Search: “framework”

Efficient identification of critical regions via Flow Matching-based Monte Carlo initialization

arXiv:2508.15318v5 Announce Type: replace-cross Abstract: Markov chain Monte Carlo (MCMC) is a standard tool for studying many-body systems, but its practical cost can become substantial, especially w

researcharxiv-cs-lg

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Tutorials

Efficient Test-Time Scaling for LLM-based Time Series Forecasting

DGX agent

arXiv:2608.08675v1 Announce Type: new Abstract: Long-term time series forecasting benefits from preserving global structure such as trends and seasonality. Recent LLM-based forecasters often improve a

tutorialsarxiv-cs-lg

11 Aug 2026

Agents

El Agente Grafico: A Semantic Execution Runtime for Scientific Agents

arXiv:2602.17902v2 Announce Type: replace Abstract: Large language models (LLMs) can plan scientific workflows and generate code, but these capabilities do not specify how scientific state is validate

agentsarxiv-cs-ai

EMMR: Emotion-Mediated Multimodal Reasoning for Personality Assessment in Asynchronous Video Interviews

arXiv:2608.07512v1 Announce Type: cross Abstract: Asynchronous Video Interviews (AVIs) have become increasingly popular for personality assessment. Recent large language models (LLMs) have shown poten

Agents

Emotion2Skill: Model-Internal Emotion Signals for Adaptive Skill Selection and Evolution

arXiv:2608.09248v1 Announce Type: new Abstract: Skill-based LLM agents select reusable procedures from an external library to solve complex tasks, yet their routing decisions rely entirely on text-lev

agentsarxiv-cs-ai

End-to-End Neural Decomposition with Koopman Operators for Time-Series Forecasting

arXiv:2608.08788v1 Announce Type: cross Abstract: Koopman theory offers a linear-operator view of nonlinear sequence dynamics by lifting observations into a space where evolution is governed by a line

researcharxiv-cs-lg

EndoMD-SLAM: Endoscopic Gaussian Splatting SLAM under Optical Degradation with Memory and Static-Transient Decomposition

model-releasesarxiv-cs-cv

arXiv:2608.08949v1 Announce Type: new Abstract: Dense 3D reconstruction is critical for clinical endoscopic navigation and documentation. While Gaussian Splatting SLAM systems show promise in this dom

EnergyBridge: Benchmarking Household Energy Management, User Participation, and Grid Flexibility

arXiv:2608.08691v1 Announce Type: new Abstract: Residential virtual power plants (VPPs) can provide grid flexibility by shifting household demand, but physical flexibility becomes dependable capacity

Enhancing Scientific Named Entity Recognition via Large Language Models: A Type-driven Multi-task Learning Approach

arXiv:2608.08636v1 Announce Type: cross Abstract: Scientific named entity recognition (SciNER) plays a crucial role in information extraction and knowledge discovery from scientific texts. Recently, l

Entropy-based Code Adversarial Translation for Real-world Repository Migration

arXiv:2608.09273v1 Announce Type: new Abstract: LLMs have demonstrated strong capabilities in code generation and automated program repair, but migrating an entire repository rarely produces a runnabl

Hardware

ERF-GS: Reconstructing Fast Motion from Disjoint Event-RGB Viewpoints

arXiv:2608.08531v1 Announce Type: new Abstract: Deep learning-driven representations such as neural radiance fields (NeRFs) and 3D Gaussian splatting (3DGS) have revolutionized the field of dynamic 3D

hardwarearxiv-cs-cv

Hardware

EsaacSim: A Multimodal Event Camera Add-on for NVIDIA Isaac Sim

arXiv:2608.08522v1 Announce Type: new Abstract: Event-based vision is becoming an increasingly important sensing paradigm for robotics, yet its adoption remains limited by sensor availability and the

hardwarearxiv-cs-ro

Evaluation of Motivational Interviewing Counsellors with Task-Aware Multi-Stage LLM-Based Simulated Clients

arXiv:2608.07499v1 Announce Type: cross Abstract: The development and benchmarking of Large Language Model (LLM)-based Motivational Interviewing (MI) counsellors now often rely on LLM-based simulated

Applications

EvBS: Event-guided Blur Synthesis for Domain-adaptive Motion Deblurring

arXiv:2608.08066v1 Announce Type: new Abstract: Motion deblurring has achieved remarkable progress with deep learning, yet pre-trained deblurring models often suffer from performance degradation in re

applicationsarxiv-cs-cv

Evidence-Grounded Forensic Reasoning for Detecting and Grounding Multi-Modal Media Manipulation

arXiv:2608.08009v1 Announce Type: cross Abstract: Fake news increasingly relies on cross-modal image-text forgeries, making transparent and verifiable reasoning chains an urgent need for Detecting and

Evolving Safety Landscape of Multi-modal Large Language Models: A Survey of Emerging Threats and Safeguards

arXiv:2608.07535v1 Announce Type: cross Abstract: Multi-modal large language models (MLLMs) integrate heterogeneous modalities through modality alignment and fusion, enabling stronger understanding an

EvoTrustRAG: Evolution-Aware Conflict Attribution and Evidence Handling for Reliable Retrieval-Augmented Generation

model-releasesarxiv-cs-cl

arXiv:2608.07933v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves the factuality of large language models with external knowledge, yet conflicting evidence remains a fund

Applications

EvTrajGS: Accurate and Efficient 3D Gaussian Splatting from Unposed Event Streams

arXiv:2608.08585v1 Announce Type: new Abstract: Event cameras, with high temporal resolution, high dynamic range, and asynchronous sensing characteristics, have shown great potential for dense 3D reco

applicationsarxiv-cs-cv

Tutorials

Experience-Sensitive Game Learning: A Behavioral Study of Humans and Language Agents

arXiv:2608.07490v1 Announce Type: cross Abstract: Large language model agents are increasingly evaluated through games, but most benchmarks emphasize final outcomes rather than how players learn from

tutorialsarxiv-cs-ai

Explaining, Verifying, and Aligning Semantic Hierarchies in Vision-Language Model Embeddings

arXiv:2603.26798v2 Announce Type: replace-cross Abstract: Vision-language model (VLM) encoders such as CLIP enable strong retrieval and zero-shot classification in a shared image-text embedding space,

exttt{DisMorph}: learning to disentangle technical distortions from true biological change

arXiv:2608.08173v1 Announce Type: cross Abstract: Longitudinal MRI enables sensitive measurement of structural brain change for studying aging and neurodegenerative disease. Deformable image registrat

F2STNet: Fair and Federated Spectral-Temporal Modeling for Graph Forecasting

arXiv:2608.09082v1 Announce Type: new Abstract: Spatiotemporal prediction on graph-structured data is central to traffic forecasting and environmental monitoring, yet decentralized and heterogeneous d

safetyarxiv-cs-lg

FactorDrive: Adaptive Multi-Step Reasoning Driven by Planning-Critical Factors for End-to-End Autonomous Driving

arXiv:2608.09591v1 Announce Type: cross Abstract: Vision-language models (VLMs) have advanced scene understanding and enabled explicit reasoning in end-to-end autonomous driving. However, existing met

safetyarxiv-cs-cv

Agents

FailForge: Distilling Procedural Competence from Persistent Failures into Code Agents

arXiv:2608.08570v1 Announce Type: new Abstract: Rejection sampling fine-tuning (RFT) is widely used to train code agents by generating trajectories on verifiable software engineering tasks, retaining

agentsarxiv-cs-ai

Fair on the Surface? Benchmarking Hidden-Output Fairness Gaps in LLM Recommenders

arXiv:2608.08284v1 Announce Type: new Abstract: Fairness audits for LLM-based recommenders have largely focused on observable outputs, implicitly assuming that stable recommendations reflect stable in

FEAST: Federated Shared-Space Training for Resource-Heterogeneous Clients

model-releasesarxiv-cs-lg

arXiv:2608.09250v1 Announce Type: new Abstract: Federated learning (FL) must serve devices with varying computational capabilities. A fixed model cannot suit all devices, while training one model per

FeedbackTrack: Visual-Cortex-Inspired Cross-Frame Feedback for Transformer Tracking

arXiv:2608.09369v1 Announce Type: cross Abstract: Visual object tracking requires effective temporal integration, yet most Transformer trackers still rely on predominantly feed-forward feature extract

Finite basis physics-informed neural networks with hard constraints for viscous fluid flow in highly perforated domains

arXiv:2608.08114v1 Announce Type: cross Abstract: In this work, viscous fluid flow governed by the Stokes equations in highly perforated domains is studied using physics-informed neural networks (PINN

safetyarxiv-cs-lg

Local Ai

FiRe: Fixed-Noise Refinement for Visual Counterfactual Explanations

arXiv:2608.08664v1 Announce Type: new Abstract: Visual counterfactual explanations aim to change classifier decisions through realistic and localized edits while preserving decision-irrelevant content

local-aiarxiv-cs-cv

FitAQA: A Benchmark of Fitness Action Quality Assessment for Multimodal Large Language Models

arXiv:2608.08736v1 Announce Type: new Abstract: Fitness Action Quality Assessment (AQA) is important for intelligent sports training, yet the capabilities of Multimodal Large Language Models (MLLMs) i

FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records

arXiv:2505.16941v4 Announce Type: replace-cross Abstract: Foundation models (FMs) promise to address core limitations of traditional supervised machine learning: (i) reliance on large amounts of label

Tutorials

FreCast: Refining Radar Echo Intensity via Phase-Preserving Amplitude Residual Diffusion for Precipitation Nowcasting

arXiv:2608.08436v1 Announce Type: new Abstract: Precipitation nowcasting predicts the spatiotemporal evolution of future radar echoes from historical radar echo sequences, thereby estimating the occur

tutorialsarxiv-cs-cv

From Chains to DAGs: Probing the Graph Structure of Reasoning in LLMs

arXiv:2601.17593v3 Announce Type: replace Abstract: Recent progress in large language models has renewed interest in how multi-step reasoning is represented internally. While prior work often treats r

researcharxiv-cs-cl

From Diagnosis to Correction: Benchmarking and Improving Real-World Table Parsing

model-releasesarxiv-cs-cv

arXiv:2608.09842v1 Announce Type: new Abstract: Recent document parsers achieve table TEDS scores above 93 on OmniDocBench v1.6, yet community feedback and our audit reveal persistent failures on comp

From Manuals to Maintenance: Fine-Tuning MedGemma for Multi-Modal Imaging System Support in Low-Resource Settings

arXiv:2608.08896v1 Announce Type: new Abstract: Imaging device downtime is a major barrier to healthcare delivery in low- and middle-income countries (LMICs), often driven by limited access to special

From Mimicry to True Intelligence (TI) -- A New Paradigm for Artificial General Intelligence

arXiv:2509.14474v3 Announce Type: replace Abstract: The debate around Artificial General Intelligence (AGI) remains open due to two fundamentally different goals: replicating human-level performance v

From Noise to Meaning: Meaningful Secret Sharing with Tamper Detection for Facial Recognition

arXiv:2608.08924v1 Announce Type: new Abstract: Popularity of AI-based face recognition system directly demands protection of sensitive biometric data used for training. Visual secret sharing is an in

researcharxiv-cs-cv

From Operational Design Domain to Action: A Systematic Behavioral Taxonomy for Autonomous Driving

arXiv:2608.08941v1 Announce Type: cross Abstract: Operational Design Domain (ODD) specifications describe where an automated driving system (ADS) is permitted to operate, but they do not prescribe wha

Tutorials

From Trajectories to Evidence: Auditable Experimental Records for Industrial Research Agents

arXiv:2608.05235v1 Announce Type: cross Abstract: Research agents increasingly conduct multi-round machine-learning experiments in industrial recommendation settings and retain the resulting trajector

tutorialsarxiv-cs-ai

From Visual to Multimodal: Systematic Ablation of Encoders and Fusion Strategies in Animal Identification

arXiv:2603.02270v2 Announce Type: replace Abstract: Automated animal identification is a practical task for reuniting lost pets with their owners, yet current systems often struggle due to limited dat

researcharxiv-cs-cv

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks

arXiv:2608.09523v1 Announce Type: new Abstract: Deep neural network (DNN) training with stochastic gradient descent (SGD) and its variants achieves strong empirical performance, yet classical optimiza

safetyarxiv-cs-lg

GenTrack3: Hybrid Stochastic-Deterministic Online Multi-Object Tracking with Cluster-Aware Association

arXiv:2608.09581v1 Announce Type: new Abstract: Multi-object tracking (MOT) involves maintaining consistent target identities as objects dynamically enter and leave a scene. Deterministic approaches,

researcharxiv-cs-cv

Local Ai

GLocFM: A Geometry-Aware Foundation Model for 3D Indoor Wireless Localization

arXiv:2608.09285v1 Announce Type: cross Abstract: Learning-based wireless localizers often fail to utilize geometric information about the propagation environment, limiting their ability to exploit no

local-aiarxiv-cs-ai

Goal-oriented Navigation Instruction Generation with Tour Video Priors

model-releasesarxiv-cs-cv

arXiv:2608.08596v1 Announce Type: new Abstract: Navigation Instruction Generation (NIG) aims to produce step-by-step natural language instructions for navigation guidance. Existing studies primarily t

Goedel-Code-Prover: Hierarchical Proof Search for Open State-of-the-Art Code Verification

arXiv:2603.19329v3 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate plausible code but offer limited guarantees of correctness. Formally verifying that implementations

Goose: Anisotropic Speculation Trees for Training-Free Speculative Decoding

arXiv:2604.02047v2 Announce Type: replace-cross Abstract: Speculative decoding accelerates large language model inference by drafting multiple candidate tokens and verifying them in a single forward p

GRACE: LLM-Grounded Semantic Metric Spaces for Scalable Mixed-Data Clustering

arXiv:2608.07881v1 Announce Type: new Abstract: Clustering mixed tabular data requires a unified metric space to bridge the inherent heterogeneity between continuous numerical measurements and discret

Graph-Guided Safe Diffuser: Topological Graph Guidance for Safe Diffusion Planning

arXiv:2608.09484v1 Announce Type: new Abstract: Many diffusion-based planners enforce safety through inference-time guidance, but such interleaved trajectory deformations often degrade kinematic feasi

safetyarxiv-cs-ro