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GAUGE: Granularity-Adaptive Counterfactual Gating of Evidence for Incomplete Multimodal Classification

arXiv:2608.05608v1 Announce Type: cross Abstract: Multimodal classification typically assumes all modalities are available, yet real-world inputs are often incomplete. Imputation and dynamic fusion ca

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Research

Gender-Based Heterogeneity in Youth Privacy-Protective Behavior for Smart Voice Assistants: Evidence from Multigroup PLS-SEM

DGX agent

arXiv:2603.27117v2 Announce Type: replace-cross Abstract: This paper investigates how gender shapes privacy decision-making in youth smart voice assistant (SVA) ecosystems. Using survey data from 469

researcharxiv-cs-ai

7 Aug 2026

GenGA: Editable and Data-Grounded Graphical Abstract Generation for Academic Papers

arXiv:2608.05478v1 Announce Type: cross Abstract: Graphical Abstracts (GAs) visually summarize the key findings of academic papers, playing a crucial role in facilitating the understanding of research

safetyarxiv-cs-cl

GeniWorld: A Generalizable Interactive World Model for Robotic Manipulation via Visual Actions

arXiv:2608.06332v1 Announce Type: new Abstract: Generalist robot policies exhibit strong capabilities, but their robustness in complex and unseen environments remains limited. Scaling robot learning a

safetyarxiv-cs-ro

Grad-CAM for Vision Transformers: A Systematic Taxonomy and Audit of Methodological Ambiguity in Explainable AI

arXiv:2608.05258v1 Announce Type: new Abstract: Gradient-weighted Class Activation Mapping (Grad-CAM) is widely used to visualize model decisions, but it was originally formulated for convolutional ne

GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning

arXiv:2604.02721v3 Announce Type: replace Abstract: Competitive programming remains one of the last few human strongholds in coding against AI. The best AI system to date still underperforms the best

GROM: Gradient-Free Rapid One-Shot Machine Unlearning

arXiv:2608.05783v1 Announce Type: cross Abstract: Machine unlearning has become a critical capability for safely removing specific, sensitive knowledge from large language models (LLMs). Current state

Grounded Well-Condition Anomaly Detection on the Volve Field: Constructed Labels, a Baseline, and a Dual-Head Model

arXiv:2608.05685v1 Announce Type: new Abstract: Most public benchmarks for machine-condition monitoring come from test rigs, where faults are induced on purpose and every event is known. Real producti

GSBF: Gaussian Splatting for Environment-Aware Beamforming

arXiv:2608.05896v1 Announce Type: new Abstract: Beamforming plays a key role in multiple-input-multiple-output (MIMO) communication systems. However, conventional beamforming design normally requires

safetyarxiv-cs-ai

GST-Bench: Can VLMs Develop Global Spatial Awareness from Video?

model-releasesarxiv-cs-cv

arXiv:2608.05747v1 Announce Type: new Abstract: Spatial intelligence is fundamental to embodied agents, yet existing benchmarks focus on local spatial perception from single or few viewpoints, overloo

Handling Missing Data in Probabilistic Regression Trees

arXiv:2608.06195v1 Announce Type: cross Abstract: Probabilistic Regression Trees (PRTrees) are a smooth and consistent alternative to classical regression trees, producing continuous predictions throu

applicationsarxiv-cs-lg

Hardware Keystores for AI Agent Signing Workflows: A Zero-Trust MCP Enforcement Architecture

arXiv:2608.06130v1 Announce Type: cross Abstract: AI agents performing cryptographic operations (signing Git commits, authenticating API calls, issuing certificates) currently store private keys in so

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization

arXiv:2608.06301v1 Announce Type: new Abstract: As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts,

HERA: Historical Evidence Routing Adapter for Physical Prediction in Latent World Models

arXiv:2608.05523v1 Announce Type: new Abstract: Predictive video models have emerged as promising world models by learning latent visual dynamics from large-scale video. Yet these models remain challe

HERALD: Counterfactual Audits and Minimal Repairs for Proof-of-Retrieval Rewards

arXiv:2608.06012v1 Announce Type: new Abstract: Search-agent rewards mix answer quality, citation grounding, tool cost, and anti-hacking terms; a high score therefore need not imply that cited evidenc

Hierarchical Flow Matching for 3D Point Cloud Generation

arXiv:2608.05557v1 Announce Type: new Abstract: Generating high-quality 3D point clouds requires capturing both global shape topology and local geometric details. Existing flow-based methods rely on c

Hierarchical Latent Prediction for Language Models

arXiv:2608.05806v1 Announce Type: cross Abstract: While standard Next-Token Prediction (NTP) lays the foundation of language model pre- training, its teacher-forced training paradigm may not be optima

researcharxiv-cs-ai

Agents

Hierarchical Server Architecture for Agentic Science

arXiv:2608.05332v1 Announce Type: cross Abstract: Agentic science is transforming the landscape of computational work, extending to scientific pipelines and workload managers. The workloads require sp

agentsarxiv-cs-ai

Hijacking Robots with a Piece of Paper: A Systematic Study of Physical Prompt Injection in VLM-Controlled Robots

arXiv:2608.05715v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as planners in robotic systems, where they translate natural-language commands into executable

HOPE: Hand-Object Pressure Estimation from Monocular Videos

arXiv:2608.06192v1 Announce Type: new Abstract: Estimating physical pressure from vision is essential for understanding contact-rich hand-object interaction. However, prior vision-based pressure estim

How Far Do Simple Transformations Translate Across Text Embedding Models?

arXiv:2608.05980v1 Announce Type: new Abstract: We investigate whether simple transformations can translate representations across heterogeneous text embedding models. Understanding how independently

researcharxiv-cs-lg

How Much Reconstruction Does Quantum Machine Learning Need? Late Fusion of Independently Trained Quantum Subcircuits

model-releasesarxiv-cs-lg

arXiv:2608.05595v1 Announce Type: cross Abstract: Circuit cutting lets a large quantum neural network (QNN) run as independent subcircuits on small devices, but rebuilding its outputs by reconstructio

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs

arXiv:2608.05759v1 Announce Type: new Abstract: Recognizing new and rare words - named entities, acronyms, domain specific special words, and other items scarce in training data - remains a key challe

tutorialsarxiv-cs-cl

Human-Like Anaphor Resolution in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2608.05630v1 Announce Type: new Abstract: Anaphors are expressions that refer to other expressions, called antecedents. The process of connecting the two is called resolution. Cognitive science

Hybrid-Adaptive Thread Tuning to Mitigate Simulation Execution Bottlenecks in High-Performance Reinforcement Learning Inference

arXiv:2608.06025v1 Announce Type: new Abstract: In simulation-in-the-loop decision-making systems, reinforcement learning (RL) inference is often constrained by simulator-side execution overhead, wher

tutorialsarxiv-cs-lg

Hybrid Machine Learning Framework for Herd-Level Cattle Growth Pattern and Weight Gain Forecasting in Grazing-Based Production Systems

arXiv:2608.06001v1 Announce Type: new Abstract: Commercial grazing systems yield irregular livestock observations, which challenge cattle growth forecasting. This study developed a hybrid machine lear

Hybrid Probabilistic Zonotopes for Identifiable and Refinable Predictive Uncertainty

arXiv:2608.05454v1 Announce Type: new Abstract: Probabilistic prediction heads in neural networks typically output either a Gaussian mixture or a single conformal region. Neither separates the distinc

researcharxiv-cs-lg

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging

arXiv:2608.05541v1 Announce Type: new Abstract: Evolution Strategy (ES) is a promising alternative to gradient-based fine-tuning for resource-constrained Large Language Model (LLM) reasoning. However,

Hypothesis Testing with Conditional Queries: Learnability and the Value of Interaction

arXiv:2608.06262v1 Announce Type: new Abstract: Model evaluations may fix all tests before observing any responses or select later tests using earlier responses. We study this choice in a conditional-

safetyarxiv-cs-lg

HyTBE: Hyperbolic Target-Background Expert Model for Cross-Domain Infrared Small Target Detection

arXiv:2608.05771v1 Announce Type: cross Abstract: Infrared small target detection (IRSTD) has achieved substantial progress under domain-consistent evaluation, yet detector performance often degrades

researcharxiv-cs-ai

Agents

iARCS: Iterative Agentic RL for Controllable 3D Scene Generation

arXiv:2608.06161v1 Announce Type: new Abstract: Synthetic 3D scene generation is increasingly used as a data source for computer vision and embodied AI, but existing generators often optimize perceptu

agentsarxiv-cs-ai

Hardware

IcFuzz: Fuzzing Isaac Sim with Semantic Stage Guidance and Multi-level Mutation

arXiv:2608.06088v1 Announce Type: new Abstract: Robotics simulators serve as a foundational infrastructure for embodied AI, facilitating safe and scalable robotic system development. NVIDIA Isaac Sim

hardwarearxiv-cs-ro

IDperturb: Enhancing Variation in Synthetic Face Generation via Angular Perturbation

arXiv:2602.18831v2 Announce Type: replace Abstract: Synthetic data has emerged as a practical alternative to authentic face datasets for training face recognition (FR) systems, especially as privacy a

applicationsarxiv-cs-cv

IFlowNets: Extending Generative Samplers to Learn Strategies in Incomplete Information Games

arXiv:2608.05422v1 Announce Type: new Abstract: While many algorithms blend reinforcement learning (RL) with counterfactual regret (CFR) methods to leverage tradeoffs in computational speed and perfor

tutorialsarxiv-cs-lg

IMMENSE: Inductive Multi-perspective User Classification in Social Networks

arXiv:2608.05259v1 Announce Type: cross Abstract: Online social networks increasingly expose people to users who propagate discriminatory, hateful, and violent content. Young users, in particular, are

Improving Interoperability among Defence and National Security Ontologies: Analysis and Evaluation Tasks

arXiv:2608.05867v1 Announce Type: new Abstract: The use of ontologies and knowledge graphs is becoming increasingly widespread in the defence and national security domain. Numerous ontologies have bee

safetyarxiv-cs-ai

Improving the Realism of Synthetic Clinical Benchmarks Under Utility Constraints

arXiv:2608.06265v1 Announce Type: new Abstract: Synthetic clinical benchmarks for enterprise AI agents can pass existing utility checks and still remain structurally unrealistic, especially in privacy

Local Ai

In-Context Forcing: Uncovering Context Effects in Autoregressive Video Diffusion

arXiv:2608.05237v1 Announce Type: cross Abstract: Current few-step autoregressive video diffusion models depend on previous fully denoised clean frames as context for all denoising steps of the curren

local-aiarxiv-cs-ai

In-Context VLA: Endowing Vision-Language-Action Models with Language via In-Context Post-Training and Agentic Tool Use

arXiv:2608.05738v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become the dominant recipe for generalist manipulation, yet they are almost universally trained by behavior clo

safetyarxiv-cs-ro

Innocent Panels, Hateful Stories: Evaluating and Detecting Hateful Intent in Multi-Turn Visual Story Generation

arXiv:2608.05210v1 Announce Type: cross Abstract: Picture books and comics have long been used to disseminate hateful narratives because they are easily understood even by children, as exemplified by

Local Ai

Innovation-Residual Auditing of Autonomous Analysis Agents: Localization, Detection Limits, Error Control, and Identifiability

arXiv:2608.05490v1 Announce Type: new Abstract: Autonomous agents now carry out entire data analyses, selecting cohorts, joining tables, and fitting models with little step-by-step supervision. When s

local-aiarxiv-cs-ai

Inspecting Training Dynamics of Similarity Development in Supervised Vision Networks

arXiv:2505.21338v2 Announce Type: replace Abstract: For trustworthy and human-aware artificial intelligence, models should be evaluated beyond accuracy, among others through error predictability and s

safetyarxiv-cs-cv

Integrating Human Linguistic Insights into AI: Theory-Driven Representation for Multilingual Text-to-Speech

arXiv:2204.07228v2 Announce Type: replace Abstract: This paper explores the integration of human linguistic insights into multilingual text-to-speech (TTS) systems by evaluating the Featurally Undersp

researcharxiv-cs-cl

Integrating Implicit and Explicit Relational Biases through Graph-Based Multiple Instance Learning: A Case Study in Skin Lesion Diagnosis

arXiv:2608.06037v1 Announce Type: new Abstract: Relational inductive biases are essential for capturing structural dependencies among data. This study investigates a dual-level relational framework fo

tutorialsarxiv-cs-ai

Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising

arXiv:2510.05589v3 Announce Type: replace-cross Abstract: Effective time series forecasting enables various real-world applications, benefiting from the proliferation of mobile devices. However, the v

Investigating Artificial Intelligence Digital Sovereignty in Mobile Shopping Apps: A Case Study of Nigeria

arXiv:2608.06364v1 Announce Type: cross Abstract: The use of e-commerce mobile applications is expanding in Nigeria, creating both opportunities and risks, including fraud and reduced user control ove

Invisible Shortcuts: Why Vision Encoders Know Your Camera

arXiv:2608.05424v1 Announce Type: new Abstract: Deep vision models exploit shortcuts, relying on cues that correlate with supervision signals. Prior work has focused on visible biases, such as object-

IPV-Bench: Benchmarking Image Protection Methods under Diverse Image-to-Video Generation Scenarios

model-releasesarxiv-cs-cv

arXiv:2603.26154v2 Announce Type: replace Abstract: Image-to-video (I2V) generation models can be misused to animate a single image into a convincing fake video, motivating perturbation-based image pr