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G3Ego: Gaze-Guided Graphs for Egocentric Action Understanding

arXiv:2608.20157v1 Announce Type: new Abstract: Egocentric action understanding is often addressed using large video models pretrained on extensive exocentric datasets. However, many first-person acti

researcharxiv-cs-cv

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Gallileo-4D: Frozen Backbone Ensemble for Dynamic 4D Reconstruction

DGX agent

arXiv:2608.19743v1 Announce Type: new Abstract: We describe our entry to the PhysAI Dynamic 4D Reconstruction Challenge, which placed third of 27 teams at 0.58356 APD on the final leaderboard, without

model-releasesarxiv-cs-cv

21 Aug 2026

Gen AI in Proof-based Math Courses: A Pilot Study

arXiv:2509.13570v2 Announce Type: replace Abstract: With the rapid rise of generative AI in higher education, understanding how students use AI is increasingly important. This exploratory study examin

safetyarxiv-cs-ai

Generating Diverse Personas for User Simulators to Test Interview Dialogue Systems

arXiv:2608.19549v1 Announce Type: new Abstract: This paper addresses the issue of the significant labor required to test interview dialogue systems. While interview dialogue systems are expected to be

researcharxiv-cs-cl

Generative AI Use in Entrepreneurship: An Integrative Review and an Empowerment-Entrapment Framework

arXiv:2604.02567v2 Announce Type: replace-cross Abstract: Despite the growing use of generative artificial intelligence (GenAI) in entrepreneurship, research on its impact remains fragmented. To addre

GenMatch: An End-to-End Generative Matching Framework for Micro-View Order-Dispatching in Ride-Hailing

arXiv:2608.19751v1 Announce Type: new Abstract: Micro-View Order-Dispatching assigns available drivers to passenger orders within each dispatch batch and is critical to the service quality and operati

applicationsarxiv-cs-ai

GOAG: Generative and Object-Agnostic Grasp Planner for Dexterous Robotic Manipulation

arXiv:2608.19759v1 Announce Type: cross Abstract: Multifingered grasping is a crucial robotic skill, but current deep-learning grasp planners often struggle to generalize to new objects because they a

applicationsarxiv-cs-ai

GRACE: Grounded Reasoning via Adapter Composition and Evidence-Aware Calibration for Educational Visual Question Answering

model-releasesarxiv-cs-cv

arXiv:2608.19355v1 Announce Type: cross Abstract: Educational visual question answering, or VQA, requires models to solve curriculum-oriented multiple-choice questions using both language and visual e

Gravitational-wave parameter estimation with machine-learning generated surrogate waveforms

arXiv:2608.20222v1 Announce Type: cross Abstract: The worldwide network of gravitational-wave detectors have detected more than 350 binary coalescence events till date. Future third-generation detecto

Gravity-aware partially calibrated absolute pose estimation from affine- or rotation-covariant features

arXiv:2608.20056v1 Announce Type: new Abstract: Inertial measurement units (IMUs) are now standard in most consumer devices, such as smartphones, drones, and extended reality (XR) headsets. By fusing

researcharxiv-cs-cv

Green BOA: Determining the environmental break-even point for ML-based data compression

arXiv:2608.19994v1 Announce Type: new Abstract: We summarise the outcome of two summer internship projects based at the University of Manchester, focused on the break-even point in terms of environmen

researcharxiv-cs-lg

GridCodex: A RAG-Driven AI Framework for Power Grid Code Reasoning and Compliance

arXiv:2508.12682v2 Announce Type: replace Abstract: The global shift towards renewable energy presents unprecedented challenges for the electricity industry, making regulatory reasoning and compliance

Grounded verification of chemical and materials reasoning: detection is the bottleneck

arXiv:2607.17417v2 Announce Type: replace Abstract: Language models are moving into chemistry and materials discovery workflows, where a wrong molecular formula, space group, or formation energy can s

researcharxiv-cs-lg

Growth Without Us: Machine Consumers, Corporate Circularity, and the Decoupling of GDP from Humanity after AGI

arXiv:2608.20231v1 Announce Type: cross Abstract: The standard objection to full automation is demand-side: if humans earn nothing, who buys the output? This confuses an accounting role with a biologi

safetyarxiv-cs-ai

Guided Diffusion by Optimized Loss Functions on Relaxed Parameters for Inverse Material Design

model-releasesarxiv-cs-cv

arXiv:2602.15648v2 Announce Type: replace-cross Abstract: Inverse design problems are common in engineering and materials science. The forward direction, i.e., computing output quantities from design

Hallucination as a Feature, not a Defect: Evaluating a multi-agent architecture to transform speculative language-model outputs into testable scientific hypotheses

arXiv:2608.19206v1 Announce Type: cross Abstract: Contemporary Large Language Models (LLMs) are increasingly aligned to suppress hallucinations, prioritizing factual retrieval over combinatorial creat

safetyarxiv-cs-ai

Tutorials

HandMvNet: Real-Time 3D Hand Pose Estimation Using Multi-View Cross-Attention Fusion

arXiv:2608.20093v1 Announce Type: new Abstract: In this work, we present HandMvNet, one of the first real-time method designed to estimate 3D hand motion and shape from multi-view camera images. Unlik

tutorialsarxiv-cs-cv

HarmoHOI: Harmonizing Appearance and 3D Motion for Multi-view Hand-Object Interaction Synthesis

arXiv:2607.17097v2 Announce Type: replace Abstract: Hand-Object Interaction (HOI) synthesis is a cornerstone for animation production and embodied AI. Despite the strong priors of video foundation mod

applicationsarxiv-cs-cv

HARP: Hierarchical Adaptive Ranking with Preference-Adaptive Fusion for Query-Based CVE Prioritization

arXiv:2608.19430v1 Announce Type: cross Abstract: Vulnerability prioritization is inherently preference dependent, since the same CVE can receive different remediation priority under different operati

safetyarxiv-cs-cl

HBVLA: Pushing 1-Bit Post-Training Quantization for Vision-Language-Action Models

arXiv:2602.13710v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models enable instruction-following embodied control, but their large compute and memory footprints hinder deployment o

safetyarxiv-cs-lg

HealMed: Multilingual Evaluation of Large Language Models in Medicine

model-releasesarxiv-cs-cl

arXiv:2608.19981v1 Announce Type: new Abstract: We present HealMed, an expert-reviewed benchmark for multilingual evaluation of large language models in medicine. HealMed contains 1,000 examples in ea

Hear2Act: Benchmarking When Prosody Should Change What an Assistant Does

arXiv:2608.19515v1 Announce Type: new Abstract: Prosodic cues can convey task-relevant information that alters the trajectory and outcome of a task-oriented dialogue, even when the words themselves re

researcharxiv-cs-cl

Heteroscedastic Neural Surrogate Modeling for Robust and Rapid Bayesian Inference in Fusion Plasma Diagnostics

arXiv:2608.19377v1 Announce Type: cross Abstract: Bayesian inference via Markov Chain Monte Carlo (MCMC) provides effective parameter estimation, but its real-time application in complex physical syst

HiRA-CAM: Preserving Fine-Grained Spatial Relevance in Gradient-Based Visual Explanations

arXiv:2608.19407v1 Announce Type: cross Abstract: Deep Learning models can include billions of parameters or more, making it difficult to explain their internal transformations and outputs. However, e

HiTac-WAM: A Hierarchical Tactile World Action Model for Contact-Rich Robot Manipulation

arXiv:2608.19574v1 Announce Type: new Abstract: World action models jointly predict future visual observations and actions, whereas existing tactile-aware variants typically represent future touch as

researcharxiv-cs-ro

Holtercare-Bench: A Multimodal Benchmark for Evaluating Long-Term Dynamic ECG Analysis

arXiv:2608.19297v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) excel in medical applications, most of them favor static images or short-term signals. In the critical fi

Tutorials

How to Navigate Uncertainty About AI Consciousness

arXiv:2608.19215v1 Announce Type: new Abstract: Given deep uncertainty about the possibility of artificial consciousness, it is unclear how we should treat potentially sentient AI. On the one hand, we

tutorialsarxiv-cs-ai

HT-Bench: Benchmarking and Learning Dexterous Full-Hand Tactile Representations with Egocentric Vision

model-releasesarxiv-cs-ro

arXiv:2606.19161v2 Announce Type: replace Abstract: Establishing a universal benchmark for tactile representation learning in robotic manipulation remains challenging due to the diversity of tactile s

Hybrid Feedback Sampling for Sample-Efficient Model Predictive Control

arXiv:2608.19443v1 Announce Type: new Abstract: Thanks to its parallelizability and flexibility, sampling-based Model Predictive Control (MPC) has become widely popular for controlling real-world robo

safetyarxiv-cs-ro

HYDRA: A Heterogeneous Chiplet DSE Framework for Serving Dynamic Hybrid LLM Workloads

arXiv:2608.19395v1 Announce Type: cross Abstract: Hybrid Transformer-Mamba large language models (LLMs) enhance long-context efficiency, but their heterogeneous computation and communication patterns

ID-VTG: Image-Disambiguated Video Temporal Grounding

arXiv:2608.20127v1 Announce Type: new Abstract: Video Temporal Grounding (VTG) faces significant challenges when natural language queries must distinguish between multiple events involving visually si

researcharxiv-cs-cv

Improved Confidence Estimates for Black-Box Large Language Models

arXiv:2608.19323v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) is essential for the safe deployment of large language models (LLMs). Existing methods, from verbalized confidence to

applicationsarxiv-cs-ai

Tutorials

In Two Minds about Lifelong Learning: Exploring Hemispheric Redundancy and Specialisation in Neural Models

arXiv:2608.19514v1 Announce Type: cross Abstract: Persistent intelligent systems require the ability to learn continually, but current machine learning approaches face significant challenges in this a

tutorialsarxiv-cs-ai

Inadvertent Context Leakage in Language Models

arXiv:2608.19857v1 Announce Type: new Abstract: For AI agents to be useful beyond simple chat, they must hold sensitive user context such as calendars, credentials, health records, and financial data.

Incident-Data Robustness Analysis of the OWASP Top 10 for LLM Applications (2026): How a Community-Expert Ranking Holds Up Against a Large-Scale LLM Incident Corpus

arXiv:2608.19266v1 Announce Type: cross Abstract: The OWASP Top 10 for LLM Applications ranks the risks that a community of security practitioners judges most important. We ask a narrower question: ch

Agents

Inducing Task Models from Computer-Use Traces

arXiv:2608.20319v1 Announce Type: cross Abstract: Naturalistic computer-use traces, passively recorded screenshots and mouse or keyboard actions, are a valuable resource for deriving symbolic, auditab

agentsarxiv-cs-ai

Information on trajectories: martingales and random times

arXiv:2608.20337v1 Announce Type: cross Abstract: Accounting for information flow on the path space of trajectories of a nonnegative martingale yields exact variational identities for it, even at arbi

researcharxiv-cs-lg

Inject, Align, Recover: Staged Post-Training for Retrieval-Free Document Knowledge Internalization

model-releasesarxiv-cs-ai

arXiv:2608.20281v1 Announce Type: cross Abstract: Large language models often fail to answer questions about a bounded document collection when the source documents are not retrieved at inference time

InsufficiencyBench: Evaluating LLM legal advice on underspecified user queries

model-releasesarxiv-cs-ai

arXiv:2608.20220v1 Announce Type: new Abstract: Legal AI systems are increasingly used to answer legal questions, yet existing benchmarks assume queries arrive fully specified. In practice, users omit

Inter-X++: A Comprehensive Benchmark for Multimodal Human-Human Interaction Analysis

model-releasesarxiv-cs-cv

arXiv:2608.20312v1 Announce Type: new Abstract: The capability to perceive and synthesize human-human interactions is fundamental to developing intelligent digital human systems. However, existing dat

Interaction valence reveals contrasting social networks in dairy cattle

arXiv:2608.19222v1 Announce Type: new Abstract: Social relationships shape access to resources, exposure to conflict and group stability, yet automated livestock monitoring typically treats behaviour

Interpretable Feature Learning for RF Fingerprinting via Polar MKANs

arXiv:2608.19881v1 Announce Type: cross Abstract: Radio frequency (RF) fingerprinting authenticates wireless devices from hardware-induced I/Q impairments, typically with deep learning feature extract

Interrupting the Loop: Periodic Subject Changes Raise Judged Surprise and Connection in Base Language Models

arXiv:2608.19893v1 Announce Type: cross Abstract: Where does the novelty a base language model produces with no task come from, and what can an LLM judge of a long stream actually see? We dismantle a

Kahler landscapes for complex neural network descents and guarantees including a search and destroy of the Calabi-Yau manifold

arXiv:2608.19584v1 Announce Type: new Abstract: We study landscapes for complex-parameterized networks. Our approach is motivated with an information-theoretic manifold perspective of the parameter an

Keeping the Franka Emika Panda alive: a ROS 2 stack with a reliable position interface

arXiv:2608.19740v1 Announce Type: new Abstract: This paper presents an open-source software stack that restores ROS 2 support for the Franka Emika Panda robot while resolving the long-standing unrelia

researcharxiv-cs-ro

Learn for Variation: Efficient AAV Trajectory Learning through a Differentiable Wireless World Model

arXiv:2603.18853v3 Announce Type: replace-cross Abstract: Autonomous aerial vehicles (AAVs) enable data collection for sixth-generation Internet-of-Things networks, but their trajectories couple nonli

safetyarxiv-cs-lg

Learning-Augmented Power System Operations: A Unified Optimization View

arXiv:2505.05203v3 Announce Type: replace-cross Abstract: With the increasing penetration of renewable energy and inverter-based resources, traditional physics-based power-system operation faces growi

Learning-Based Speed Estimation from Accelerometer-Only Inertial Sensing

model-releasesarxiv-cs-ai

arXiv:2401.07468v4 Announce Type: replace-cross Abstract: The proposed model, CarSpeedNet, estimates scalar vehicle speed from a window of three-axis smartphone acceleration, without gyroscope, wheel-