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Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

arXiv:2606.05015v1 Announce Type: new Abstract: World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet h

safetyarxiv-cs-ro

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Generating Financial Time Series by Matching Random Convolutional Features

DGX agent

arXiv:2606.05138v1 Announce Type: new Abstract: Generating realistic financial time series is challenging as training data is often limited to a single historical path. With such scarce data, overfitt

applicationsarxiv-cs-lg

4 Jun 2026

GenSpan: Generation-Calibrated Motion Span Priors for Multi-Verb Video Corpus Moment Retrieval

arXiv:2603.22121v2 Announce Type: replace-cross Abstract: Video Corpus Moment Retrieval (VCMR) aims to retrieve both the correct video and its temporal segment corresponding to a natural-language quer

Geometry-Aware Distillation for Prompt Tuning Biomedical Vision-Language Models

arXiv:2606.04922v1 Announce Type: cross Abstract: Current prompt-based and adapter-based tuning of vision-language models (VLMs) is attractive for medical imaging, where clinical data sensitivity favo

safetyarxiv-cs-ai

Geometry-Aware Hallucination Detection in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2601.06196v3 Announce Type: replace-cross Abstract: Large language models (LLMs) frequently generate factually incorrect or unsupported content, commonly referred to as hallucinations. Prior wor

Geometry Gaussians: Decoupling Appearance and Geometry in Gaussian Splatting

arXiv:2606.05124v1 Announce Type: cross Abstract: After the success of 3D Gaussian Splatting (3DGS) for novel view synthesis, many works have explored how to also use it for geometric surface represen

Geometry-Preserving Encoder/Decoder in Latent Generative Models

arXiv:2501.09876v3 Announce Type: replace-cross Abstract: Generative modeling aims to generate new data samples that resemble a given dataset. When using diffusion models for this task, one of the mai

tutorialsarxiv-cs-lg

Geometry-Preserving Unsupervised Alignment for Heterogeneous Foundation Models

arXiv:2606.04385v1 Announce Type: new Abstract: Foundation models have driven rapid progress in computer vision, yet the two dominant paradigms, vision-language foundation models (VLMs) and vision-onl

GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling

arXiv:2606.04516v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) significantly advances LLM reasoning, yet it faces a dilemma: standard supervised scaling is thr

tutorialsarxiv-cs-ai

Geospatial Foundation Models to Enable Progress on Sustainable Development Goals

arXiv:2505.24528v3 Announce Type: replace Abstract: Foundation Models (FMs) are large-scale, pre-trained artificial intelligence (AI) systems that have revolutionized natural language processing and c

safetyarxiv-cs-cv

GIFT: Games as Informal Training for Generalizable LLMs

arXiv:2601.05633v2 Announce Type: replace Abstract: Recent LLMs excel at formal tasks such as mathematical reasoning and code generation, but still struggle with broader abilities such as planning, cr

researcharxiv-cs-cl

Global Sketch-Based Watermarking for Diffusion Language Models

arXiv:2606.04486v1 Announce Type: cross Abstract: Watermarking methods for language models have been studied extensively in the autoregressive setting, where tokens are generated sequentially. These w

GlossAssist -- A Tool to Simplify Corpus Creation and Study the Effect of NLP Models in Low-Resource Documentation Settings

arXiv:2606.04367v1 Announce Type: new Abstract: Interlinear glossed text (IGT) is the standard format for linguistic annotation in language documentation. Producing it manually, however, is often slow

researcharxiv-cs-cl

Good Reasoning Makes Good Demonstrations: Implicit Reasoning Quality Supervision via In-Context Reinforcement Learning

arXiv:2603.09803v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) improves reasoning in large language models but treats all correct solutions equally, potentia

safetyarxiv-cs-lg

Gradient estimators for parameter inference in discrete stochastic kinetic models

model-releasesarxiv-cs-lg

arXiv:2604.02121v2 Announce Type: replace-cross Abstract: Stochastic kinetic models are ubiquitous in physics, yet inferring their parameters from experimental data remains challenging. For determinis

Applications

GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors

arXiv:2606.05160v1 Announce Type: new Abstract: Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleop

applicationsarxiv-cs-ro

GRAIL: Gradient-Reweighted Advantages for Reinforcement Learning with Verifiable Rewards

arXiv:2606.04889v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (e.g. GRPO) is now a common way to improve mathematical reasoning in Large Language Models (LLMs). Howeve

Graph Cascades: Contagion-Based Mesoscopic Rewiring for Structure-Aware Graph Machine Learning

arXiv:2606.05046v1 Announce Type: new Abstract: We introduce Graph Cascades, a mesoscopic rewiring strategy for Graph Neural Networks (GNNs) and Graph Transformers (GTs) that captures intermediate-sca

researcharxiv-cs-lg

Graph-Guided Universum Learning in Generalized Eigenvalue Proximal SVMs for Alzheimer's Disease Classification

arXiv:2606.04699v1 Announce Type: cross Abstract: Early and accurate detection of Alzheimer's disease (AD) is important for timely intervention and disease management. Generalized Eigenvalue Proximal

Agents

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

arXiv:2507.21892v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) mitigates hallucination in LLMs by incorporating external knowledge, but relies on chunk-based retrieval that l

agentsarxiv-cs-cl

Graph Set Transformer

model-releasesarxiv-cs-lg

arXiv:2606.05116v1 Announce Type: new Abstract: We introduce the Graph Set Transformer (GST), a neural network architecture for learning on sets of graphs, designed for tasks in which per-element pred

Gravity-Aware Hierarchical Routing for Lightweight SensorLLM on Human Activity Recognition

model-releasesarxiv-cs-ai

arXiv:2606.04019v1 Announce Type: cross Abstract: Recent studies on sensor-language alignment have shown that two-stage frameworks can improve the semantic modeling ability of wearable-sensor human ac

GroupToM-Bench: Benchmarking Group Theory of Mind and Nonlinear Social Emergence in MLLMs

arXiv:2606.04184v1 Announce Type: new Abstract: True general intelligence requires not only a model of the physical world but also a social world model: the capacity to infer how individual mental sta

HalfNet: Randomized Neural Networks with Learned Subspace Geometry

arXiv:2606.04583v1 Announce Type: new Abstract: Many researchers investigated neural networks with some of their weights fixed to values randomly drawn from a given distribution, e.g., N(0, I). Our pr

tutorialsarxiv-cs-lg

Handwriting Extraction and Analysis of Signature Lists in Swiss Popular Initiatives

arXiv:2606.05018v1 Announce Type: new Abstract: Popular initiatives and referendums are central to Swiss democracy, yet the validation of handwritten signature lists remains a labor-intensive manual p

HapTile: A Haptic-Informed Vision-Tactile-Language-Action Dataset for Contact-Rich Imitation Learning

arXiv:2606.04825v1 Announce Type: new Abstract: Despite the importance of tactile sensing for reliable manipulation, most existing Vision-Language-Action (VLA) datasets remain vision-only, and those t

safetyarxiv-cs-ro

HD-DinoMoE: A Class-Aware Hierarchical Dual Mixture-of-Experts Network for Scleral Anomaly Segmentation in Complex Acquisition Scenarios

arXiv:2606.04888v1 Announce Type: new Abstract: Traditional Chinese Medicine (TCM) ocular inspection provides empirical cues for assessing scleral surface anomalies, but its clinical use remains subje

Hierarchical Self-Supervised Adversarial Training for Robust Vision Models in Histopathology

arXiv:2503.10629v2 Announce Type: replace Abstract: Adversarial attacks pose significant challenges for vision models in critical fields like healthcare, where reliability is essential. Although adver

Hierarchical Space Partition for Surface Reconstruction

arXiv:2606.04891v1 Announce Type: new Abstract: Generating compact polygonal models from point clouds is a key problem in 3D vision and computer graphics. However, due to inherent limitations of LiDAR

High-Quality Entity Segmentation and Grounding

model-releasesarxiv-cs-cl

arXiv:2402.02555v2 Announce Type: replace-cross Abstract: In this work, we propose ESG, a pipeline for high-quality entity segmentation and grounding supported by a new dataset EntitySeg. At first, th

HighTide: An Agent-Curated Open-Source VLSI Benchmark Suite

model-releasesarxiv-cs-ai

arXiv:2606.04126v1 Announce Type: cross Abstract: We introduce HighTide, an evolving AI-assisted benchmark suite. Specifically, the contributions are: (i) a diverse open-source suite spanning multiple

HORIZON: Recoverability-Governed Curriculum for Physical-Domain Scaling

model-releasesarxiv-cs-ro

arXiv:2606.05143v1 Announce Type: new Abstract: Scaling robust robot policies requires more than broader randomization, because physical-domain experience must remain organized and learnable throughou

How do machines learn? Evaluating the AIcon2abs method

arXiv:2401.07386v5 Announce Type: cross Abstract: This study expands on previous work that introduced the AIcon2abs method (AI from Concrete to Abstract: Demystifying Artificial Intelligence to the ge

tutorialsarxiv-cs-ai

How Users Understand Robot Foundation Model Performance through Task Success Rates and Beyond

arXiv:2602.03920v2 Announce Type: replace Abstract: Robot Foundation Models (RFMs) represent a promising approach to developing general-purpose home robots. Given the broad capabilities of RFMs, users

researcharxiv-cs-ro

Hybrid Adversarial Defence for Natural Language Understanding Tasks

arXiv:2606.04612v1 Announce Type: new Abstract: Large Language Models (LLMs) are vulnerable both to hallucination and adversarial manipulation. Although these problems are closely related, existing de

HYolo: An Intelligent IoT-Based Object Detection System Using Hypergraph Learning

arXiv:2606.04345v1 Announce Type: cross Abstract: This paper presents HYolo, an intelligent IoT-based object detection framework that integrates hypergraph learning into the YOLO architecture. Traditi

Hyper-ICL: Attention Calibration with Hyperbolic Anchor Distillation for Multimodal In-Context Learning

arXiv:2606.04434v1 Announce Type: new Abstract: Multimodal In-Context Learning (ICL) has emerged as a practical inference paradigm for Multimodal Large Language Models, where a small set of interleave

Identifying and Correcting Label Noise for Robust GNNs via Influence Contradiction

model-releasesarxiv-cs-lg

arXiv:2601.17469v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have shown remarkable capabilities in learning from graph-structured data with various applications such as social anal

Local Ai

Identifying Gems from Roman RAPIDly

arXiv:2606.05103v1 Announce Type: cross Abstract: The Nancy Grace Roman Space Telescope (Roman), set for launch as early as September 2026, will conduct wide-field infrared imaging surveys with unprec

local-aiarxiv-cs-cv

Imagine Before You Draw: Visual Prompt Engineering for Image Generation

arXiv:2606.04457v1 Announce Type: new Abstract: Incorporating visual semantic representations as an intermediate step before image generation can reduce the modeling difficulty between text and images

Imbuing Large Language Models with Bidirectional Logic for Robust Chain Repair

arXiv:2606.05030v1 Announce Type: new Abstract: Autoregressive chain-of-thought (CoT) reasoning in large language models (LLMs) is fundamentally forward-directed: each step conditions only on prior to

Applications

Implicit Fuzzification via Bounded Noise Injection for Robust Medical Image Segmentation

arXiv:2606.04427v1 Announce Type: new Abstract: Image segmentation remains fundamentally limited by boundary ambiguity arising from sampling-induced information loss and inherent uncertainty in pixel-

applicationsarxiv-cs-cv

IMPose: Interactive Multi-person Pose Estimation with Dynamic Correction Propagation

arXiv:2606.04480v1 Announce Type: new Abstract: High-quality dynamic human pose annotation equips AI with precise motion kinematics to enable human behavior mastery, yet remains labor-intensive and ti

Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization

arXiv:2606.04545v1 Announce Type: new Abstract: Recent advances in generative image editing have improved the realism and controllability of localized image manipulation, raising new challenges for im

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes

arXiv:2512.14177v3 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) often produce plausible but unreliable outputs, making robust uncertainty estimation essential. Recent work on

In-Context Graphical Inference

arXiv:2606.05042v1 Announce Type: cross Abstract: Marginal inference in discrete graphical models forces a choice between exactness and scalability: exact algorithms are intractable for high-treewidth

Inclusion-of-Thoughts: Mitigating Preference Instability via Purifying the Decision Space

arXiv:2604.04944v2 Announce Type: replace-cross Abstract: Multiple-choice questions (MCQs) are widely used to evaluate large language models (LLMs). However, LLMs remain vulnerable to the presence of

Local Ai

Incremental Sheaf Cohomology on Cellular Complexes: O(1)-in-n Lazy Edit Processing under Bounded Local Geometry

arXiv:2606.04227v1 Announce Type: cross Abstract: We present an algorithmic framework for incremental maintenance of first sheaf cohomology H^1(X; F) on dynamically evolving 1-dimensional cellular com

local-aiarxiv-cs-ai