safety

Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

arXiv:2608.18294v1 Announce Type: cross Abstract: An increasing number of scholars use AI to measure variables they subsequently include in downstream analyses. Although AI-measured variables are ofte

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Decision-Metric Alignment in Latent World Models: Diagnostics and Action-Conditioned Objectives for MPC Planning

DGX agent

arXiv:2608.18746v1 Announce Type: cross Abstract: JEPA-style latent world models can use Euclidean distance to a goal latent as the cost for model-predictive control (MPC). Strong decoding of task var

safetyarxiv-cs-cv

20 Aug 2026

Detecting Backdoors in Object Detection via Pre-NMS Prediction Distribution Shift

arXiv:2608.19088v1 Announce Type: cross Abstract: Object detection models deployed in safety-critical applications remain vulnerable to backdoor attacks that cause targeted misbehaviors when a hidden

Dream2Reward: Transition-Alignment Reward Models from Positive Demonstrations for Robotic Manipulation

arXiv:2608.18787v1 Announce Type: new Abstract: Learning robotic policies requires dense rewards that remain informative when behavior departs from successful demonstrations. Progress-based rewards es

DynCur-Geo: Dynamic Curiosity Reward Shaping for Multimodal Active Geo-Localization

arXiv:2608.18673v1 Announce Type: new Abstract: Active geo-localization enables low-altitude UAVs to search for specified targets from limited local aerial observations, supporting time-sensitive appl

EgoHRV: Continuous Heart Rate Variability Estimation from Egocentric Systems for Autonomic Response and Skill Assessment

arXiv:2608.18711v1 Announce Type: new Abstract: Egocentric vision systems capture human behavior from visible cues, but overlook physiological indicators of autonomic states such as stress, engagement

Engineering Psychological Safety in Autonomous Vehicles: A Systems-Theoretic Framework for Psychological Safety in Autonomous Vehicles and its Validation in Real-World Scenarios

arXiv:2608.18778v1 Announce Type: cross Abstract: Despite rapid technological advances, the societal acceptability of autonomous vehicles (AVs) remains limited by psychological barriers that extend be

Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections

arXiv:2608.18690v1 Announce Type: cross Abstract: The European Union has committed to reducing greenhouse gas emissions 55% below 1990 levels by 2030, but whether current trends are compatible with th

extsc{TestifAI}: Tomography-Based Testing for Deep Learning Systems

arXiv:2608.18900v1 Announce Type: new Abstract: As AI systems are increasingly deployed in safety-critical application domains (e.g., autonomous driving), associated risks increase too. Deep learning

FACET: Preserving Source Intent and Executable State in Terminal Task Synthesis

arXiv:2608.18580v1 Announce Type: new Abstract: Training terminal agents requires scalable executable supervision, yet synthesizing high-quality terminal tasks remains challenging. Each task couples a

Fast Best-in-Class Regret for Contextual Bandits

arXiv:2510.15483v3 Announce Type: replace-cross Abstract: We study the problem of stochastic contextual bandits in the agnostic setting, where the goal is to compete with the best policy in a given cl

FD-CanKD: Frequency-Decoupled Cross-Attention Distillation as a Refinement Prior for Compact Object Detectors

arXiv:2608.18590v1 Announce Type: new Abstract: Compact object detectors are suitable for resource-constrained visual perception, but their limited representation capacity creates an accuracy gap rela

Flux-form spatiotemporal neural operators for coarse-grained dynamics of multiscale PDEs

arXiv:2608.18148v1 Announce Type: cross Abstract: We study data-driven prediction of coarse-grained dynamics in multiscale PDE systems. Adopting a closure-free operator-learning viewpoint, we apply a

Fractional Decay KV-Cache: Ownership-Aware Memory Management for Improved Inference Relevancy in Dialog Systems

arXiv:2608.18098v1 Announce Type: cross Abstract: Key-value (KV) caching is essential for efficient autoregressive inference in transformer based dialog systems, yet existing strategies treat all cach

From Inference to Adaptation: A Unified Optimal Transport View of Vision Language Model

arXiv:2608.18339v1 Announce Type: cross Abstract: Vision-language models (VLMs) have demonstrated remarkable zero-shot capabilities yet remain sensitive to real-world distribution shifts during infere

`From Prompt to Perturbation': An Adaptive Framework for Voice-Based Jailbreaks on Audio LLMs

arXiv:2502.00735v4 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly integrated into audio-based applications, growing concerns have emerged regarding their vulne

From Storage to Access: Verifiable Activation of Parametric Knowledge in LLMs via Explicit Priming and Implicit Reasoning

arXiv:2608.18581v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) encode rich factual knowledge in their parameters, reliably recalling and verifying such knowledge remains a key

Future Policy Approximation for Offline Reinforcement Learning in LLM Reasoning

arXiv:2509.19893v3 Announce Type: replace Abstract: Reinforcement learning (RL) has emerged as a key driver of post-training for complex reasoning in large language models (LLMs), yet online RL introd

safetyarxiv-cs-cl

GAPL: Grounded Action-effect Policy Learning for LLM-Based Trajectory Planning

arXiv:2608.18254v1 Announce Type: new Abstract: Trajectory planning for autonomous driving requires both high-level reasoning and precise low-level control. Large Language Models (LLMs) offer semantic

Generalized Audio-Driven Synthesis of Precise Drummer Motion

arXiv:2608.19055v1 Announce Type: new Abstract: Music-driven character animation enables and enhances transformative applications in entertainment and interactive education. However, synthesizing real

GenEx: A Graph-Based Representational Paradigm for SARS-CoV-2 Variant Detection via Codon Co-occurrence Networks

arXiv:2608.18238v1 Announce Type: new Abstract: Genomic analysis on viruses such as SARS-CoV-2 variants: Beta, Gamma, Delta, and Omicron is heavily dominated by classical bioinformatics methods, inclu

Geometric Data Perturbation with Noisy-Anchor Alignment for Privacy-Preserving Collaborative Learning

arXiv:2608.18749v1 Announce Type: new Abstract: Geometric Data Perturbation (GDP) enables one-shot, privacy-preserving collaborative learning: each participant applies a distance-preserving transforma

GigaBrain-WBC-0.5: A Behavior World Model for Robust Whole-Body Control with Environment Interaction

arXiv:2608.18234v1 Announce Type: cross Abstract: Whole-body motion tracking policies turn a humanoid into a robust control interface: the teleoperator---or an upstream model---only supplies a coarse

Global Crises and National Policies: A Large Scale Analysis of Political Content in German Language Online Media

arXiv:2608.18268v1 Announce Type: cross Abstract: Today most media content is consumed based on algorithmic recommendations. Evidence suggests that this can lead to politically biased media consumptio

Global Index on Responsible AI 2026 : Conceptual Framework and Methodology

arXiv:2608.18122v1 Announce Type: cross Abstract: This report presents the methodology of the Global Index on Responsible AI (GIRAI), 2nd Edition. This edition refines the 1st Edition by strengthening

Going with the Flow(s): Distinct Clusters Target Individuals of Interest to Russia

Written by: Gabby Roncone, Wesley Shields Overview Google Threat Intelligence Group (GTIG) is tracking three distinct suspected Russian cyber espionage threat clusters abusing legitimate authenticatio

safetygoogle-cloud-ai

GrabVG: Graph-Attentive Binding for Visual Grounding in UAV Imagery

arXiv:2608.18996v1 Announce Type: cross Abstract: Visual grounding in Unmanned Aerial Vehicle (UAV) imagery aims to localize a target object in complex bird's-eye-view scenes according to a natural la

HarvestPoint-ACT: Explicit Target Selection and Harvest-Point Conditioning for Robotic Fruit Harvesting under Occlusion

arXiv:2608.18446v1 Announce Type: new Abstract: End-to-end imitation learning avoids hand-made robot motion for approaching and grasping, but the policy must still decide which fruit to pick and where

How AI Prompts Can Teach Us About the Structure of Human Behavior

arXiv:2608.18265v1 Announce Type: cross Abstract: We introduce a general, easy-to-implement AI-based method for studying the structure and complexity of human behavior. We assign a large language mode

Improving Rural Medication Safety with AI: A Scoping Review

arXiv:2608.18135v1 Announce Type: new Abstract: Introduction: Medication errors (MEs) represent a significant threat to global healthcare systems, contributing to patient harm. Introducing artificial

Institutional Prestige as Geographic Bias in Large Language Models: Evidence from Three Factorial Experiments with Bootstrap Confidence Intervals

arXiv:2608.18107v1 Announce Type: cross Abstract: We investigate whether large language models (LLMs) systematically discriminate in candidate evaluations based on applicant name ethnicity and/or inst

Karp got so much shit and was actually right. I know the feeling. 🙄

Karp got so much shit and was actually right. I know the feeling. 🙄 🚨OPENAI AND ANTHROPIC JUST FOLDED ON THEIR DATA RETENTION POLICY AFTER PALANTIR CEO EXPOSED THEIR REAL BUSINESS MODEL Alex Karp: >'s

Large Language Model for Verilog Code Generation: Literature Review and the Road Ahead

arXiv:2512.00020v3 Announce Type: replace-cross Abstract: Code generation has emerged as a critical research area at the intersection of Software Engineering (SE) and Artificial Intelligence (AI), att

Learned, Then Lost: A Measured Single-Example Counterfactual in Pre-training

arXiv:2608.19168v1 Announce Type: new Abstract: A single training example's contribution to a finished model is normally estimated rather than measured, because measuring it takes two expensive full p

Learning What to Fail On: Failure-Mode Contextual Bandits for Adversarial Data Curation

arXiv:2608.18681v1 Announce Type: new Abstract: We introduce a failure-aware adversarial retrieval-augmented framework for improving robustness in natural language understanding. Rather than selecting

safetyarxiv-cs-cl

Look Clearly Before Answering: Mitigating Hallucinations in LVLMs via Saliency-Driven Perceptual Realignment

arXiv:2607.16841v2 Announce Type: replace Abstract: Large vision-language models (LVLMs) have demonstrated remarkable capabilities in multimodal understanding. However, they remain prone to hallucinat

LT-Mem: Volatility-Aware Spatio-Temporal Memory for Lifelong Scene Understanding

arXiv:2608.19059v1 Announce Type: cross Abstract: Long-term robot operation in evolving environments requires object-level understanding that persists across repeated revisits. Existing systems either

MIFR: A Modality-Invariant and Fair Representation Framework for Skin Disease Classification

arXiv:2608.18774v1 Announce Type: new Abstract: Skin diseases represent a major global public health burden, yet machine learning tools developed to assist in their diagnosis suffer from two critical

Most “AI influencers” here probably don’t even understand this important (and very basic) point.

Most “AI influencers” here probably don’t even understand this important (and very basic) point. okay so everyone is talking about this but you guys realize it's not an LLM/foundation model or even a

MR-IQA-2: Faithful Image Quality Reflection via Fine-Grained Credit Assignment

arXiv:2608.18579v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown strong potential for image quality assessment (IQA) by improving consistency between quality ratin

okay so everyone is talking about this but you guys realize it's not an LLM/foundation model or even a neural network, right???? it's probab…

okay so everyone is talking about this but you guys realize it's not an LLM/foundation model or even a neural network, right???? it's probably just like some XGBoost or logistic regression algorithm o

OmniAlign: A Unified Multilingual Aligner for Word and Sentence Alignment

arXiv:2608.18474v1 Announce Type: new Abstract: Cross-lingual sequence alignment is fundamental for building and exploiting parallel corpora, spanning mappings from documents and sentences down to wor

safetyarxiv-cs-cl

🦔OpenAI's CFO held an all-hands meeting today to tell employees the company will go public by 2027 and not to worry about Anthropic beating…

🦔OpenAI's CFO held an all-hands meeting today to tell employees the company will go public by 2027 and not to worry about Anthropic beating them to it. This came days after the CRO, COO, and product c

ORV: 4D Occupancy-centric Robot Video Generation

arXiv:2506.03079v3 Announce Type: replace Abstract: Recent embodied intelligence suffers from data scarcity, while conventional simulators lack visual realism. Controllable video generation is emergin

PCQA-R1: Advancing Generalized 3D Point Cloud Quality Assessment with Reinforcement Learning

arXiv:2608.18627v1 Announce Type: new Abstract: No-reference point cloud quality assessment (PCQA) has been an active topic in recent years and is used to measure and optimize the visual experience of

Personalized Autonomous Driving via Optimal Control with Clearance Constraints from Questionnaires

arXiv:2602.08326v2 Announce Type: replace Abstract: Driving without considering the preferred separation distance from surrounding vehicles may cause discomfort for users. To address this limitation,

PGFS++: Molecular Property Improvement under Synthesis and Diversity Constraints

arXiv:2608.19121v1 Announce Type: cross Abstract: Improving molecular properties, such as drug-likeness or binding affinity, is a recurring task in early-stage drug discovery. However, molecules optim

Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Models

arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Althoug