Search: “safety”

TTM-Bench: A Framework for Text-to-Music System Performance Benchmarking

arXiv:2609.18585v1 Announce Type: cross Abstract: Text-to-music (TTM) systems are increasingly used to generate musical audio from natural-language descriptions. Robust evaluation is therefore essenti

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UMI-Bridge: Action-Anchored Latent Alignment across Human and Robot Manipulation Data

DGX agent

arXiv:2609.18232v1 Announce Type: new Abstract: Real-robot demonstrations are limited, motivating the use of human manipulation data collected without robots, including egocentric videos and handheld

safetyarxiv-cs-ro

17 Sept 2026

Unleash LLMs Potential for Sequential Recommendation by Coordinating Dual Dynamic Index Mechanism

arXiv:2409.09253v2 Announce Type: replace-cross Abstract: Owing to the unprecedented capability in semantic understanding and logical reasoning, large language models (LLMs) have shown fantastic poten

Veo-Act: Enhancing VLA Policies with Frontier Video Models

arXiv:2604.04502v2 Announce Type: replace Abstract: Video generation models can produce coherent vi- sual sequences depicting object motion and interactions. We in- vestigate how frontier video genera

Vision-Language Grounded Task-Context-Aware Imitation Learning for Robotic Disassembly

arXiv:2609.17714v1 Announce Type: new Abstract: Real-world robotic disassembly requires long-horizon execution, where robots must perform ordered sequences of manipulation tasks across multiple parts

VLEM: Real-Time 3D Vision-Language Embedding Mapping

arXiv:2508.06291v2 Announce Type: replace Abstract: Semantic scene understanding in robotics requires representations that are both metric-accurate and queryable via natural language in real-time. Whi

VLM-MPPI: Grounding Natural Language in Behaviorally Diverse Trajectories for Aerial Navigation

arXiv:2609.18451v1 Announce Type: new Abstract: We present a hierarchical UAV navigation framework that aligns natural-language intent with dynamically feasible flight behaviors in cluttered indoor en

When AI Generates Covariates: Causal Typing and Estimand Drift in Sequential Experiments

arXiv:2609.17772v1 Announce Type: cross Abstract: AI-generated covariates from notes, conversations, images, and wearable streams can change the causal question when their roles are left unspecified.

When to Call an LLM: A Confidence-Gated Hybrid for Cost-Effective Emotion Recognition in Conversational AI

arXiv:2609.17977v1 Announce Type: new Abstract: Emotion recognition in conversation (ERC) is a production capability behind agent-assist prompts, escalation routing, and post-call analytics in contact

Where Grokking Happens: Distributed Utility and Fourier Recoding Without a Module Switch

arXiv:2609.17571v1 Announce Type: cross Abstract: Where in a Transformer is the change from memorization to generalization functionally expressed? We introduce Transition Games--behavior-aligned exact

Who Audits Whom, on What Substrate, with What Evidence? An Independence-Graded Audit Protocol for Agentic AI

arXiv:2609.18272v1 Announce Type: new Abstract: Agentic AI systems plan, invoke tools and act with limited supervision; they are now both the subject of audits and, increasingly, the auditor. Independ

Whom Do AI Agents Work For? Role Assignment Induces Sponsorship Bias in LLM Recommenders

arXiv:2609.17989v1 Announce Type: cross Abstract: Large language models (LLMs) now serve as conversational shopping assistants on platforms that also sell advertising. These AI agents face a conflict

A Cyber Range Evaluation of Autonomous Network Incident Response Agents

arXiv:2609.16541v1 Announce Type: cross Abstract: We test the performance of agents for automated network intrusion response in a cyber range intended for human operator training. The range implements

A Data-free Universal Prior over Syntactic Structures

arXiv:2609.16854v1 Announce Type: new Abstract: Probability is fundamental to theories of language comprehension, production, acquisition, and evolution, as well as to large language models. Existing

A Programmable Optics Cloud Laboratory

arXiv:2609.16413v1 Announce Type: cross Abstract: Laboratory automation can improve experimental throughput, accessibility, and reproducibility, but many robotic laboratory systems remain difficult to

AI-Driven Feedback Systems, Digital Labour, and Silent Quitting: Transforming African Workplaces

arXiv:2609.16192v1 Announce Type: cross Abstract: The current trend of digitalisation has revolutionised the organisation of work and the way it is measured and performed across the globe, with AI bec

AllShowers: One model for all calorimeter showers

arXiv:2601.11716v2 Announce Type: replace-cross Abstract: Accurate and efficient detector simulation is essential for modern collider experiments. To reduce the high computational cost, various fast m

Artificial intelligence and biosecurity: capabilities, threat pathways, and defense-in-depth governance

arXiv:2609.16213v1 Announce Type: new Abstract: Artificial intelligence is reshaping biological research across an increasingly connected digital-to-physical workflow. General-purpose large language m

Autonomous Droplet Navigation via Model-Based Reinforcement Learning

arXiv:2609.16369v1 Announce Type: new Abstract: Precise manipulation of liquid droplets underpins lab-on-a-chip platforms for diagnostics, chemical synthesis, and biological assays. Yet autonomous dro

Beyond the Name: Demographic Leakage in De-Identified Resumes and Evaluation Artifacts in LLM Bias Audits

arXiv:2609.16501v1 Announce Type: cross Abstract: De-identified resume screening assumes that redacting explicit fields prevents ethnocultural inference; however, recent audits attribute residual leak

Beyond Token-Local Imitation: Reward-Compatible Temporal Credit Assignment for On-Policy Distillation

arXiv:2609.16937v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as an effective approach for large language model post-training, yet existing objectives face a trade-off bet

Bias Audits Detect Bias but Disagree on Ranking: Evidence from Ten Instruments and Ten Frontier Models

arXiv:2609.15995v1 Announce Type: new Abstract: Emerging AI regulation mandates bias audits of high-risk systems, and audit scores are beginning to be used to rank models. Both uses assume different a

Bias-Induced Crossover in Absolute Capacity of Dense Associative Memory

arXiv:2609.17477v1 Announce Type: cross Abstract: The absolute capacity of dense associative memory has mainly been analyzed for unbiased patterns. Here we examine the effect of bias in centered binar

BiCLIP: Bidirectional and Consistent Language-Image Processing for Robust Medical Image Segmentation

arXiv:2603.00156v2 Announce Type: replace Abstract: Medical image segmentation is a cornerstone of computer-assisted diagnosis and treatment planning. While recent multimodal vision-language models ha

Calibrate Once, Fly Any Team: Residual-Grounded Low-Fidelity Training for Cooperative Drone Swarms

arXiv:2609.17265v1 Announce Type: cross Abstract: Training multi-agent drone-swarm policies directly in high-fidelity (HF) rigid-body physics is accurate but computationally expensive. This cost scale

Calibrate, Then Route: A Measured Study of Learned Request Routing for Disaggregated LLM Serving

arXiv:2609.16206v1 Announce Type: new Abstract: Disaggregated LLM serving places compute heavy prefill and memory heavy decode on separate GPU pools. Systems such as DistServe, Splitwise, and Mooncake

Can LLMs Model Incorrect Student Reasoning? A Case Study on Distractor Generation

arXiv:2603.15547v2 Announce Type: replace-cross Abstract: Modeling student misconceptions in a realistic manner is critical for AI in education. In this work, we examine how large language models (LLM

Collaborative Optimization of Multiclass Imbalanced Learning: Density-Aware and Region-Guided Boosting

arXiv:2512.22478v2 Announce Type: replace Abstract: Numerous studies on Boosting attempt to mitigate classification bias caused by class imbalance. However, existing studies have yet to explore the co

Comment on arXiv:2607.01233: Survivorship Bias in Published-Paper Baselines for Research-Idea Distributions

arXiv:2609.15996v1 Announce Type: new Abstract: Chen, Zhao, and Cohan introduce a valuable distributional evaluation of LLM-generated research ideas. This comment raises a narrower identification conc

Coupled Calibration and Learning: Mitigating Teacher Bias in LLM Distillation without Target-Domain Reward Feedback

arXiv:2609.17474v1 Announce Type: cross Abstract: Large language model (LLM) distillation aims to transfer the capabilities of a powerful teacher to a smaller student. Direct imitation, however, can a

DenseFace: Bias Mitigation in Face Recognition via Density-Aware Probabilistic Matching

arXiv:2609.16149v1 Announce Type: new Abstract: Despite steady progress in face recognition, current face recognition models still suffer from significant demographic biases. While approaches for bias

Do You Have Freestyle? Expressive Humanoid Locomotion via Audio Control

arXiv:2512.23650v3 Announce Type: replace Abstract: Humans intuitively move to sound, but current humanoid robots lack expressive improvisational capabilities, confined to predefined motions or sparse

DoubleAgents: Human-Agent Alignment in a Socially Embedded Workflow

arXiv:2509.12626v4 Announce Type: replace-cross Abstract: Aligning agentic AI with user intent is critical for delegating complex, socially embedded tasks, yet user preferences are often implicit, evo

Efficient Quantization-Aware Distillation with Cross-Modal Alignment for Edge Vision-Language Models

arXiv:2609.16689v1 Announce Type: new Abstract: Large-scale vision-language models (VLM) such as CLIP enable strong open-vocabulary reasoning, yet deploying these capabilities on resource-constrained

Extremely coarse learning objectives induce human-aligned representations in AI vision models

arXiv:2605.05556v2 Announce Type: replace Abstract: Artificial neural networks trained on visual tasks develop internal representations resembling those of the primate visual system, a discovery that

FairLint-DL: An IDE-Native Tool for Fairness Debugging of Deep Learning Software

arXiv:2609.16321v1 Announce Type: cross Abstract: Existing fairness analysis tools predominantly operate as post-training evaluation frameworks, requiring practitioners to complete the full model deve

FLAT: Resampling Image and Text into 1D Flexible-Length Aligned Transmodal Tokens for Retrieval and Generation

arXiv:2609.16591v1 Announce Type: new Abstract: Traditional multimodal representation learning and generation are two stages: a contrastive or self-supervised visual encoder is trained first, followed

FluxVLA Engine: A One-Stop VLA Engineering Platform for Embodied Intelligence

arXiv:2609.17210v1 Announce Type: cross Abstract: Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of

GrowMTP: Can RL Grow Its Own Draft Head?

arXiv:2609.16648v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training drives the frontier capabilities of large language models, with its wall-clock dominated by autoregressive r

How Humans and LLMs Read Gender into Gender-Neutral Physical Descriptions

arXiv:2609.16366v1 Announce Type: cross Abstract: When foundation models describe people, recent work in AI fairness, accessibility, and ethics recommends avoiding inferred identity labels (e.g., 'she

Hub-Spectral Activation of Latent Multimodal Knowledge

arXiv:2609.17094v1 Announce Type: new Abstract: Multimodal representation learning seeks shared representations for cross-modal retrieval and knowledge transfer. Hub-based binding reduces pairwise sup

HyCoSeq: Contextual Hyperbolic Representation Learning for Genomic Sequences

arXiv:2609.16925v1 Announce Type: new Abstract: Hyperbolic geometry provides a natural inductive bias for genomic representation learning, but existing hyperbolic genomic models primarily use Lorentz

Hyper-RED: Scalable Event Pre-training via Semantic Hypergraph Distillation

arXiv:2609.16811v1 Announce Type: new Abstract: Event cameras have shown great potential for robust visual perception, yet scaling event representation learning remains challenging due to the scarcity

IL-ACT: Imitation Learning with Adaptive Cartesian Tracking Control for a 30-ton Excavator

arXiv:2609.16696v1 Announce Type: new Abstract: Autonomous excavator control is challenged by coupled kinematics, actuation lag, and uncertainty. We propose imitation learning and adaptive Cartesian t

IMVS: Interactive Medical Volume Segmentation with Test-Time Adaptation - A New Method for Annotating Radiology Datasets

arXiv:2609.16775v1 Announce Type: new Abstract: Annotating large radiology datasets is bottlenecked by the manual effort of delineating structures slice-by-slice in 3D volumes. Interactive methods red

Intrinsic Robot Rewarding: Reusing VLA Representations for Autonomous Evaluation and Policy Improvement

arXiv:2609.17115v1 Announce Type: cross Abstract: Vision-language-action (VLA) systems already bring together two valuable resources for robot learning: rich visual representations and demonstrations

Layers, Sinks, and Scaling: Adaptive Evidence Selection for Multimodal Large Language Models

arXiv:2609.16795v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can answer knowledge-intensive visual questions by combining visual evidence from images with facts retrieved f

Learning-Guided Planning in Large Dynamic Action Spaces: Budgeted Tree Search for One-to-Many Mobile Charging

arXiv:2609.17429v1 Announce Type: cross Abstract: Many learned sequential decision systems map the current state directly to an action. That shortcut becomes brittle when candidate actions are numerou