstract: In this paper, we investigate discrete optimal transport (DOT) as a black-box attack against modern automatic speaker verification (ASV) and a

Dissecting Advantage-Guided Post-Training for Vision-Language-Action Policies

arXiv:2609.28161v1 Announce Type: new Abstract: Advantage-guided reinforcement learning provides a practical way to post-train vision-language-action (VLA) policies using limited robot data. However,

Distillation for Efficient Multitask Manipulation Policies via Conditional Flow Matching

arXiv:2609.28107v1 Announce Type: cross Abstract: Advances in generative modeling have recently been extensively employed in robotics for policy learning. In particular, Conditional Flow Matching (CFM

DMM-Align: Closed-Loop Optimization for 2D-3D Registration with Dual-Role Diffusion

arXiv:2609.27794v1 Announce Type: new Abstract: 2D-3D registration remains brittle in challenging scenarios such as low overlap, occlusion, repetitive structures, and severe cross-modal ambiguity. A k

Do We Need Complex Topology Control? Distinct-Peer Random Routing Improves Cost-Efficiency in Sparse Multi-Agent Debate

arXiv:2609.27150v1 Announce Type: new Abstract: Multi-agent debate (MAD) has emerged as a promising paradigm for improving the reasoning accuracy of large language models (LLMs) through iterative peer

EmbodiedMemory-Bench: Benchmarking Embodied Memory for Long-Horizon Embodied Tasks

arXiv:2609.28236v1 Announce Type: new Abstract: Long-horizon embodied interaction requires agents to retain and continually update information about the environment as they observe, act, and encounter

Exact Minimax One-Bit Unbiased Compression: Heavy-Tail Necessity and Finite-Randomness Approximation

arXiv:2609.27860v1 Announce Type: new Abstract: A pointwise-unbiased one-bit compressor reconstructs every real input in expectation while transmitting one bit. For a scalar source P with CDF F, mean

FairTest: Search-Based Fairness Testing for Multi-Agent Reinforcement Learning Systems

arXiv:2609.27309v1 Announce Type: cross Abstract: Multi-agent Reinforcement Learning (MARL) trains a team of agents that share one environment and learn their policies together. Training maximizes the

FFM-CP: Cross-Backbone Fusion of Vision-Language Foundation Models for Few-Shot Computational Pathology

arXiv:2609.27710v1 Announce Type: new Abstract: Pathology vision-language foundation models vary in performance across diseases and tasks, with no single model consistently performing best. The high c

From Agent Output to Authorized Transition

arXiv:2609.28216v1 Announce Type: cross Abstract: Agentic engineering systems can edit repositories, run tools and tests, build firmware, synthesize schematics, and prepare deployable or manufacturabl

From Alignment to Fusion in 3D Vision-Language

arXiv:2609.28222v1 Announce Type: new Abstract: Unified 3D vision-language systems must combine complementary geometry, scale, and appearance cues while supporting tasks from instance segmentation to

From Reasoning Strings to Partial Orders: Verifier-Certified Rule Transport through Quotient Policy Optimization

arXiv:2609.27833v1 Announce Type: new Abstract: Many computations admit several valid execution orders because independent subgoals or disjoint state updates can commute. Reinforcement learning with v

From Sentiment Classification to Actionable and Responsible Feedback: A Scoping Review and Evidence Map of NLP in Student Evaluation of Teaching, 2015-2026

arXiv:2609.27939v1 Announce Type: new Abstract: Natural language processing (NLP) applied to open-ended teaching-evaluation comments (Student Evaluation of Teaching, SET) has tracked the field's techn

safetyarxiv-cs-cl

FSCE: A Target-Aware Frequency-Spatial Collaborative Enhancement Framework for Noise-Resilient SAR ATR

arXiv:2603.21565v2 Announce Type: replace-cross Abstract: Synthetic aperture radar automatic target recognition (SAR ATR) is severely challenged by coherent speckle noise, whose interference can be pr

Full-Covariance Smoothing of Bayesian Neural Networks for Online Adaptation

arXiv:2609.27244v1 Announce Type: new Abstract: A neural network's layers can be treated as time steps of a state-space model, turning Bayesian training into a smoothing problem: a forward pass propag

GaussianDS: Depth-supervised Semantic Gaussian Splatting for Scene Understanding

arXiv:2609.27850v1 Announce Type: new Abstract: 3D Gaussian Splatting provides an efficient representation for 3D reconstruction, and recent extensions attach semantic attributes to Gaussians for open

Gender Bias in Vision-Language In-Context Learning

arXiv:2609.27682v1 Announce Type: new Abstract: In-context learning (ICL) enables large vision-language models (LVLMs) to perform tasks by following patterns from in-context examples, yet its potentia

HaRP: High Dynamic Range Photosequencing through Dual Reversed Shutter Scanning

arXiv:2609.28439v1 Announce Type: new Abstract: The adoption of CMOS sensors in mobile photography is frequently compromised by the rolling shutter (RS) effect, which introduces geometric distortions

High Dynamic Range Video Reconstruction from Single-Exposure Raw Sequences

arXiv:2609.27274v1 Announce Type: new Abstract: Due to the limited dynamic range of conventional image sensors, captured low dynamic range (LDR) video often suffers from highlight clipping and shadow

HiRE: Hindsight Reward Editing for Policy Finetuning

arXiv:2609.27068v1 Announce Type: new Abstract: Pre-trained robot policies always require finetuning to adapt to specific environments. Reinforcement Learning (RL) offers high performance potential be

Humanoid Locomotion with a Fly-Inspired Recurrent Controller

arXiv:2609.27001v1 Announce Type: new Abstract: We investigate humanoid locomotion with a fly-inspired recurrent controller and identify the pathways supporting its deployed behavior. The controller c

Impact-Time Guidance via Normal Contraction to a Time-to-Go Isochron

arXiv:2609.26906v1 Announce Type: cross Abstract: We develop a contraction-based perspective on impact-time guidance that augments a baseline homing command with a timing bias. The proposed perspectiv

InfiNoVA: Infinite Novel View Augmentation for Viewpoint Invariant Robot Policies

arXiv:2609.27734v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies often rely strongly on the camera viewpoints seen during training, causing substantial performance degradation w

Model Releases

InGuard: Towards Generalized Inner Guardrail for Safe Text-to-Image Generation

model-releasesarxiv-cs-ai

arXiv:2609.27620v1 Announce Type: cross Abstract: Modern text-to-image (T2I) models generate high-quality images from arbitrary user prompts, yet they can just as easily produce not-safe-for-work (NSF

Learning a Speed-adaptive Hip Exoskeleton Control Policy Via Sim-to-real Reinforcement Learning

arXiv:2609.28027v1 Announce Type: new Abstract: Providing personalized exoskeleton assistance across varying walking speeds remains challenging. Existing online optimization methods are sample-ineffic

Learning Expressive Humanoid Locomotion from Monocular Runway Videos for Robot Fashion Shows

arXiv:2609.27003v1 Announce Type: new Abstract: Runway walking requires coordinated control of posture, stride, foot placement, and whole-body motion to effectively present clothing and convey a disti

Learning Risk Scores Robust to Unobserved Confounders

arXiv:2609.27144v1 Announce Type: new Abstract: We consider the problem of learning risk scores to prioritize individuals for scarce resources or interventions, from historical observational data affe

Learning to Remember: Attentive Reinforcement Learning for Edge Serverless Autoscaling

arXiv:2603.28790v2 Announce Type: replace-cross Abstract: In edge computing, the stochastic and bursty nature of serverless workloads challenges autonomous resource orchestration. Traditional reactive

Learning What to Activate: Combinatorial Capability Allocation for Long-Horizon Multimodal Agents

arXiv:2609.27869v1 Announce Type: new Abstract: Long-horizon multimodal agents rely on specialized capabilities for perception, retrieval, reasoning, verification, and execution. Existing designs typi

Learning Where to Look: A Shared Relative-Alignment Module for Time-Series Forecasting and PPG-to-Vital-Sign Reconstruction

arXiv:2609.27473v1 Announce Type: new Abstract: PPG-to-vital-sign reconstruction turns a wrist-worn photoplethysmogram into clinical waveforms such as the ECG. Long-horizon multivariate time-series fo

LiMA: Bridging Long-term Imagination to Real-time Dexterous Manipulation via Asynchronous Diffusion

arXiv:2609.28431v1 Announce Type: new Abstract: Dexterous manipulation demands long-term foresight and rapid reactive control. Vision-Language-Action (VLA) models, while proficient in high-level reaso

Loss Choice or Model Choice? The Role of Forecast Level in Cryptocurrency Volatility Forecasting

arXiv:2609.27024v1 Announce Type: cross Abstract: Volatility forecasts play a central role in financial risk management because their overall level and day-to-day movements affect downstream decisions

Marginally Correct Tool Caches Can Reverse Group-Normalized Policy Updates

arXiv:2609.26866v1 Announce Type: new Abstract: Tool-result caching reduces repeated execution in agent training, but also couples rollout randomness. We study a two-action model in which independent

Median Temporal Ensembling: Training-Free Robust Aggregation for Action-Chunked Visuomotor Policies

arXiv:2609.27167v1 Announce Type: cross Abstract: Action-chunked visuomotor policies predict overlapping trajectories, so every executed action is covered by several predictions. Temporal ensembling s

MemBodied: Recurrent Associative Memory for Vision-Language-Action Models

arXiv:2609.28256v1 Announce Type: cross Abstract: Vision-Language-Action models provide a strong foundation for general-purpose robot control, yet a vast majority of policies do not preserve and lever

Memory That Changes Action Is Not Memory That Guides It: Counterfactual Auditing of History-Conditioned Robot Policies

arXiv:2609.27247v1 Announce Type: new Abstract: A robot returning a block to its origin tray may encounter two task-consistent pasts that reconverge to the same current input but warrant different act

NavProbe: Evidence-Grounded Reasoning with Active Memory Retrieval for Zero-Shot Navigation

arXiv:2609.27526v1 Announce Type: new Abstract: Long-horizon navigation requires an agent to revise its intermediate objectives as evidence accumulates. Full visual histories are costly to process, wh

Never Too Late for Force: Accelerating VLA Post-Training with Reactive Force Injection

arXiv:2607.14236v2 Announce Type: replace-cross Abstract: Pretrained vision-language-action (VLA) policies provide strong language-conditioned manipulation knowledge, but they remain largely vision-dr