All entries

From We to Me: Theory Informed Narrative Shift with Abductive Reasoning

model-releasesarxiv-cs-cl

arXiv:2603.03320v2 Announce Type: replace Abstract: Effective communication often relies on aligning a message with an audience's narrative and worldview. Narrative shift involves transforming text to

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Applications

Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction

DGX agent

arXiv:2608.01202v1 Announce Type: new Abstract: Fruit ripeness prediction (FRP) is a classification-based agricultural computer vision task that has attracted much attention, thanks to its wide-rangin

applicationsarxiv-cs-cv

4 Aug 2026

Fused Bayesian Flow Networks for Dual-Target Molecular Design

arXiv:2608.01007v1 Announce Type: new Abstract: Dual-target drug design aims to generate 3D molecules that can simultaneously interact with two target proteins, offering a promising route for discover

FusionRS: A Large-Scale RGB-Infrared-Style Remote Sensing Dataset for Cross-Modal Vision-Language Learning

arXiv:2606.17020v2 Announce Type: replace Abstract: Remote sensing vision-language models have advanced Earth observation, but available large-scale vision-language resources remain RGB-centered, leav

safetyarxiv-cs-cv

G-Skin: Learning to Bind 3D Gaussians with Generative Visual Priors

arXiv:2608.01726v1 Announce Type: new Abstract: 3D Gaussian Splatting has achieved remarkable success in photorealistic and efficient rendering, leading to a rapid increase in 3D assets represented by

Gaokerena: A Small Persian Medical Language Model Family

model-releasesarxiv-cs-cl

arXiv:2608.00932v1 Announce Type: new Abstract: The integration of artificial intelligence into medical question-answering systems has advanced rapidly; however, research remains predominantly focused

GAPSL: A Gradient-Aligned Parallel Split Learning over Data-Heterogeneous Edge Computing Systems

arXiv:2603.18540v2 Announce Type: replace Abstract: The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge dev

safetyarxiv-cs-lg

Applications

GaussianSelector: Lightweight Human-Guided Object Selection in 3D Gaussian Splatting with Graph Optimization

arXiv:2608.01492v1 Announce Type: new Abstract: Selecting a complete 3D object from a reconstructed scene with minimal user effort is essential for practical scene editing and embodied interaction. Ex

applicationsarxiv-cs-cv

Tutorials

Gecko: Fast Private Inference via Secure Public Encoder Offloading

arXiv:2608.02378v1 Announce Type: new Abstract: Private inference protects both user inputs and server models during neural network inference, but existing solutions remain too slow for practical depl

tutorialsarxiv-cs-lg

GeminiPainter's sequence-formed pipeline comprised of perception, cognition, planning, and action stages

model-releasesarxiv-cs-ro

arXiv:2608.00829v1 Announce Type: new Abstract: We present an autonomous robotic portrait-generation system combining real-time face detection, AI-based sketch generation, and robotic drawing. The sys

Local Ai

Generalized Quadratic Gradient: A New Direction in Optimization via the Fusion of Positive-Definite Curvature Matrices and Gradients into A Unified Framework

arXiv:2608.01552v1 Announce Type: cross Abstract: Quadratic Gradient (QG) is a Newton-type optimization framework that bridges first-order gradient descent and second-order optimization by incorporati

local-aiarxiv-cs-lg

Generated Images Are Easier to Forget: A Machine Unlearning Perspective for Synthetic Image Detection

arXiv:2608.00716v1 Announce Type: new Abstract: Robust detection of generated images is critical to counter the misuse of generative models. Existing methods primarily depend on learning from human-an

Generative AI and Foundation Models in Medical Image

arXiv:2608.01686v1 Announce Type: new Abstract: In recent years, generative AI has attracted significant public attention, and its use has been rapidly expanding across a wide range of domains. From c

Tutorials

Generative Brownian Bridge Diffusion In Motion Space For Enhanced Myocardial Strain Analysis

arXiv:2608.01677v1 Announce Type: new Abstract: Myocardial strain analysis of cardiac magnetic resonance (CMR) images provides an important tool for evaluating cardiac function. However, current techn

tutorialsarxiv-cs-cv

Generative Models for Modeling and Synthesizing MIMO Channels in Adverse Weather Conditions

arXiv:2608.00156v1 Announce Type: cross Abstract: The push for broader coverage in future cellular networks depends on reliable service, yet this is increasingly harder to do as we encounter more inst

researcharxiv-cs-lg

Generic Vision and Cross-Attention for Reaction Yield Prediction

arXiv:2608.00776v1 Announce Type: new Abstract: Traditional reaction yield prediction is constrained by 1D quantum descriptors that lack explicit spatial information. To address this gap, a dual-modal

researcharxiv-cs-lg

GenPrior: Unleashing Text-to-Motion Generative Priors for Zero-Shot Skeleton-based Action Recognition

arXiv:2608.02236v1 Announce Type: new Abstract: Zero-shot skeleton-based action recognition (ZSAR) aims to recognize unseen action categories by aligning skeleton features with textual semantics. Howe

GenTrack: Physical Alignment for Robot-Native Motion Generation and Zero-Shot Humanoid Tracking

arXiv:2608.01410v1 Announce Type: cross Abstract: General-purpose humanoid trackers can execute diverse references, but their zero-shot coverage depends on large embodied corpora that are costly to ex

safetyarxiv-cs-cv

GeoArbiter: Verifiability-Guided Grounding for Remote-Sensing Multimodal LLMs

arXiv:2608.00877v1 Announce Type: new Abstract: Remote-sensing multimodal large language models (MLLMs) often assert facts that imagery cannot establish, such as a facility's identity or function. Coo

safetyarxiv-cs-lg

GeoCore-9B: Towards Geo-Aware Generative Foundation Models in Earth Observation

arXiv:2608.01896v1 Announce Type: new Abstract: Existing generative models for earth observation (EO) predominantly rely on fine-tuning natural image priors, which limits their scalability and introdu

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation

arXiv:2608.02315v1 Announce Type: new Abstract: Geospatial foundation models aim to learn representations that transfer across regions and sensors, yet evaluating them on specific tasks requires large

Geometric Analysis of Token Selection in Multi-Head Attention

arXiv:2602.01893v2 Announce Type: replace-cross Abstract: We present a geometric framework for analysing multi-head attention in large language models (LLMs). Without altering the mechanism, we view s

Local Ai

Geometric-Topological Perception and Motion Prior for Real-Time Satellite Video Object Tracking

arXiv:2603.07564v2 Announce Type: replace Abstract: Satellite video object tracking (SVOT) remains fundamentally challenging due to texture scarcity, arbitrary rotation, aspect ratio changes, and seve

local-aiarxiv-cs-cv

Geometry-guided Emotion Modulation for Controllable and Photorealistic Emotional Talking Face Generation

arXiv:2608.00663v1 Announce Type: new Abstract: Audio-driven emotional talking face generation aims to synthesize realistic videos with expressive facial dynamics. However, existing methods struggle t

Geometry-Guided Layerwise FFN Width Allocation in Transformers

arXiv:2608.02064v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) account for a large fraction of Transformer parameters, yet their hidden width is usually constant across depth. We ask w

researcharxiv-cs-cl

GIFT: Geometry-Invariant Fine-Tuning for Non-Lambertian Monocular Depth Estimation

arXiv:2608.02068v1 Announce Type: new Abstract: Monocular depth foundation models, benefiting from large-scale synthetic training data, have demonstrated strong generalization. However, they often hal

Gimbal360: Canonicalizing Planar Diffusion for Spherical Panorama Completion

arXiv:2603.23179v2 Announce Type: replace Abstract: Diffusion models provide powerful priors for 2D image completion, but these priors are learned on bounded planar images and do not transfer directly

Tutorials

GLAIM: Learning Global and Local Adaptive Inter-Variable Dependency for Multivariate Time Series Imputation

arXiv:2608.02366v1 Announce Type: new Abstract: Multivariate time series imputation is fundamental to downstream analysis, yet modeling inter-variable dependencies with incomplete observations remains

tutorialsarxiv-cs-lg

Global Optimization and Inference-Time Region Grafting for Agentic Workflows

model-releasesarxiv-cs-cl

arXiv:2608.02353v1 Announce Type: new Abstract: Recent advances in agentic workflow optimization automate workflow design through task-specific workflow search or input-conditioned architecture select

Applications

Global-Scale Self-Supervised Spatiotemporal Learning for NDVI Time-Series Reconstruction

arXiv:2608.02322v1 Announce Type: new Abstract: Accurate and efficient reconstruction of cloud-contaminated and noise-corrupted NDVI time series remains a challenge in remote sensing. Deep learning pr

applicationsarxiv-cs-cv

Applications

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM

arXiv:2509.22910v2 Announce Type: replace Abstract: Given that Visual SLAM relies on appearance cues for localization and scene understanding, texture-less or visually degraded environments (e.g., pla

applicationsarxiv-cs-ro

Local Ai

GPrune-LLM: Generalization-Aware Structured Pruning for Large Language Models

arXiv:2603.13418v2 Announce Type: replace Abstract: Structured pruning is widely applied to compress large language models (LLMs), but its performance depends heavily on how neuron importance is estim

local-aiarxiv-cs-lg

GradCuit: Credit-Assigned Gradient Flow Enables Robust and Interpretable Test-Time Latent Reasoning

arXiv:2608.02585v1 Announce Type: cross Abstract: Optimization-based latent reasoning improves large language model outputs by optimizing instance-specific continuous states at test time while keeping

researcharxiv-cs-cl

Gram-Space: Structure-Preserving Codebook Compression for Memory-Efficient Neuro-Symbolic AI

arXiv:2608.01528v1 Announce Type: new Abstract: Vector symbolic architectures (VSA) are widely used for reasoning in neuro-symbolic (NeSy) AI, yet high-dimensional codebooks often create severe memory

GraphIR: Architecture-Level Search States for LLM-Guided Neural Architecture Evolution

arXiv:2608.01633v1 Announce Type: new Abstract: Large language models (LLMs) enable neural architecture search (NAS) directly over executable neural network programs. However, code-level flexibility d

GraRe: Grasp Candidate Re-Ranking for Frozen 6-DoF Grasp Detectors

arXiv:2608.00946v1 Announce Type: cross Abstract: Existing 6-DoF grasp detectors typically rank grasp candidates by detector confidence. However, our analysis on GraspNet-1Billion shows that detector

Grasp Execution Without a Planner: Configuration-Space Grasp Distance Fields with Certified Safety & Guaranteed Quality

model-releasesarxiv-cs-ro

arXiv:2608.00600v1 Announce Type: new Abstract: Standard multifingered grasp execution architectures plan a collision-free trajectory to a selected grasp pose and track it with a feedback law. Executi

Ground, Cover, and Refine: Evidence-Centric Frame Selection for Long-Video Question Answering

arXiv:2608.01660v1 Announce Type: new Abstract: Long-video question answering requires identifying sparse yet critical evidence from videos containing thousands of frames under a constrained visual-to

Grounded Semantic Re-Binding for Robust Instruction Generalization in Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2608.02497v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models excel in robotic manipulation but suffer catastrophic performance drops when canonical instructions are simply parap

Grounded Vision-Language Interpreter for Long-Horizon Bimanual Task and Motion Planning

arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees

safetyarxiv-cs-ro

Grounding Agentic VLMs with Dedicated Segmentation for Fine-Grained Vehicle Damage Assessment

arXiv:2608.02470v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed as reasoning agents in real-world visual assessment pipelines, yet their spatial grounding remai

Grounding and Explaining Visual Evidence for AI-Generated Image Detection in Human-Centric Scenes

arXiv:2608.01988v1 Announce Type: new Abstract: Rapid advances in image generation models call for interpretable AI-generated image detection methods that not only determine authenticity but also prov

GROVE: Growing and Reasoning over Temporally Stratified Memory from Streaming Video Experience

arXiv:2608.02392v1 Announce Type: new Abstract: A wearable assistant should both answer questions about its visual history and recognize when that history is useful to the present situation. Existing

Agents

GSRAIN: Physically Calibrated High-/Low-Frequency Rainfall Synthesis for 3D Gaussian Driving Scenes

arXiv:2608.02177v1 Announce Type: new Abstract: Existing rainfall simulation methods for autonomous driving remain limited in physical controllability and multi-view consistency. This paper presents G

agentsarxiv-cs-cv

GuideGround: VLM-guided Semantic Understanding and Viewpoint-aware Reasoning for 3D Visual Grounding

arXiv:2608.00518v1 Announce Type: new Abstract: 3D visual grounding aims to localize the target object in a 3D scene from a natural language query, requiring both fine-grained semantic understanding a

H+ Embedding: Harmonizing Global and Token-Level Retrieval with Context-Dependent Phrases

arXiv:2608.00065v1 Announce Type: cross Abstract: Terminology-intensive retrieval, especially in medical settings, depends on preserving multi-word entities, abbreviations, numerical constraints, and

researcharxiv-cs-lg

HAFI-VLM: A Frequency Perspective for Diagnosing and Enhancing Visual Perception in Vision-Language Models

arXiv:2608.02124v1 Announce Type: cross Abstract: Vision-language models (VLMs) remain unreliable when predictions require fine-grained visual evidence. We identify a previously overlooked cause: spec

researcharxiv-cs-cl

HapticVLA: Contact-Rich Manipulation via Vision-Language-Action Model without Inference-Time Tactile Sensing

arXiv:2603.15257v2 Announce Type: replace Abstract: Tactile sensing is a crucial capability for Vision-Language-Action (VLA) architectures, as it enables dexterous and safe manipulation in contact-ric

safetyarxiv-cs-ro