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GDEPO: Group Dual-dynamic and Equal-right Advantage Policy Optimization for Sample-Efficient Reinforcement Learning

arXiv:2601.06795v4 Announce Type: replace Abstract: Automated Theorem Proving (ATP) is a fundamental AI challenge, requiring machine-verifiable proofs in formal languages like Lean to evaluate reasoni

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Human DGX agent

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Local Ai

Generalizable field of view extension for diffusion MRI via conditional flow matching

DGX agent

arXiv:2610.17401v1 Announce Type: new Abstract: Incomplete field-of-view (FOV) diffusion MRI (dMRI) acquisitions compromise whole-brain white matter analysis by excluding brain regions from tractograp

local-aiarxiv-cs-ai

15 Oct 2026

Generalizing Identifiability Results in Causal Discovery from Complete Data to Missing Data Settings

model-releasesarxiv-cs-lg

arXiv:2610.19211v1 Announce Type: cross Abstract: While causal discovery methods have matured for complete data, such algorithms for handling missing values remain limited. We establish general suffic

Applications

Generating Synthetic Doctor-Patient Conversations for Long-form Audio Summarization

arXiv:2604.06138v2 Announce Type: replace-cross Abstract: Long-context audio reasoning is underserved in both training data and evaluation. Existing benchmarks target short-context tasks, and the open

applicationsarxiv-cs-ai

Generation of data on discontinuous manifolds via continuous stochastic non-invertible networks

arXiv:2112.09646v2 Announce Type: replace Abstract: The generation of discontinuous distributions is a difficult task for most known frameworks such as generative autoencoders and generative adversari

Generative Representation Learning for Scalable Latent Tokenization

arXiv:2610.20533v1 Announce Type: cross Abstract: We introduce an approach for self-supervised representation learning designed to be used as a tokenizer for generative modeling. Our objective supervi

researcharxiv-cs-cv

Generative World Simulation with DAO and JING

arXiv:2610.19726v1 Announce Type: new Abstract: We present a Generative World Simulation framework that couples persistent shared world state with continuous first-person audiovisual generation. The f

researcharxiv-cs-cv

Genesis Steering: Better Activation Steering Through Training Data

model-releasesarxiv-cs-lg

arXiv:2610.19114v1 Announce Type: new Abstract: Activation steering controls large language models at inference time, but its effectiveness depends on the choice of reference data. We introduce genesi

GenState-AI: State-Aware Dataset for Text-to-Video Retrieval on AI-Generated Videos

model-releasesarxiv-cs-cv

arXiv:2603.14426v2 Announce Type: replace Abstract: Existing text-to-video retrieval benchmarks often permit matching from static appearance, making it difficult to determine whether models capture st

Agents

GeoCloak: An Agentic Framework for Semantics-Preserving Geolocation Privacy via Peripheral Clue Manipulation

arXiv:2610.20055v1 Announce Type: new Abstract: The rapid advancement of large vision language models (LVLMs) has made geolocation inference from images highly accurate and accessible. This poses seri

agentsarxiv-cs-cv

Geometric Alignment without Functional Equivalence: A Layer-wise Analysis of the Speech-Text Modality Gap

arXiv:2603.01502v2 Announce Type: replace Abstract: End-to-end speech large language models (LLMs) often answer the same question less accurately from speech than from text, even when the spoken conte

safetyarxiv-cs-cl

Geometric Kernel Diversity: An Axiomatic Diversity Measure in Euclidean Space

arXiv:2610.19570v1 Announce Type: cross Abstract: Quantifying the diversity of a set of objects is a fundamental problem in machine learning and statistics. Mironov and Prokhorenkova (2025) recently s

Applications

Geospatial Vector Geometry as a Native Spatial Modality for Vision-Language Models

arXiv:2610.16769v1 Announce Type: new Abstract: Geospatial reasoning links VLMs to real-world action and decision making. Reliable reasoning requires accurate spatial information and effective spatial

applicationsarxiv-cs-ai

Tutorials

GeoThinker-F: Endogenous Predictive World Representations for Fast Spatial Intelligence

arXiv:2610.20592v1 Announce Type: new Abstract: Existing geometry-aware Multimodal Large Language Models (MLLMs) increasingly rely on external 3D encoders to provide structural priors, but executing t

tutorialsarxiv-cs-cv

GesBench: When and Where Do Multimodal Language Models Perceive Social Meaning?

arXiv:2610.15129v1 Announce Type: new Abstract: Human social perception is incremental: we infer intent before an utterance is complete, revise our interpretation as new cues arrive, and attend to spe

Get In, Decide, Prove: A Merchant-Side Readiness Benchmark for Agentic Commerce

arXiv:2610.17378v1 Announce Type: new Abstract: AI agents now browse and buy on people's behalf, and benchmarks measure how well the agents perform. Far less is known about the other side of the trans

Hardware

Glance Forcing: Making Bidirectional Diffusion Autoregressive at a Glance

arXiv:2610.20220v1 Announce Type: new Abstract: Autoregressive generation underlies real-time, causal video synthesis and is the backbone of video world models. Today's dominant approach distills a bi

hardwarearxiv-cs-cv

Glasseek: A Transparent Recipe for Training and Trustworthy Evaluation of DeepSearch Agents

arXiv:2610.16998v1 Announce Type: new Abstract: Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-source

GLL: A Differentiable Graph Learning Layer for Neural Networks

arXiv:2412.08016v3 Announce Type: replace Abstract: Standard deep learning architectures used for classification generate label predictions with a projection head and softmax activation function. Alth

Tutorials

GLoD-LVSM: Learning Geometry-Grounded Continuous-LoD Scene Representations for Large View Synthesis Models

arXiv:2610.20254v1 Announce Type: new Abstract: Large view synthesis models (LVSMs) reconstruct scenes from sparse views and render novel views quickly, but they incur unnecessary storage and renderin

tutorialsarxiv-cs-cv

Google Earth AI Geospatial Reasoning Agent: Capabilities and a Systematic Evaluation

arXiv:2610.15750v1 Announce Type: new Abstract: Google Earth AI is a family of geospatial AI models, together with an agent that orchestrates them. We present this agent, Google Earth AI's Geospatial

Governing Copyright Responsibly in the Era of Generative AI

arXiv:2610.17002v1 Announce Type: cross Abstract: Large language models are trained on collections that may include scholarly works, while authors generally lack work-level information about whether a

researcharxiv-cs-ai

Graph Coarsening Enables Escaping Local Optima in Compute-Constrained Nonconvex MAX-CUT

model-releasesarxiv-cs-cl

arXiv:2610.19043v1 Announce Type: cross Abstract: Because its binary optimization landscape contains exponentially many local optima, MAX-CUT is highly sensitive to initialization. We study Particle P

Graph-Enhanced Disease Trajectory Discovery and Temporal Endpoint Forecasting from Longitudinal Electronic Health Records

arXiv:2610.20502v1 Announce Type: new Abstract: Longitudinal electronic health records (EHRs) can reveal disease-progression structure, while useful forecasting requires leakage-controlled discovery,

Graph-free Retrieval with Graph-Modified Embeddings

arXiv:2610.18410v1 Announce Type: cross Abstract: Dense vector retrieval can miss evidence connected through intermediate entities, while direct graph retrieval requires access to the graph at query t

Local Ai

Graph-Reweighted Behavior Cloning with Human Interventions for Precise Robotic Manipulation

arXiv:2610.20504v1 Announce Type: new Abstract: Long-horizon precise manipulation produces mixed-quality data for post-training vision-language-action (VLA) models: even successful demonstrations and

local-aiarxiv-cs-ro

Local Ai

GraphRAG-LTM: A Layered Threat Modeling Framework for Attacks on Graph Retrieval-Augmented Generation

arXiv:2610.19549v1 Announce Type: new Abstract: Graph retrieval-augmented generation (GraphRAG) uses document-derived knowledge graphs to assemble evidence for large language model (LLM) answers. Its

local-aiarxiv-cs-cl

Gray-Box Hallucination Detection in LLMs with Token Identities

model-releasesarxiv-cs-cl

arXiv:2610.19996v1 Announce Type: new Abstract: Large language models often produce fluent but factually incorrect output. Gray-box detectors identify such hallucinations from the token-probability st

Tutorials

GREAT-ESDD: Graph Edge Attention Network for Effectively Steered Delivery Decisions

arXiv:2610.14792v1 Announce Type: new Abstract: Online, same-day delivery requires operators to constantly update their routes, and the routing cost for deliveries increases with the number of custome

tutorialsarxiv-cs-ai

GroundGUI: GUI Grounding by High-Quality Data and Distillation-to-Reinforcement Learning

arXiv:2610.19100v1 Announce Type: cross Abstract: Constructing robust GUI agents relies on multimodal visual grounding: the ability to precisely map natural language intents to actionable on-screen co

researcharxiv-cs-cl

GS-PRM: Gaussian Visual Roadmap for Image-Goal Navigation

arXiv:2610.19541v1 Announce Type: new Abstract: Image-goal navigation requires a global planner that connects visually specified endpoints while providing observations that a local policy can follow.

safetyarxiv-cs-ro

Gugak-VocalSet: A Multi-Genre Studio-Quality Dataset of Korean Traditional Singing with Sigimsae Annotations

arXiv:2610.15350v1 Announce Type: cross Abstract: We present Gugak-VocalSet, the first publicly available audio dataset for Korean traditional singing with dense annotations of sigimsae, a structured

researcharxiv-cs-ai

GUIDE: Computationally Augmented Consensus for Trustworthy Clinical Practice Guidelines

arXiv:2610.16108v1 Announce Type: new Abstract: Maintaining up-to-date clinical practice guidelines (CPGs) is essential for evidence-based medicine, but rapid evidence growth and complex expert consen

HACHIMI-II: From Role-Play to Learner Behavior Modeling for Faithful Student Simulation

arXiv:2610.19654v1 Announce Type: new Abstract: Simulated students let researchers test tutoring systems and teaching strategies before real learners are available, but only if the simulation reproduc

researcharxiv-cs-cl

Handoff Curves: Initial Selection, Later Handoff, and Supervision Targets in Multi-turn LLM Routing

arXiv:2610.15993v1 Announce Type: new Abstract: We study how initial model selection, later handoff, and training targets affect success and cost in LLM tasks that span multiple turns. We compare seve

HankelKANet: Lightweight Path Loss Estimation via Physics-Inspired Hankel Convolution

model-releasesarxiv-cs-lg

arXiv:2610.19524v1 Announce Type: new Abstract: Accurate path loss (PL) estimation is essential for wireless network planning and optimization. This paper proposes HankelKANet, a lightweight physics-i

Harmony Harness: Multi-Objective Self-Evolution of Agent Harnesses

arXiv:2610.15150v1 Announce Type: new Abstract: Recent work on self-evolving LLM agents treats the agent harness as an optimization target that can be iteratively improved through execution feedback.

Harness Policy Distillation: Aligning Agent Policies with Runtime Semantics

arXiv:2610.20261v1 Announce Type: new Abstract: Deploying a general-purpose model as an agent means running it inside a product-specific runtime harness that decides which actions are executable, how

safetyarxiv-cs-lg

Agents

HarnessNet: Feedback-driven Hierarchical Joint Harness Evolution for Multi-agent Systems

arXiv:2610.15221v1 Announce Type: new Abstract: AI agents can evolve by using environment feedback to revise their harnesses, the software managing model inputs, tool use, memory, and execution, while

agentsarxiv-cs-ai

Applications

Have You Been Convinced? A Neuro-symbolic Argumentation Reasoning Approach to Detecting Persuasiveness in ChangeMyView Discussions

arXiv:2610.15091v1 Announce Type: cross Abstract: Argument structures represent how individual arguments interact within a discourse. However, leveraging these structures to infer meaningful knowledge

applicationsarxiv-cs-ai

HERO: Harnessing Evidence for Test-time Refinement and Prompt Optimization in Program Generation

arXiv:2610.19184v1 Announce Type: new Abstract: Harness optimization improves LLMs by refining reusable prompts and scaffolding, yet requires further adaptation for program generation tasks such as te

researcharxiv-cs-cl

Heterogeneous Agentic Coevolution

arXiv:2610.16078v1 Announce Type: new Abstract: Recent advances in self-improving LLM agents have demonstrated the potential of AI systems that drive their own intelligence. However, many domain-speci

HGRP: Heterogeneous Graph Neural Network for Routability Prediction

arXiv:2610.20209v1 Announce Type: new Abstract: Routability prediction enables rapid evaluation of placement quality without routing, providing effective feedback for routability-driven placement opti

Hidden in Plain Sight: Advancing Harmful Content Understanding via Perception-Aware Adversarial Self-Play

arXiv:2610.15449v2 Announce Type: new Abstract: Despite significant advances in language understanding, Large Language Models (LLMs) can still miss meaning hidden in plain sight, failing to identify h

Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance

arXiv:2610.20607v1 Announce Type: cross Abstract: Mobile Manipulation (MoMa) is a cornerstone of autonomous robotic systems, yet real-world fine-tuning remains a formidable challenge because of high-d

safetyarxiv-cs-lg

HiFun: a Hierarchical Framework for Efficient Functional Dexterous Manipulation Learning

arXiv:2610.19518v1 Announce Type: new Abstract: While multi-fingered dexterous robot hands have the potential to provide human-level dexterity, using them for functional manipulation remains difficult

safetyarxiv-cs-ro

High-Probability Regret Bounds for Feel-Good Thompson Sampling

arXiv:2610.19513v1 Announce Type: cross Abstract: Feel-good Thompson sampling (FGTS) augments the posterior of vanilla Thompson sampling with an exploration term that favors reward functions with high

Hindsight-Privileged RLVR: Single-Rollout Token Credit Without Group Sampling

arXiv:2610.20497v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) trains language models from checked task outcomes, but assigning a terminal reward to individual r

safetyarxiv-cs-lg