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Guardian: Detecting Robotic Planning and Execution Errors with Vision-Language Models

arXiv:2512.01946v4 Announce Type: replace-cross Abstract: Robust robotic manipulation requires reliable failure detection and recovery. Although recent Vision-Language Models (VLMs) show promise in ro

safetyarxiv-cs-cv

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Model Releases

GuardianBench: A Same-Scene Instruction-Contrastive Benchmark for Latent Contextual Risk in Embodied AI

DGX agent

arXiv:2608.21928v1 Announce Type: new Abstract: In embodied AI, safety risk can be latent: a benign instruction and a safe scene become hazardous only when composed. Prior work has advanced embodied s

model-releasesarxiv-cs-ai

25 Aug 2026

GuardPaint:SpeculativeSafetyDecodingforText-to-ImageGeneration

arXiv:2608.21869v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models offer powerful visual generation, but their controllability creates a critical safety challenge: adversarial prom

GUI-Primitives: Diagnosing Spatial Reasoning Failures in Vision-Language GUI Grounding

model-releasesarxiv-cs-cl

arXiv:2608.21832v1 Announce Type: new Abstract: Computer-use agents ground natural-language instructions in screenshots to locate interface elements, yet existing benchmarks do not isolate whether mod

Guidance for Prior Change via Density Ratio Estimation

arXiv:2608.21729v1 Announce Type: cross Abstract: Simulation-Based Inference (SBI) serves as a vital framework for parameter inference in scientific fields where simulators involve intractable likelih

Guided Riemannian Optimization (GuRO): Bridging Model Predictive Control and Decision Transformers

model-releasesarxiv-cs-ro

arXiv:2608.23204v1 Announce Type: new Abstract: Decision-making in high-dimensional, nonlinear systems remains a central challenge in robotics. While model-based methods like Model Predictive Control

Local Ai

GuidedFlow: An Attention-Guided Framework for Anomaly Detection in Additive Manufacturing

arXiv:2608.22789v1 Announce Type: new Abstract: Additive Manufacturing (AM) plays a vital role in the ongoing industrial revolution. However, quality control remains crucial and challenging due to pri

local-aiarxiv-cs-cv

Hack-Verifiable Terminal Bench: Evaluating Reward Hacking in Terminal Tasks

arXiv:2608.22103v1 Announce Type: new Abstract: As agents grow more capable and autonomous, their tendency to reward hack, satisfying a task's checks while violating its intent, becomes an increasingl

Agents

HANSARD: A Reference Architecture for Forensic Readiness, Runtime Witnessing, and Graded Attribution in Autonomous Multi-Agent AI Systems

arXiv:2608.22512v1 Announce Type: new Abstract: Autonomous multi-agent systems nowadays act in finance, software supply chains, and security operations. Already, the first largely AI-orchestrated intr

agentsarxiv-cs-ai

Hate Speech Classification In Roman Urdu: A Comparative Study On Parameter Efficient Fine-Tuning And Prompt Engineering

arXiv:2608.21408v1 Announce Type: new Abstract: Due to the widespread accessibility of the internet and social media, toxic and hateful con-tent has grown exponentially, causing significant distress a

HAWKEYE: Seeing One Layer Deeper -- A Cohesion-Aware Structural Channel for Temporal Link Prediction

arXiv:2608.22727v1 Announce Type: cross Abstract: State-of-the-art temporal-link-prediction (TLP) models are, in essence, multi-channel information aggregators: they combine an interaction-history cha

HeatTok: Enhancing Remote Sensing Image Understanding via Thermodiffusion-based Tokenization

arXiv:2608.22485v1 Announce Type: new Abstract: Current visual tokenizers in Multimodal Large Language Models (MLLMs) predominantly rely on patch-based partitioning, which causes severe semantic mixtu

HelaBERT: Enhancing Sinhala Language Understanding with Dual Pooling Classification Head

arXiv:2608.22922v1 Announce Type: new Abstract: We present HelaBERT, a family of two BERT-based masked language models pre-trained from scratch on approximately 1 billion tokens of Sinhala text source

researcharxiv-cs-cl

HERO: Human-profile Enhanced Retrieval Optimization Framework for Long-term Agent Memory

arXiv:2608.22310v1 Announce Type: new Abstract: Long-term memory is crucial for personalized responses and long-horizon agent interactions. Existing methods often rely on LLMs to compress or rewrite d

Hidden in the Request: Explaining Unethical LLM Compliance through Token Relevance

arXiv:2608.23264v1 Announce Type: new Abstract: Although Large Language Models (LLMs) are aligned to optimize for both helpfulness and harmlessness, these dual objectives may conflict, inevitably lead

HiDiffTIR: Hierarchical Difficulty-Aware Policy Optimization for Multi-Turn Tool-Integrated Reasoning

arXiv:2608.21863v1 Announce Type: cross Abstract: Tool-Integrated Reasoning (TIR) is a fundamental capability for LLM agents to solve complex tasks by interacting with external tools iteratively. Rein

Hierarchical Book Organization for Learning-Resource Discovery using Dual-Path Graph Convolutions

arXiv:2512.21076v2 Announce Type: replace-cross Abstract: The growing availability of books and textual materials in digital learning environments necessitates reliable semantic organization to suppor

Hierarchical Exponential-Gaussian Mixtures for Watch-Time Distribution Prediction

arXiv:2608.23356v1 Announce Type: cross Abstract: Accurate watch-time (WT) prediction is an important requirement for short-video recommendations. Yet WT distributions are near-zero-inflated, long-tai

Hierarchy-Aware Semantic Losses for Knowledge Graph Link Prediction

arXiv:2608.22981v1 Announce Type: new Abstract: Knowledge graphs are often accompanied by ontological class hierarchies that encode valuable semantic information, yet many link prediction methods eith

Hierarchy-Aware Supervised Uncertainty Estimation for Black-box LLM Taxonomic Reasoning

arXiv:2608.22839v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for scientific decision support, yet reliable confidence estimation remains difficult in black-box

HiFiC-G: Adapting HiFiC for Hi-C Contact Matrices

arXiv:2608.21446v1 Announce Type: cross Abstract: We study whether the loss design of High-Fidelity Generative Image Compression (HiFiC), a GAN-based neural codec originally built for natural photogra

Higher-Order Kuramoto Oscillator Network for Dense Associative Memory

arXiv:2507.21984v2 Announce Type: replace-cross Abstract: Networks of phase oscillators can serve as dense associative memories when they incorporate genuine many-body coupling beyond the classical Ku

researcharxiv-cs-lg

Local Ai

HiMA-MDD: A Hierarchical Multi-Agent Harness for Interpretable Multimodal Depression Detection in Clinical Interviews

arXiv:2608.21868v1 Announce Type: new Abstract: Depression assessment from multimodal clinical interviews requires integrating dispersed evidence from multiple symptoms into a coherent PHQ-8 profile.

local-aiarxiv-cs-ai

Hints, Critics, and Teachers: Prior Injection for Sparse-Reward RL in Vision-Language Math Reasoning

arXiv:2608.21811v1 Announce Type: new Abstract: Reinforcement learning for vision-language math reasoning starves under sparse reward: on a pool of 20,830 visual-math problems where Qwen2-VL-2B answer

HIRA: A Human-in-the-Loop Retrieval-Augmented Cascade for Document Classification in Regulated Industries

arXiv:2608.21792v1 Announce Type: new Abstract: Document classification in regulated industries is constrained by data residency, limited cold-start labels, scarce review capacity, and costly model-go

HiViS: Hiding Visual Tokens from the Drafter for Speculative Decoding in Vision-Language Models

arXiv:2509.23928v3 Announce Type: replace-cross Abstract: Speculative decoding has proven effective for accelerating inference in Large Language Models (LLMs), yet its extension to Vision-Language Mod

HOT-POT: Optimal Transport for Sparse Stereo Matching

model-releasesarxiv-cs-cv

arXiv:2601.12423v2 Announce Type: replace Abstract: Stereo vision between images faces a range of challenges, including occlusions, motion, and camera distortions, across applications in autonomous dr

How Agents Represent Humans: Human-Directed Stereotypes in an Open Agent Social Network

arXiv:2608.22192v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in persistent social environments, where generated claims can be posted, replied to, remembered, and reused.

safetyarxiv-cs-cl

How AI Assistance Affects Human Skill Development: A Study of Learning with Logic Puzzles

arXiv:2608.23543v1 Announce Type: new Abstract: While AI assistance can improve human task performance in the short term, it may also undermine the development of skills in the longer term. We examine

How Architecture and Training Affect TPC Representations Across Experiments

arXiv:2608.21756v1 Announce Type: cross Abstract: Deep-learning efforts have increasingly shifted toward foundation model approaches. In experimental physics, this allows models and learned representa

How Does Research Evolve? Tracing Cross-Domain Trajectories in NLP, ML, and CV Through Claim-Grounded Typed Citations

model-releasesarxiv-cs-cl

arXiv:2606.22342v2 Announce Type: replace Abstract: How does research evolve, and can we trace it at the level of individual claims? Scientific progress is not simply a uniform accumulation of facts.

How Merge-Tolerant Are Vision Transformers for Wheat Phenotyping?

model-releasesarxiv-cs-cv

arXiv:2608.23142v1 Announce Type: new Abstract: Vision-based wheat phenotyping requires repeated measurements under deployment constraints, from growth-stage recognition to wheat-head counting and org

How Much Regularization Survives Averaging? Update Masking in Federated Learning

arXiv:2608.23286v1 Announce Type: cross Abstract: Federated learning on non-IID data seeks flat minima to generalize across clients, and existing methods borrow sharpness-aware minimization from centr

How to Train a Critic Stably and Efficiently

arXiv:2608.23566v1 Announce Type: cross Abstract: Group-based reinforcement learning methods such as GRPO for large language models avoid training a critic by sampling multiple responses for each prom

How Useful are LLMs for Grammar Engineering? Cantonese ParGram Resources and Controlled Experimental Evaluation with English Baselines

model-releasesarxiv-cs-cl

arXiv:2608.23448v1 Announce Type: new Abstract: This paper presents new Cantonese ParGram resources and evaluates LLMs for knowledge-driven grammar engineering within a controlled experimental paradig

Applications

HP-UniIF: Hierarchical Prompt Learning for Unified Image Fusion

arXiv:2608.21786v1 Announce Type: new Abstract: General image fusion seeks to integrate complementary information from multiple source images, yet real-world applications often require a single system

applicationsarxiv-cs-cv

Hybrid Generative-Discriminative Object Placement

arXiv:2608.22692v1 Announce Type: new Abstract: As an important operation of image composition, object placement aims to predict the plausible placement (location, scale) for the inserted foreground o

Hybrid Panels: Toward Human-AI Collaboration in Survey Research

arXiv:2608.22582v1 Announce Type: cross Abstract: Large-scale population surveys are essential for generating robust social and scientific insights, yet they face significant challenges, including dec

Hyper^2: Unleashing Hyperbolic Geometry's Full Potential via Dual-Space Consistency

arXiv:2608.22238v1 Announce Type: new Abstract: HyperbolicCD pioneered hyperbolic geometry for point cloud completion by replacing the Euclidean Chamfer distance with arcosh(1+alpha||x-y||^2), but the

safetyarxiv-cs-cv

Hyperbolic Hierarchical Clustering for Visual Representation Learning

arXiv:2608.22665v1 Announce Type: cross Abstract: We investigate the token mixer in vision backbones by revisiting clustering, one of the most classic approaches in machine learning. An effective toke

Hypergraph Embedding Indexing for Efficient Dense Vector Retrieval

arXiv:2608.22980v1 Announce Type: cross Abstract: Dense vector retrieval has become the foundation of modern semantic search, yet existing approximate nearest neighbor (ANN) indexes treat an embedding

Image-Conditional Diffusion Transformer for Underwater Image Enhancement

arXiv:2407.05389v2 Announce Type: replace-cross Abstract: Underwater image enhancement (UIE) has attracted much attention owing to its importance for underwater operation and marine engineering. Motiv

Image-Conditioned Diffusion Models for Quality Assurance of Organ-at-Risk Segmentations in Radiotherapy

arXiv:2608.23432v1 Announce Type: new Abstract: Accurate organ-at-risk segmentation is essential for radiotherapy planning, but reviewing segmentations is time-consuming and subjective. We investigate

Improved denoising diffusion probabilistic models with efficient non-diagonal covariance modeling

arXiv:2608.21972v1 Announce Type: new Abstract: The sampling process of Denoising Diffusion Probabilistic Models (DDPMs) can be accelerated by leveraging second-order information in the form of approx

Improving Energy Efficiency of Oil Platforms Through Optimal Loading of Diesel Generators Using Machine Learning and Search Algorithms

arXiv:2608.22076v1 Announce Type: cross Abstract: Rising energy demand, fossil fuel depletion and climate change highlight the need for more efficient energy production and consumption. Offshore oil a

Improving Few-Step Language Flows with Untied Self-Conditioning

arXiv:2608.22244v1 Announce Type: cross Abstract: Flow-matching language models refine all token positions in parallel and can trade sampling steps for latency, yet generation quality still degrades s

Improving O-RADS Risk Stratification from Ultrasound Reports: A Comparative Evaluation of Hybrid versus End-to-End LLM Reasoning Strategies

arXiv:2608.23061v1 Announce Type: new Abstract: Background: Automating clinical guideline-based decision-making with large language models (LLMs) remains challenging because of reliability, hallucinat

In-Situ Reconstruction of the International Space Station Using 3D Gaussian Splatting and Astrobee

arXiv:2608.21685v1 Announce Type: new Abstract: This article presents a novel 3D reconstruction and mapping of the interior of the International Space Station (ISS) using 3D Gaussian Splatting (3DGS).

researcharxiv-cs-ro