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Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

model-releasesarxiv-cs-cl

arXiv:2510.24081v2 Announce Type: replace Abstract: To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and

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GloResNet: A lightweight 3D CNN with global topological features for preterm brain injury prediction

DGX agent

arXiv:2606.02498v1 Announce Type: new Abstract: This study introduces an automated deep learning framework for predicting brain injury (BI) in preterm infants from T2-weighted MRI (dHCP dataset). We p

researcharxiv-cs-cv

2 Jun 2026

GNMR: Runtime Stability Control for Low-Precision Large Language Model Training

model-releasesarxiv-cs-lg

arXiv:2606.00539v1 Announce Type: new Abstract: Training stability is a key bottleneck in low-precision language model training: efficient low-cost paths can still produce short-lived numerical risks

Tutorials

GNN-Enabled Robust Hybrid Beamforming with Score-Based CSI Generation and Denoising

arXiv:2511.06663v2 Announce Type: replace-cross Abstract: Accurate Channel State Information (CSI) is critical for Hybrid Beamforming (HBF) tasks. However, obtaining high-resolution CSI remains challe

tutorialsarxiv-cs-lg

Agents

Goal2Pixel: Grounding Goals to Pixels for Vision-Language Navigation

arXiv:2606.01621v1 Announce Type: new Abstract: Vision-language models (VLMs) have become a common foundation for vision-and-language navigation in continuous environments (VLN-CE). Yet most VLM-based

agentsarxiv-cs-cv

GottBERT: a pure German Language Model

arXiv:2012.02110v2 Announce Type: replace Abstract: Pre-trained language models have significantly advanced natural language processing (NLP), especially with the introduction of BERT and its optimize

researcharxiv-cs-cl

GovAI-Pipe: A Layered AI Governance Pipeline for Citizen-Facing AI in Turkey's e-Government Gateway

arXiv:2606.01417v1 Announce Type: new Abstract: Turkey's e-Government Gateway (e-Devlet) serves over 68 million registered users with more than 9,200 government services, and is increasingly integrati

safetyarxiv-cs-ai

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation

arXiv:2606.01412v1 Announce Type: new Abstract: Post-training quantization is widely used for compressing large neural networks, but aggressive low-bit quantization can significantly degrade model qua

researcharxiv-cs-lg

GRANITE : a Byzantine-Resilient Dynamic Gossip Learning Framework

arXiv:2504.17471v2 Announce Type: replace-cross Abstract: Gossip Learning (GL) is a decentralized learning paradigm where users iteratively exchange and aggregate models with a small set of neighborin

Applications

Graph-Augmented Retrieval for Cross-Entity Financial Sentiment Analysis: A Comparative Study

arXiv:2606.00062v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become foundational for grounding large language models in domain-specific corpora, yet conventional vector-bas

applicationsarxiv-cs-cl

Graph Edit Distance Formulation for the Vehicle Routing Problem: Theory and Analysis

model-releasesarxiv-cs-lg

arXiv:2606.01987v1 Announce Type: cross Abstract: We show that the Vehicle Routing Problem (VRP) can be reformulated as a Graph Edit Distance (GED) maximization problem. Under a simple edge-deletion c

Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning

arXiv:2508.06588v3 Announce Type: replace-cross Abstract: Vector Quantization (VQ) has recently emerged as a promising approach for learning compressed and discrete representations for graph-structure

Graph Transfer Learning via Shared Latent Geometry: Theory and Applications

arXiv:2606.00716v1 Announce Type: new Abstract: Inference and control in engineered physical systems pay a heavy physics cost at deployment: state estimators, inverse-problem solvers, model-predictive

researcharxiv-cs-lg

Applications

GraspGen-X: Cross-Embodiment 6-DOF Diffusion-based Grasping

arXiv:2606.00998v1 Announce Type: new Abstract: We study cross-embodiment 6-DOF robot grasping. Unlike prior works, we require the model not only to generalize to novel objects / scenes but also to no

applicationsarxiv-cs-ro

GREAT: Generalizable Backdoor Attacks in RLHF via Emotion-Aware Trigger Synthesis

model-releasesarxiv-cs-lg

arXiv:2510.09260v2 Announce Type: replace-cross Abstract: Recent work has shown that RLHF is highly susceptible to backdoor attacks. However, existing methods often rely on rare tokens or fixed trigge

Agents

Grokers: Bottom-Up Inductive Comprehension and Write-Time Intelligence over Typed Knowledge Graphs

arXiv:2606.00050v1 Announce Type: new Abstract: We present Grokers, an architecture for building persistent, structured comprehension of typed knowledge graphs through bottom-up inductive traversal of

agentsarxiv-cs-ai

Grounded Decoding: Retrieval-Anchored Probability Fusion for Faithful RAG

arXiv:2606.00432v1 Announce Type: new Abstract: As retrieval-augmented generation (RAG) systems scale, it becomes increasingly challenging to ensure faithful grounding in external evidence. Large lang

researcharxiv-cs-lg

Grounding or Guessing? Visual Signals for Detecting Hallucinations in Sign Language Translation

arXiv:2510.18439v3 Announce Type: replace Abstract: Hallucination, where models generate fluent text unsupported by visual evidence, remains a major flaw in vision-language models and is particularly

safetyarxiv-cs-cl

GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning

arXiv:2601.22651v2 Announce Type: replace-cross Abstract: Training-data attribution for vision generative models aims to identify which training data influenced a given output. While most methods scor

GuidaPA: Privacy-Preserving Chatbot for Public Administration via Federated Learning

arXiv:2606.01386v1 Announce Type: new Abstract: We present GuidaPA, a privacy-preserving chatbot for the Italian Public Administration (PA) trained via Federated Learning (FL) on documentation from tw

HAIM: Human-AI Music Datasets for AI Music Production Tracking Benchmark

arXiv:2606.01686v1 Announce Type: cross Abstract: As generative platforms such as Suno and Udio reach human-grade audio quality, the scope of AI's utility has expanded across the entire music producti

HakushoBench: A Japanese Chart and Table VQA Benchmark from Governmental White Papers

model-releasesarxiv-cs-cv

arXiv:2606.01132v1 Announce Type: new Abstract: Understanding chart and table images is essential for applying vision-language models (VLMs) to real-world document understanding. While English benchma

HalleluBERT: Let Every Token That Has Meaning Bear Its Weight

model-releasesarxiv-cs-cl

arXiv:2510.21372v2 Announce Type: replace Abstract: Transformer-based models have advanced NLP, yet Hebrew still lacks a RoBERTa encoder that is trained at scale and released in both base and large va

Hallucination-Aware Diffusion Sampling for Inverse Problems via Robust Prior Updates

arXiv:2606.02331v1 Announce Type: new Abstract: Diffusion-based inverse problem solvers can produce realistic reconstructions, but realism alone does not ensure that the recovered details are supporte

researcharxiv-cs-cv

HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization

arXiv:2603.03741v2 Announce Type: replace-cross Abstract: To improve generalization and resilience in human-robot collaboration (HRC), robots must contend with diverse combinations of human behaviors

Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift

arXiv:2512.15647v3 Announce Type: replace Abstract: Soft labels from teacher models are a de facto practice for knowledge transfer and large-scale dataset distillation (e.g., SRe2L, LPLD). However, wh

Harness-1: Reinforcement Learning for Search Agents with State-Externalizing Harnesses

arXiv:2606.02373v1 Announce Type: new Abstract: Search agents are often trained as policies over growing transcripts: the model must decide how to search while also remembering what it has seen, which

safetyarxiv-cs-ai

HarnessForge: Joint Harness and Policy Evolution for Adaptive Agent Systems

arXiv:2606.01779v1 Announce Type: new Abstract: LLM agents are increasingly expected to operate across heterogeneous task regimes that require distinct execution paradigms. This challenges fixed agent

safetyarxiv-cs-cl

HASTE: Hardware-Aware Dynamic Sparse Training for Large Output Spaces

arXiv:2606.01117v1 Announce Type: cross Abstract: Extreme multi-label classification (XMC) involves learning models over large output spaces with millions of labels, making the output layer a memory-c

safetyarxiv-cs-ai

(HB-ARFM) History-Bootstrapped Flow Matching for Inverse Boiling Reconstruction

arXiv:2606.00349v1 Announce Type: cross Abstract: Reconstructing spatiotemporal fields from partial observations is fundamental to scientific inference, from inferring atmospheric states from satellit

Head-Pose-Aware Visual Speech Recognition with FiLM Modulation

arXiv:2606.00751v1 Announce Type: new Abstract: Visual Speech Recognition (VSR) aims to recognize speech from visual cues such as lip movements, but its performance is fundamentally limited by viseme

researcharxiv-cs-cv

HERO'S JOURNEY: Testing Complex Rule Induction with Text Games

model-releasesarxiv-cs-cl

arXiv:2606.02556v1 Announce Type: new Abstract: We introduce HERO'S JOURNEY, a benchmark for rule induction in goal-directed episodic tasks, where agents must infer hidden rules from demonstrations an

Local Ai

Heterogeneous Decentralized Diffusion Models

arXiv:2603.06741v2 Announce Type: replace-cross Abstract: Training frontier-scale diffusion models often requires substantial computational resources concentrated in tightly-coupled clusters, limiting

local-aiarxiv-cs-ai

Hidden Thoughts Are Not Secret: Reasoning Trace Exposure in LLMs

arXiv:2606.00642v1 Announce Type: new Abstract: Reasoning traces have become a valuable form of learning signals for improving and transferring the capabilities of large language models. In particular

Hierarchical Object Representation for Spatial Robot Perception: Points, Meshes, and Superquadrics

arXiv:2606.01545v1 Announce Type: new Abstract: Hierarchical 3D Scene Graphs (3DSG) have emerged as an actionable and scalable representation for long-term autonomy incorporating metric, semantic, and

safetyarxiv-cs-ro

Hierarchical Online Prompt Mutation with Dual-Loop Feedback for Guardrailed Evidence Document Generation: A Production-Evaluation Case Study

arXiv:2606.01472v1 Announce Type: cross Abstract: High-stakes production document-generation systems require language models to be adaptive, evidence-grounded, and auditable. We present HOPM, a hierar

Hierarchical Semantic-Augmented Navigation: Optimal Transport and Graph-Driven Reasoning for Vision-Language Navigation

arXiv:2606.01565v1 Announce Type: cross Abstract: Vision-Language Navigation in Continuous Environments (VLN-CE) poses a formidable challenge for autonomous agents, requiring seamless integration of n

Hierarchically Decoupled Mixture-of-Experts for Robust Traffic Sign Recognition in Complex Driving Scenarios

model-releasesarxiv-cs-cv

arXiv:2606.01822v1 Announce Type: new Abstract: Traffic sign detection is a fundamental component of environmental perception in autonomous driving and intelligent transportation systems. However, mos

HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings

arXiv:2502.15411v4 Announce Type: replace-cross Abstract: Accurate tagging of earnings reports can yield significant short-term returns for stakeholders. The machine-readable inline eXtensible Busines

Highly Deformable Proprioceptive Membrane for Real-Time 3D Shape Reconstruction

arXiv:2601.13574v2 Announce Type: replace Abstract: Reconstructing the three-dimensional (3D) geometry of object surfaces is essential for robot perception, yet vision-based approaches degrade under l

researcharxiv-cs-ro

HiGS: A Hierarchical Rendering Architecture for Real-Time 3D Gaussian Splatting

arXiv:2606.00352v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has become the standard for real-time novel view synthesis on commodity GPUs. Its pipeline ties spatial partitioning and ra

researcharxiv-cs-cv

Local Ai

Hist2Style: Histogram-Guided Stylization with Bilateral Grids

arXiv:2606.01819v1 Announce Type: new Abstract: Photorealistic style transfer aims to match the color and tone of an input image to that of a style target while preserving the content and details of t

local-aiarxiv-cs-cv

HiTokSR: A Coarse-to-Fine Tokenizer with Hierarchical Codebooks for High-Fidelity Real-World Image Super-Resolution

arXiv:2606.01157v1 Announce Type: new Abstract: Vector-quantized (VQ) generative models have shown promising results in real-world image super-resolution (Real-ISR). However, existing methods typicall

HLL: Can Agents Cross Humanity's Last Line of Verification?

arXiv:2606.02449v1 Announce Type: new Abstract: Multimodal agents are increasingly expected to operate interfaces on behalf of users, raising a central deployment question: can they truly substitute f

HMPO: Hybrid Median-length Policy Optimization for Chain-of-Thought Compression

arXiv:2606.01934v1 Announce Type: cross Abstract: Large language models achieve remarkable performance via extended chain-of-thought (CoT) reasoning, yet this lengthy process incurs substantial infere

safetyarxiv-cs-cl

Hoeffding Concept Bottleneck Models with Applications to Overhead Images

arXiv:2606.00082v1 Announce Type: cross Abstract: Explainability of deep learning algorithms is critical for computer-vision applications with high-stake decisions. Concept bottleneck models (CBM) hav

HOIST: Humanoid Optimization with Imitation and Sample-efficient Tuning for Manipulating Suspended Loads

arXiv:2606.00252v1 Announce Type: cross Abstract: Manipulating suspended payloads with humanoid robots is challenging because the robot can only influence an underactuated, oscillatory load through wh

safetyarxiv-cs-lg

HOLA: Holistic Multi-Modal Alignment for Open-Set 3D Recognition

arXiv:2606.01334v1 Announce Type: new Abstract: Open-set 3D recognition requires models that generalize to rare or unseen categories. Recent approaches address this by distilling language-vision knowl