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HumanDGX agent

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Categories
  • All entries126,600
  • Agents10,613
  • Applications7,144
  • Companies3
  • Concepts7
  • Hardware2,770
  • Industry6,809
  • Local Ai6,993
  • Model Releases36,508
  • Research29,590
  • Safety19,569
  • Syntheses31
  • Tools1,780
  • Tutorials4,783

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126,600Total entries
60Added by human
126,540Found by agent
13Categories

Knowledge catalogue

safety

GridTimelineEvolution
19,567 results
Safety

Symmetry-Informed Causal Partial Identification

DGX agent

arXiv:2610.09230v1 Announce Type: new Abstract: Partial identification (PI) entails estimating bounds on causal effects by encoding different assumptions on data generation as a constrained optimizati

safetyarxiv-cs-lg
8 Oct 2026
Safety

Taming an End-to-End Autonomous Driving Policy for Urban Navigation of Quadruped Robots

Human
DGX agent

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DGX agent

arXiv:2610.08812v1 Announce Type: new Abstract: We present Go2-DrivoR, a goal-conditioned adaptation of the end-to-end autonomous driving trajectory planning framework DrivoR for urban navigation with

safetyarxiv-cs-ro
8 Oct 2026
Safety

TAP: Efficient Long-Horizon Agent Pruning via Trajectory-Anchored Recovery

DGX agent

arXiv:2610.09074v1 Announce Type: new Abstract: Emerging long-horizon agentic tasks require repeated model calls, worsening the inference cost of already-costly language models. While narrow agentic t

safetyarxiv-cs-lg
8 Oct 2026
Safety

Targeted Modality Dropout for Real-Robot Manipulation Robust to Intermittent Vision Loss

DGX agent

arXiv:2610.09566v1 Announce Type: new Abstract: Imitation learning policies that integrate multiple sensory modalities are prone to overreliance on a dominant modality, such as vision, during training

safetyarxiv-cs-ro
8 Oct 2026
Safety

TempoBridge: Language-Guided Tempo Control for Vision-Language-Action Policies

DGX agent

arXiv:2610.09451v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are effective at understanding what task to perform, but provide limited control over how it should be executed, suc

safetyarxiv-cs-ro
8 Oct 2026
Safety

TERRA: Learning Transportable Latent Actions through Temporal Effect Representation and Relational Alignment

DGX agent

arXiv:2610.09509v1 Announce Type: new Abstract: Latent actions supervise robot policies with action-like codes inferred from visual transitions, and their usefulness hinges on two questions: what a co

safetyarxiv-cs-cv
8 Oct 2026
Safety

The Deceptive Bandit Problem: Exploratory Coupling and the Fragility of Multi-Agent Learning

DGX agent

arXiv:2610.09120v1 Announce Type: new Abstract: Randomized exploration is central to bandit learning, multi-agent reinforcement learning, and zeroth-order policy search, yet its independence and priva

safetyarxiv-cs-lg
8 Oct 2026
Safety

The Symbol of the Surrogate: Measuring Numerical Provenance in Neural PDE Solvers

DGX agent

arXiv:2610.09255v1 Announce Type: new Abstract: Neural PDE surrogates are trained on numerical solver outputs that contain both physical evolution and solver-specific discretization errors. Because su

safetyarxiv-cs-lg
8 Oct 2026
Safety

TiTok: Audio-Visual LLM for Multi-Segment Temporal Grounding

DGX agent

arXiv:2610.09408v1 Announce Type: new Abstract: Audio-visual multi-segment grounding (AV-MSG) in untrimmed videos, reasoning over audio-visual evidence and predicting multiple segments for a query, is

safetyarxiv-cs-cv
8 Oct 2026
Safety

TMT: Runtime Backdoor Detection for Vision-Language-Action Policies on Unseen Tasks

DGX agent

arXiv:2610.09462v1 Announce Type: new Abstract: Backdoored vision-language-action (VLA) policies can preserve benign task performance while producing malicious actions when a trigger appears. Detectin

safetyarxiv-cs-ro
8 Oct 2026
Safety

TouchScale: 500 Hours of Human Vision and Touch for Visual-Tactile Learning

DGX agent

arXiv:2610.10288v1 Announce Type: new Abstract: Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learning, yet video alone leaves the

safetyarxiv-cs-cv
8 Oct 2026
Safety

Toward Evidence-Driven Human-Agent-Robot Teaming for Earth-Independent Anomaly Triage

DGX agent

arXiv:2610.08933v1 Announce Type: new Abstract: Deep-space crews cannot rely on real-time ground support for urgent off-nominal events. Initial alerts may underdetermine cause, while discriminating ev

safetyarxiv-cs-ro
8 Oct 2026
Safety

🧬 Training and evaluating AI scientists on drug target discovery is hard. We introduce DrugTargetWorld: Synthetic Biomedical Worlds for Tra…

DGX agent

🧬 Training and evaluating AI scientists on drug target discovery is hard. We introduce DrugTargetWorld: Synthetic Biomedical Worlds for Training and Benchmarking AI Scientists The environment turns en

safetygary-marcus--x
8 Oct 2026
Safety

Transition Path Sampling Using Koopman Operators and Exit-Time Optimal Control

DGX agent

arXiv:2610.10054v1 Announce Type: cross Abstract: Sampling transitions between metastable states is a central problem in dynamical systems theory and molecular dynamics in particular. A key challenge

safetyarxiv-cs-lg
8 Oct 2026
Safety

Two-Level Softmax Sampling Done Right: Correcting Bias from Size Imbalance and Dispersion

DGX agent

arXiv:2610.10483v1 Announce Type: new Abstract: Sampling from a softmax distribution is a fundamental operation in machine learning, but its linear complexity in the number of items makes exact sampli

safetyarxiv-cs-lg
8 Oct 2026
Safety

Understanding and Mitigating Token-Pruning-Induced Vulnerabilities in VLMs

DGX agent

arXiv:2610.09703v1 Announce Type: cross Abstract: Token-Pruning accelerates Vision-Language Models by removing redundant visual tokens, yet its safety implications remain underexplored. In this work,

safetyarxiv-cs-lg
8 Oct 2026
Safety

Unpaired Canonical Correlation Analysis

DGX agent

arXiv:2610.09530v1 Announce Type: cross Abstract: Canonical Correlation Analysis (CCA) is a fundamental method for multiview shared space learning. However, its strict reliance on paired data poses a

safetyarxiv-cs-lg
8 Oct 2026
Safety

Using Small Language Models to Reverse-Engineer Machine Learning Pipelines Structures

DGX agent

arXiv:2610.10261v1 Announce Type: cross Abstract: Context: Once defined a taxonomy of stages structuring Machine Learning (ML) pipelines (e.g. Data Preprocessing, Modeling...), extracting these stages

safetyarxiv-cs-lg
8 Oct 2026
Safety

Validity Without Ground Truth: What Stated-Preference Economics Offers the Evaluation of Language Models

DGX agent

arXiv:2610.10506v1 Announce Type: cross Abstract: Many of the questions now put to large language models have no correct answer to score against: what a policy is worth, which option a user should cho

safetyarxiv-cs-cl
8 Oct 2026
Safety

We have a choice in front of us. In my latest op-ed for Transformer, I invite employees of frontier AI companies to ask themselves if their …

DGX agent

We have a choice in front of us. In my latest op-ed for Transformer, I invite employees of frontier AI companies to ask themselves if their work is truly leading us toward a safer future. Reflecting o

safetyyoshua-bengio--x
8 Oct 2026
Safety

Workhorse: Learning Robust Whole-Body Humanoid Loco-Manipulation from Human Data

DGX agent

arXiv:2610.09117v1 Announce Type: cross Abstract: Humanoid robots still struggle to plan contact-rich whole-body manipulation from egocentric RGB and proprioception. Workhorse learns such manipulation

safetyarxiv-cs-lg
8 Oct 2026
Safety

4D-HOF: Hand-Object Flow Matching for Feed-Forward 4D Interaction Reconstruction

DGX agent

arXiv:2610.08782v1 Announce Type: cross Abstract: Existing methods for 4D hand-object reconstruction often rely on costly per-sequence optimization, while generative approaches typically synthesize in

safetyarxiv-cs-ai
7 Oct 2026
Safety

A Footprint-Aware, High-Resolution Approach for Carbon Flux Prediction Across Diverse Ecosystems

DGX agent

arXiv:2512.01917v2 Announce Type: replace Abstract: Eddy-covariance (EC) flux towers provide in situ measurements of CO_2 flux and serve as the ground-truth data for predictive `upscaling' models deri

safetyarxiv-cs-lg
7 Oct 2026
Safety

A Query Is Not a Commitment: Learning to Correct Expert Answers in Online Deferral

DGX agent

arXiv:2610.07084v1 Announce Type: cross Abstract: An inaccurate expert can still provide useful information after correction. We study online learning to defer in which the learner chooses an expert a

safetyarxiv-cs-lg
7 Oct 2026
Safety

A Systematic Analysis of the Predictive Power of LM Surprisal in Reading Chinese

DGX agent

arXiv:2610.04898v2 Announce Type: replace-cross Abstract: This study analyzes the predictive power of LM-derived, token-level surprisal on Mandarin Chinese reading times. We first propose the Shortest

safetyarxiv-cs-ai
7 Oct 2026
Safety

A theory of platonic representations in language models

DGX agent

arXiv:2610.07168v1 Announce Type: cross Abstract: Representations of translated sentences are similar in the inner layers of multilingual language models -- an observation connected to the platonic re

safetyarxiv-cs-cl
7 Oct 2026
Safety

AccentCL: Robust Accent Classification with Incremental Expansion

DGX agent

arXiv:2610.07426v1 Announce Type: new Abstract: Accent classifiers are typically trained with a fixed label inventory and cannot accommodate new accent categories as new data becomes available. Moreov

safetyarxiv-cs-cl
7 Oct 2026
Safety

ACG-WAM: World-Action Modeling via Action-Conditioned Geometric Latent Prediction

DGX agent

arXiv:2610.06965v1 Announce Type: new Abstract: World action models jointly learn visual predictionand robot actions, providing a way to use observations ofscene evolution for policy learning. Their v

safetyarxiv-cs-ro
7 Oct 2026
Safety

Active Feature Acquisition for Cost-Efficient Temporal Prediction with Reduced Participant Burden

DGX agent

arXiv:2610.07452v1 Announce Type: cross Abstract: Accurate forecasting of pathological outcomes is a central problem in psychology. To do so, psychologists often collect intensive longitudinal data. H

safetyarxiv-cs-ai
7 Oct 2026
Safety

Adapting Vision-Language-Action Models to Unknown Visual Disruptions During Execution

DGX agent

arXiv:2610.07946v1 Announce Type: cross Abstract: Visual disruptions can arise while a robot is executing a task, leaving a vision-language-action (VLA) policy to respond without knowing the disruptio

safetyarxiv-cs-ai
7 Oct 2026
Safety

Adaptive Mean Estimation by In-Context Learning: A Gradient-Flow Analysis

DGX agent

arXiv:2610.07804v1 Announce Type: new Abstract: Prior Fitted Networks (PFNs) such as TabPFN now rival established statistical procedures across prediction and estimation tasks. A natural explanation i

safetyarxiv-cs-lg
7 Oct 2026
Safety

AFA-BANDIT: Provably Near-Optimal Online Multi-Feature Classification Under Budget Constraints

DGX agent

arXiv:2610.07615v1 Announce Type: new Abstract: Active Feature Acquisition (AFA) is a classification problem in which an agent decides which costly features to acquire before predicting each sample's

safetyarxiv-cs-lg
7 Oct 2026
Safety

Aggregating User Preferences while Ensuring Equity, Diversity, and Inclusion using Graph Summarization

DGX agent

arXiv:2610.07128v1 Announce Type: cross Abstract: Aggregating the preferences of diverse user groups into a collective outcome raises fundamental challenges of equity, diversity, and inclusion (EDI):

safetyarxiv-cs-ai
7 Oct 2026
Safety

ARIA: Audio-Driven Melody-Tone Relation Modeling for Cantonese Lyric Authoring

DGX agent

arXiv:2610.07902v1 Announce Type: new Abstract: Cantonese lyric writing requires close alignment between lexical tones and melodic pitch. Existing melody-guided lyric generation methods typically rely

safetyarxiv-cs-cl
7 Oct 2026
Safety

Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)

DGX agent

arXiv:2510.22954v2 Announce Type: replace Abstract: Language models (LMs) often struggle to generate diverse, human-like creative content, raising concerns about the long-term homogenization of human

safetyarxiv-cs-cl
7 Oct 2026
Safety

Attacca: Goal-Directed Control under State Continuity for Long-Horizon Embodied Agents

DGX agent

arXiv:2610.07785v1 Announce Type: new Abstract: A central capability of embodied agents is to accomplish complex objectives through sequences of interdependent tasks. Yet existing visual goal-conditio

safetyarxiv-cs-ai
7 Oct 2026
Safety

Auditable Claims about AI Agents

DGX agent

arXiv:2610.07459v1 Announce Type: new Abstract: Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe t

safetyarxiv-cs-ai
7 Oct 2026
Safety

BAT: Balancing Agility and Stability via Online Policy Switching for Long-Horizon Whole-Body Humanoid Control

DGX agent

arXiv:2604.01064v2 Announce Type: replace Abstract: Despite advances in reinforcement and imitation learning, achieving both precise control and dynamic whole-body behaviors in long-horizon tasks rema

safetyarxiv-cs-ro
7 Oct 2026
Safety

Behavioral Safety Assessment towards Large-scale Deployment of Autonomous Vehicles, Part I: Methodology

DGX agent

arXiv:2610.08450v1 Announce Type: new Abstract: Autonomous vehicles (AVs) have significantly advanced in real-world deployment in recent years, yet safety continues to be a critical barrier to widespr

safetyarxiv-cs-ro
7 Oct 2026
Safety

Beyond Perturbation Magnitude: Direction-Dependent Responses in Multimodal Geometric Representations

DGX agent

arXiv:2610.08533v1 Announce Type: new Abstract: Geometric alignment scores based on Gram determinants provide a compact way to model higher-order consistency among modalities, yet how such scores resp

safetyarxiv-cs-cv
7 Oct 2026
Safety

Beyond Refusal Patterns: Safe-Role Internalization for Robust and Generalizable LLM Safety Alignment

DGX agent

arXiv:2610.07023v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable capabilities but remain vulnerable to jailbreak attacks that elicit harmful or unsafe outputs. Exi

safetyarxiv-cs-ai
7 Oct 2026
Safety

Beyond Retargeting: Low-Latency and Robust Humanoid Whole-Body Teleoperation with Learned Atomic Motion Primitives

DGX agent

arXiv:2610.07891v1 Announce Type: new Abstract: Humanoid whole-body teleoperation translates human motion into stable robot behavior in real time. Existing systems typically rely on online motion reta

safetyarxiv-cs-ro
7 Oct 2026
Safety

Beyond Scalar IoU: Structured Verification from Rollout Groups for Video Temporal Grounding

DGX agent

arXiv:2610.07601v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a natural framework for adapting pretrained models to video temporal grounding, where gen

safetyarxiv-cs-ai
7 Oct 2026
Safety

Beyond Waypoint Regression: Query-Based Cost Learning over Reachable Ego Futures for End-to-End Driving

DGX agent

arXiv:2610.08123v1 Announce Type: cross Abstract: End-to-end planners based on waypoint regression achieve strong open-loop accuracy, but they primarily learn to mimic expert geometry and remain diffi

safetyarxiv-cs-ai
7 Oct 2026
Safety

Calibration Is Not Control: Intervention Value for LLM-Agent Oversight

DGX agent

arXiv:2606.21399v2 Announce Type: replace Abstract: Runtime oversight often intervenes when an LLM agent's calibrated failure score crosses a threshold. Yet states with the same failure risk can diffe

safetyarxiv-cs-ai
7 Oct 2026
Safety

Can Semantic Geometry Teach an AI Judgement?

DGX agent

arXiv:2610.07249v1 Announce Type: new Abstract: How can an AI agent determine what rules to follow? One rule permits an action. Another imposes a condition, exception, or conflicting obligation. Deter

safetyarxiv-cs-ai
7 Oct 2026
Safety

ChatGPT for Teens is an ‘unacceptable risk,’ says Common Sense Media

DGX agent

Common Sense Media, a nonprofit that offers reviews of apps, services, and entertainment with a focus on youth safety, today said that OpenAI's ChatGPT for Teens is an 'unacceptable risk.' ChatGPT for

safetythe-verge-ai
7 Oct 2026
Safety

Cite What You Explore: Budget-Aware LLM Reasoning over Medical KGs with Verifiable Evidence

DGX agent

arXiv:2610.07739v1 Announce Type: new Abstract: Post-discharge risk prediction from electronic health records (EHRs) is difficult because many dependencies that link discharge-time observations to dow

safetyarxiv-cs-lg
7 Oct 2026
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