All entries

arXiv:2603.24329v2 Announce Type: replace-cross Abstract: Multimodal LLMs are increasingly deployed as perceptual backbones for autonomous agents in 3D environments, from robotics to virtual worlds. T

agentsarxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

GaNI: Global and Near Field Illumination Aware Neural Inverse Rendering

DGX agent

arXiv:2403.15651v5 Announce Type: replace Abstract: In this paper, we present GaNI, a Global and Near-field Illumination-aware neural inverse rendering technique that can reconstruct geometry, albedo,

researcharxiv-cs-cv

14 Apr 2026

GanitLLM: Difficulty-Aware Bengali Mathematical Reasoning through Curriculum-GRPO

arXiv:2601.06767v2 Announce Type: replace-cross Abstract: We present a Bengali mathematical reasoning model called GanitLLM (named after the Bangla word for mathematics, 'Ganit'), together with a new

GazeVaLM: A Multi-Observer Eye-Tracking Benchmark for Evaluating Clinical Realism in AI-Generated X-Rays

arXiv:2604.11653v1 Announce Type: new Abstract: We introduce GazeVaLM, a public eye-tracking dataset for studying clinical perception during chest radiograph authenticity assessment. The dataset compr

General-purpose LLMs as Models of Human Driver Behavior: The Case of Simplified Merging

arXiv:2604.09609v1 Announce Type: new Abstract: Human behavior models are essential as behavior references and for simulating human agents in virtual safety assessment of automated vehicles (AVs), yet

General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks

arXiv:2604.11778v1 Announce Type: cross Abstract: Contemporary large language models (LLMs) have demonstrated remarkable reasoning capabilities, particularly in specialized domains like mathematics an

Generalizable Deepfake Detection Based on Forgery-aware Layer Masking and Multi-artifact Subspace Decomposition

arXiv:2601.01041v3 Announce Type: replace Abstract: Deepfake detection remains highly challenging, particularly in cross-dataset scenarios and complex real-world settings. This challenge mainly arises

Generating Hadamard matrices with transformers

arXiv:2604.11101v1 Announce Type: cross Abstract: We present a new method for constructing Hadamard matrices that combines transformer neural networks with local search in the PatternBoost framework.

researcharxiv-cs-lg

Generating High Quality Synthetic Data for Dutch Medical Conversations

arXiv:2604.09645v1 Announce Type: cross Abstract: Medical conversations offer insights into clinical communication often absent from Electronic Health Records. However, developing reliable clinical Na

Applications

Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models

arXiv:2604.10748v1 Announce Type: cross Abstract: Generating multiple-choice questions (MCQs) with difficulty estimation remains challenging in automated MCQ-generation systems used in adaptive, AI-as

applicationsarxiv-cs-ai

Generation-Augmented Generation: A Plug-and-Play Framework for Private Knowledge Injection in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2601.08209v3 Announce Type: replace Abstract: In domains such as materials science, biomedicine, and finance, high-stakes deployment of large language models (LLMs) requires injecting private, d

Hardware

Generative Design for Direct-to-Chip Liquid Cooling for Data Centers

arXiv:2604.10941v1 Announce Type: cross Abstract: Rapid growth in artificial intelligence (AI) workloads is driving up data center power densities, increasing the need for advanced thermal management.

hardwarearxiv-cs-lg

Generative Path-Finding Method for Wasserstein Gradient Flow

arXiv:2604.11519v1 Announce Type: new Abstract: Wasserstein gradient flows (WGFs) describe the evolution of probability distributions in Wasserstein space as steepest descent dynamics for a free energ

researcharxiv-cs-lg

Generative UI: LLMs are Effective UI Generators

arXiv:2604.09577v1 Announce Type: cross Abstract: AI models excel at creating content, but typically render it with static, predefined interfaces. Specifically, the output of LLMs is often a markdown

GenProve: Learning to Generate Text with Fine-Grained Provenance

arXiv:2601.04932v2 Announce Type: replace Abstract: Large language models (LLM) often hallucinate, and while adding citations is a common solution, it is frequently insufficient for accountability as

safetyarxiv-cs-cl

GenTac: Generative Modeling and Forecasting of Soccer Tactics

arXiv:2604.11786v1 Announce Type: new Abstract: Modeling open-play soccer tactics is a formidable challenge due to the stochastic, multi-agent nature of the game. Existing computational approaches typ

GeoArena: Evaluating Open-World Geographic Reasoning in Large Vision-Language Models

arXiv:2509.04334v4 Announce Type: replace Abstract: Geographic reasoning is a fundamental cognitive capability that requires models to infer plausible locations by synthesizing visual evidence with sp

GeoFormer: A Lightweight Swin Transformer for Joint Building Height and Footprint Estimation from Sentinel Imagery

arXiv:2602.09932v2 Announce Type: replace Abstract: Building height (BH) and footprint (BF) are fundamental urban morphological parameters required by climate modelling, disaster-risk assessment, and

GeoMeld: Toward Semantically Grounded Foundation Models for Remote Sensing

arXiv:2604.10591v1 Announce Type: cross Abstract: Effective foundation modeling in remote sensing requires spatially aligned heterogeneous modalities coupled with semantically grounded supervision, ye

safetyarxiv-cs-ai

Geometry-Aware Localized Watermarking for Copyright Protection in Embedding-as-a-Service

model-releasesarxiv-cs-cl

arXiv:2604.11344v1 Announce Type: cross Abstract: Embedding-as-a-Service (EaaS) has become an important semantic infrastructure for natural language and multimedia applications, but it is highly vulne

GeomPrompt: Geometric Prompt Learning for RGB-D Semantic Segmentation Under Missing and Degraded Depth

arXiv:2604.11585v1 Announce Type: new Abstract: Multimodal perception systems for robotics and embodied AI often assume reliable RGB-D sensing, but in practice, depth is frequently missing, noisy, or

Applications

Geoparsing: Diagram Parsing for Plane and Solid Geometry with a Unified Formal Language

arXiv:2604.11600v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but continue to struggle with geometric reasoning, primarily due to the perce

applicationsarxiv-cs-cv

GIANTS: Generative Insight Anticipation from Scientific Literature

arXiv:2604.09793v1 Announce Type: cross Abstract: Scientific breakthroughs often emerge from synthesizing prior ideas into novel contributions. While language models (LMs) show promise in scientific d

Tutorials

GIF: A Conditional Multimodal Generative Framework for IR Drop Imaging in Chip Layouts

arXiv:2604.09999v1 Announce Type: new Abstract: IR drop analysis is essential in physical chip design to ensure the power integrity of on-chip power delivery networks. Traditional Electronic Design Au

tutorialsarxiv-cs-cv

GIST: Gauge-Invariant Spectral Transformers for Scalable Graph Neural Operators

arXiv:2603.16849v2 Announce Type: replace Abstract: Adapting transformer positional encodings to graphs and meshes faces a fundamental tension: exact spectral methods require cubic-complexity eigendec

researcharxiv-cs-lg

GLEaN: A Text-to-image Bias Detection Approach for Public Comprehension

arXiv:2604.09923v1 Announce Type: new Abstract: Text-to-image (T2I) models, and their encoded biases, increasingly shape the visual media the public encounters. While researchers have produced a rich

safetyarxiv-cs-ai

Global Geometry of Orthogonal Foliations of Signed-Quadratic Systems

arXiv:2604.01912v2 Announce Type: replace-cross Abstract: This work formalizes the differential topology of redundancy resolution for systems governed by signed-quadratic actuation maps. By analyzing

researcharxiv-cs-ro

Local Ai

Global monitoring of methane point sources using deep learning on hyperspectral radiance measurements from EMIT

arXiv:2604.10094v1 Announce Type: new Abstract: Anthropogenic methane (CH4) point sources drive near-term climate forcing, safety hazards, and system inefficiencies. Space-based imaging spectroscopy i

local-aiarxiv-cs-cv

GlobalCY I: A JAX Framework for Globally Defined and Symmetry-Aware Neural Kahler Potentials

model-releasesarxiv-cs-lg

arXiv:2604.11404v1 Announce Type: cross Abstract: We present GlobalCY, a JAX-based framework for globally defined and symmetry-aware neural Kahler-potential models on projective hypersurface Calabi--Y

GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning

arXiv:2505.17022v2 Announce Type: replace-cross Abstract: Visual generation models have made remarkable progress in creating realistic images from text prompts, yet struggle with complex prompts that

Agents

Governance by Design: A Parsonian Institutional Architecture for Internet-Wide Agent Societies

arXiv:2604.11337v1 Announce Type: cross Abstract: The dominant paradigm of local multi-agent systems -- orchestrated, enterprise-bounded pipelines -- is being superseded by internet-wide agent societi

agentsarxiv-cs-ai

Governed Reasoning for Institutional AI

arXiv:2604.10658v1 Announce Type: new Abstract: Institutional decisions -- regulatory compliance, clinical triage, prior authorization appeal -- require a different AI architecture than general-purpos

Hardware

GPU-Accelerated Continuous-Time Successive Convexification for Contact-Implicit Legged Locomotion

arXiv:2604.09993v1 Announce Type: new Abstract: Contact-implicit trajectory optimization (CITO) enables the automatic discovery of contact sequences, but most methods rely on fine time discretization

hardwarearxiv-cs-ro

Hardware

GPU Acceleration of Sparse Fully Homomorphic Encrypted DNNs

arXiv:2604.11659v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) has recently attracted significant attention as both a cryptographic primitive and a systems challenge. Given the l

hardwarearxiv-cs-lg

Local Ai

Gradient-based Optimisation of Modulation Effects

arXiv:2601.04867v2 Announce Type: replace-cross Abstract: Modulation effects such as phasers, flangers and chorus effects are heavily used in conjunction with the electric guitar. Machine learning bas

local-aiarxiv-cs-lg

Gradient-Variation Regret Bounds for Unconstrained Online Learning

model-releasesarxiv-cs-lg

arXiv:2604.11151v1 Announce Type: new Abstract: We develop parameter-free algorithms for unconstrained online learning with regret guarantees that scale with the gradient variation V_T(u) = sum_{t=2}^

Graph-Coarsening Approach for the Capacitated Vehicle Routing Problem with Time Windows

arXiv:2510.22329v2 Announce Type: replace Abstract: The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is a fundamental NP-hard optimization problem in logistics. Solving large-scale i

Graph Retention Networks for Dynamic Graphs

model-releasesarxiv-cs-lg

arXiv:2411.11259v3 Announce Type: replace Abstract: In this paper, we propose Graph Retention Networks (GRNs) as a unified architecture for deep learning on dynamic graphs. The GRN extends the concept

Graph-RHO: Critical-path-aware Heterogeneous Graph Network for Long-Horizon Flexible Job-Shop Scheduling

arXiv:2604.10073v1 Announce Type: cross Abstract: Long-horizon Flexible Job-Shop Scheduling~(FJSP) presents a formidable combinatorial challenge due to complex, interdependent decisions spanning exten

Local Ai

GraspSense: Physically Grounded Grasp and Grip Planning for a Dexterous Robotic Hand via Language-Guided Perception and Force Maps

arXiv:2604.05697v2 Announce Type: replace Abstract: Dexterous robotic manipulation requires more than geometrically valid grasps: it demands physically grounded contact strategies that account for the

local-aiarxiv-cs-ro

Grid2Matrix: Revealing Digital Agnosia in Vision-Language Models

arXiv:2604.09687v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel on many multimodal reasoning benchmarks, but these evaluations often do not require an exhaustive readout of the i

GrOCE:Graph-Guided Online Concept Erasure for Text-to-Image Diffusion Models

arXiv:2511.12968v2 Announce Type: replace Abstract: Concept erasure aims to remove harmful, inappropriate, or copyrighted content from text-to-image diffusion models while preserving non-target semant

Grounded Forcing: Bridging Time-Independent Semantics and Proximal Dynamics in Autoregressive Video Synthesis

arXiv:2604.06939v2 Announce Type: replace Abstract: Autoregressive video synthesis offers a promising pathway for infinite-horizon generation but is fundamentally hindered by three intertwined challen

Grounded World Model for Semantically Generalizable Planning

arXiv:2604.11751v1 Announce Type: cross Abstract: In Model Predictive Control (MPC), world models predict the future outcomes of various action proposals, which are then scored to guide the selection

GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMs

arXiv:2511.11653v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have emerged as powerful tools for passage reranking in information retrieval, leveraging their superior reasonin

GS4City: Hierarchical Semantic Gaussian Splatting via City-Model Priors

arXiv:2604.11401v1 Announce Type: new Abstract: Recent semantic 3D Gaussian Splatting (3DGS) methods primarily rely on 2D foundation models, often yielding ambiguous boundaries and limited support for

GTASA: Ground Truth Annotations for Spatiotemporal Analysis, Evaluation and Training of Video Models

arXiv:2604.10385v1 Announce Type: new Abstract: Generating complex multi-actor scenario videos remains difficult even for state-of-the-art neural generators, while evaluating them is hard due to the l

safetyarxiv-cs-cv

Gypscie: A Cross-Platform AI Artifact Management System

arXiv:2604.10311v1 Announce Type: new Abstract: Artificial Intelligence (AI) models, encompassing both traditional machine learning (ML) and more advanced approaches such as deep learning and large la