Search: “framework”

Fusing Sequence Motifs and Pan-Genomic Features: Antimicrobial Resistance Prediction using an Explainable Lightweight 1D CNN-XGBoost Ensemble

arXiv:2509.23552v2 Announce Type: replace Abstract: Antimicrobial Resistance (AMR) is a rapidly escalating global health crisis. While genomic sequencing enables rapid prediction of resistance phenoty

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Model Releases

GAN-Blot: A Controllable Structure-Style Synthesis Benchmark for Western Blot Forensics

DGX agent

arXiv:2609.06619v1 Announce Type: new Abstract: Western blot (WB) images are widely used as key evidence in biomedical research. Recent scientific misconduct cases reveal that WB imagery is increasing

model-releasesarxiv-cs-cv

9 Sept 2026

GIF: Agentic Generation of Interactive and Functional Object Compositions for Robot Learning

model-releasesarxiv-cs-ro

arXiv:2609.05927v1 Announce Type: new Abstract: Robot manipulation foundation models require scalable evaluation and data generation across diverse scenarios, with simulation providing an environment

GRAN-TED: Generating Robust, Aligned, and Nuanced Text Embedding for Diffusion Models

arXiv:2512.15560v3 Announce Type: replace Abstract: The text encoder is a critical component of text-to-image and text-to-video diffusion models, fundamentally determining the semantic fidelity of the

Applications

Granular-Ball Quantum Clustering for Resource-Efficient and Robust Learning

arXiv:2609.06016v1 Announce Type: new Abstract: Quantum clustering aims to exploit quantum feature representations to uncover complex data structures beyond conventional Euclidean geometry. Yet this s

applicationsarxiv-cs-lg

Guiding Worker Self-Selection in Crowdsourcing Contests: An LLM-Augmented Algorithmic Approach

arXiv:2609.07749v1 Announce Type: new Abstract: Crowdsourcing platforms coordinate large pools of online workers who strategically choose which contests to enter and how much effort to invest. This se

researcharxiv-cs-lg

How to Learn from What a Human Would Avoid? Intervention-Aware World Models with Real-World RL for Dexterous Manipulation

arXiv:2609.06009v1 Announce Type: new Abstract: Multi-fingered dexterous manipulation remains a frontier for real-world reinforcement learning (RL) due to the high-dimensional action space and the pro

ICI-VLA: In-Context Imitation with Spatiotemporally Aligned Demonstrations for Vision-Language-Action Models

arXiv:2609.07581v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are commonly adapted to new manipulation settings through additional gradient updates, which limits rapid deployme

Information-Guided Safe Reinforcement Learning for Autonomous Gas Source Localization using sUAS

arXiv:2609.05569v1 Announce Type: new Abstract: The autonomous localization of fugitive gas emissions using small Unmanned Aircraft Systems (sUAS) constitutes a fundamentally ill-posed inverse problem

local-aiarxiv-cs-ro

InSituRes: A Physics-Informed Same-Grid Model for Enhanced Dynamic X-ray Micro-CT Reconstructions

arXiv:2508.17708v2 Announce Type: replace Abstract: X-ray micro-computed tomography (micro-CT) provides non-destructive three-dimensional (3D) imaging of porous material microstructures. In situ exper

local-aiarxiv-cs-cv

L2G-Map: Local-to-Global Mapping via Hierarchical Diffusion Refinement and Elliptical Bayesian Fusion

arXiv:2503.02578v2 Announce Type: replace Abstract: Offline high-definition maps provide essential geometric and topological priors for autonomous driving systems. Pure-vision solutions have become th

Learning functional components of PDEs from data using neural networks

arXiv:2602.13174v2 Announce Type: replace Abstract: Partial differential equation (PDE) models frequently contain unknown functional terms that cannot be measured directly, limiting their predictive u

Learning Kernels by Alignment for Multiclass Bayes Classification

arXiv:2609.06474v1 Announce Type: new Abstract: Kernel methods separate data representation from decision-making, but typically require the kernel to be chosen in advance. We show that this kernel can

Leveraging Visual and Geometric Priors for Metric-scale and Complete Vehicle Gaussian Reconstruction from Limited Views

arXiv:2609.08841v1 Announce Type: new Abstract: High-fidelity vehicle assets are essential for controllable traffic scene generation, particularly for synthesizing rare and safety-critical long-tail s

safetyarxiv-cs-cv

Lightweight Dynamic Modeling of Cable-Driven Continuum Robots Based on Actuation-Space Energy Formulation

arXiv:2512.13271v2 Announce Type: replace Abstract: Cable-driven continuum robots (CDCRs) require accurate, real-time dynamic models for high-speed dynamics prediction or model-based control, making s

researcharxiv-cs-ro

Low-Rank Plus Sparse Matrix Transfer Learning under Growing Representations and Ambient Dimensions

arXiv:2601.21873v2 Announce Type: replace Abstract: Learning systems often expand their ambient features or latent representations over time, embedding earlier representations into larger spaces with

MedGSSR: Generalizable Medical Image Super-Resolution 3D Reconstruction via Hierarchical Feed-forward Gaussian Splatting

arXiv:2609.06874v1 Announce Type: cross Abstract: High-resolution volumetric medical imaging is critical for clinical diagnosis, yet acquisition is often limited by scanner hardware, scan time, and fo

local-aiarxiv-cs-cv

Memory in Deep Time-Series Models

arXiv:2609.06006v1 Announce Type: new Abstract: Deep learning for time series has progressed through successive architectural paradigms, from recurrent networks and transformers to structured state-sp

agentsarxiv-cs-lg

MI-PEFT: Mixture-of-Experts Integrated Parameter-Efficient Fine-Tuning Protein Language Models Improves Acidophilic Proteins Classification

arXiv:2609.08059v1 Announce Type: cross Abstract: Acidophilic proteins that remain stable and functional under highly acidic conditions, are important for industrial biocatalysis, acid-related bioproc

Mitigating Shortcut Learning: Texture-Penalized Prototype Networks

arXiv:2609.07504v1 Announce Type: new Abstract: Standard Convolutional Neural Networks (CNNs) exhibit severe performance degradation due to a strong inductive texture bias that prioritizes local, high

local-aiarxiv-cs-cv

MobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control

arXiv:2609.06251v1 Announce Type: new Abstract: Grounding natural-language instructions into reliable and executable actions remains a fundamental challenge for vision-language-action (VLA) systems on

safetyarxiv-cs-cv

MorphoOrgaAgent: A Foundation-Model-Based Multi-Agent System for Autonomous Organoid Analysis

arXiv:2609.08696v1 Announce Type: cross Abstract: Organoids are three-dimensional tissue models whose morphology provides important insights into tumor development, disease progression, and drug testi

Multi-Fidelity Physics-Informed Neural Networks with Bayesian Uncertainty Quantification and Adaptive Residual Learning for Efficient Solution of Parametric Partial Differential Equations

arXiv:2602.01176v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs) by embedding physical

Novel Methods for Catheter and Guidewire Segmentation in X-ray Fluoroscopy under a Federated Learning Setting

arXiv:2609.06876v1 Announce Type: new Abstract: Endovascular procedures rely on real-time manipulation of thin instruments, catheters and guidewires, under X-ray fluoroscopy guidance, where accurate v

Omni Interaction Agent Technical Report

arXiv:2609.08977v1 Announce Type: cross Abstract: In this work, we present Gander, an end-to-end model that unifies omni perception, realtime interaction, and agentic capabilities within a single fram

agentsarxiv-cs-lg

On the Recall Scaling Laws in Mamba: A Theoretical and Mechanistic Study via Hashing

arXiv:2609.07681v1 Announce Type: new Abstract: Associative Recall (AR) is the cognitive ability to learn and retrieve links between items in memory. In NLP, AR is used as a benchmark for evaluating t

ONE CYLinder: A Benchmark for Graph-Based Surrogate Modeling of Unsteady Bluff-Body Flows

arXiv:2609.08947v1 Announce Type: cross Abstract: Graph-based surrogate models offer a promising route to accelerate computational fluid dynamics (CFD) simulations on unstructured meshes. However, the

Online Signature Verification Using Augmented Path Signature and T-Mamba

arXiv:2609.08276v1 Announce Type: cross Abstract: Handwritten signature verification is vital for personal authentication across commercial and financial applications. Although deep learning methods a

Paul Christiano, founder of the Alignment Research Center, is joining the OpenAI Foundation Board and its Safety and Security Committee, whi…

Paul Christiano, founder of the Alignment Research Center, is joining the OpenAI Foundation Board and its Safety and Security Committee, which provides governance over the safety and security practice

safetyopenai--x

PhysVidBench: Language-Grounded Evaluation of Physical Commonsense in Text-to-Video Models

arXiv:2507.15824v2 Announce Type: replace Abstract: Text-to-video (T2V) models now produce striking visuals, yet they routinely violate everyday physics; objects float, tools are misused, and causal s

PlannerForge: LLM Agents for Scenario-Based Testing of Motion Planners in Autonomous Driving

arXiv:2609.08965v1 Announce Type: cross Abstract: Ensuring the safety of autonomous driving is a critical challenge. Scenario-based testing is a systematic process used to validate Autonomous Driving

Poisson Image Denoising Using Minimax Concave and Reweighted ell_1 Penalties: Nonblind and Blind Approaches

arXiv:2609.07916v1 Announce Type: new Abstract: Images are important tools in various sciences. Despite the development of photo-taking tools, creating clear and image without noise remains challengin

agentsarxiv-cs-cv

Radiation, Rotation and Scale Invariant Feature Descriptor for Multimodal Image Matching

arXiv:2609.06343v1 Announce Type: new Abstract: Multimodal image matching is a fundamental task for multi-source information fusion. However, geometric distortions and nonlinear radiometric difference

ReLI: Cross-Lingual Language-to-Action Grounding for Human-Robot Interaction

arXiv:2505.01862v4 Announce Type: replace Abstract: Adapting autonomous agents for real-world industrial, domestic, and other daily tasks is currently gaining momentum. However, in global or cross-lin

agentsarxiv-cs-ro

Reliable iToF Depth Sensing via Sensor-Intrinsic Uncertainty Modeling and State-Space Restoration

arXiv:2609.05507v1 Announce Type: cross Abstract: Indirect time-of-flight (iToF) cameras provide compact and cost-effective dense depth measurements, but their ranging accuracy is often degraded by se

RelightFormer: Feed-forward Generative Transformer for Multiview Object Relighting

arXiv:2609.07414v1 Announce Type: new Abstract: Image relighting is traditionally tackled via complex inverse rendering pipelines, which suffer from ill-posed optimization, or single-image generative

safetyarxiv-cs-cv

ReST-RL: Reinforcing LLM Reasoning through Unified Self-Training and Value-Guided Search

arXiv:2508.19576v3 Announce Type: replace-cross Abstract: With respect to improving the reasoning accuracy of LLMs, the representative reinforcement learning (RL) method - Group Relative Policy Optimi

Robust Conformal Consensus: Multi-Agent LLM-as-a-Judge Interval Evaluation with Conformal Prediction

arXiv:2609.06367v1 Announce Type: new Abstract: LLM-as-a-Judge has emerged as a promising paradigm for evaluating natural language generation. However, the uncertainty associated with such evaluations

agentsarxiv-cs-lg

S^3F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network

arXiv:2509.23442v2 Announce Type: replace-cross Abstract: Convolutional Neural Networks have become a cornerstone of medical image analysis due to their proficiency in learning hierarchical spatial fe

SEGA: Drivable 3D Gaussian Head Avatar from a Single Image

arXiv:2504.14373v4 Announce Type: replace-cross Abstract: Creating photorealistic 3D head avatars from limited input has become increasingly important for applications in virtual reality, telepresence

Single Image to Textured 3D Object Generation in Frequency Domain: From Theory to Pipeline

arXiv:2609.07085v1 Announce Type: new Abstract: Single-view 3D reconstruction, also known as image-to-3D, is a persistently challenging task due to the extreme lack of information. Recently, diffusion

Singularity-Free Guiding Vector Fields on SO(3) with Designer-Specified Progression Behavior

arXiv:2609.07269v1 Announce Type: new Abstract: This paper develops a singularity-free guiding vector field (SF-GVF) for path following on the special orthogonal group SO(3). First, we lift the Euclid

researcharxiv-cs-ro

Situation Awareness for Intelligent Data Distribution in Connected Vehicles

arXiv:2609.05521v1 Announce Type: cross Abstract: The limitations of on-board sensors and blind spots caused by occlusion cause the reduction of perception quality in autonomous vehicles. In such case

agentsarxiv-cs-cv

SLA-Safe Energy Control for AI-Native NG-RAN Using Stability-Aware Constrained PPO

arXiv:2609.05861v1 Announce Type: cross Abstract: One important AI-for-RAN use case is energy saving, in which radio resources and cell energy modes must be dynamically controlled without violating us

SMaRT-Tug: Structured Multi-Agent Reinforcement Learning for Physics-Based Tugboat-Barge Collaborative Manipulation

arXiv:2609.07445v1 Announce Type: new Abstract: Autonomous tugboating is central for automating maritime operations such as port logistics and vessel maneuvering, where multiple tugboats must cooperat

Streaming Hierarchical Inference with Tabular Foundation Models

arXiv:2609.07956v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) have recently demonstrated strong predictive performance through in-context learning, but their deployment in high-thro

TASG-Explore: Traversability-Aware Sector-Guided Exploration for Ground Robot on Uneven Terrain

model-releasesarxiv-cs-ro

arXiv:2609.08512v1 Announce Type: new Abstract: Autonomous exploration on uneven terrain requires ground robots to balance exploration efficiency, coverage completeness, and terrain safety. Detailed t

Task-Oriented Semantic Communication for Hazard Warning and Remote Operation in Connected Vehicle Platoons

arXiv:2609.06242v1 Announce Type: cross Abstract: Connected and automated vehicle platoons require reliable dissemination of task-relevant hazard information to enable appropriate downstream responses