Search: “framework”

NBA_Streaming: A Large-Scale Benchmark for Fine-Grained Basketball Commentary Generation in Continuous Streams

model-releasesarxiv-cs-cv

arXiv:2608.09200v1 Announce Type: new Abstract: Live basketball commentary generation requires determining when an event is sufficiently observable and describing it before subsequent events unfold. H

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Neural Message Passing on Structural Interaction Graphs for Fully-Inductive Graph Neural Networks

DGX agent

arXiv:2608.08567v1 Announce Type: new Abstract: A central obstacle in building graph foundation models is the input heterogeneity in terms of feature space dimensionality, semantics, and structure. Su

safetyarxiv-cs-lg

11 Aug 2026

NeuralDMD: Interpretable Neural Representation of Dynamics from Sparse and Noisy Measurements

arXiv:2507.03094v2 Announce Type: replace Abstract: Many challenges in scientific imaging involve solving ill-posed inverse problems, where the goal is to recover spatio-temporal fields from indirect,

researcharxiv-cs-cv

OccAnyScene: Towards Unified Indoor-Outdoor 3D Occupancy Predictio

arXiv:2608.08696v1 Announce Type: new Abstract: 3D occupancy prediction is fundamental to scene understanding, yet existing 3D semantic occupancy methods are typically specialized to fixed scene types

researcharxiv-cs-cv

OD-Gear: Online Decomposition and Group Sampling for Expert-Guided Adversarial Routing in Scalable Capacitated Vehicle Routing

arXiv:2602.00488v3 Announce Type: replace Abstract: Solving large-scale capacitated vehicle routing problems (CVRP) is hindered by the high complexity of classical heuristics and the limited generaliz

safetyarxiv-cs-lg

Open Evaluation Agent: Efficient and Promptable Evaluation of Visual Generative Models

arXiv:2608.09666v1 Announce Type: new Abstract: Recent advances in visual generative models have enabled high-quality image and video generation, but evaluating these models often demands sampling hun

Hardware

Physics-Informed Condition Monitoring of SiC Power Modules

arXiv:2608.08363v1 Announce Type: cross Abstract: Silicon carbide (SiC) power modules are increasingly deployed in automotive traction inverters, where condition monitoring is essential to prevent in-

hardwarearxiv-cs-lg

PosBridge: Multi-View Positional Embedding Transplant for Identity-Aware Image Editing

arXiv:2508.17302v2 Announce Type: replace Abstract: Localized subject-driven image editing aims to seamlessly integrate user-specified objects into target scenes. As generative models continue to scal

local-aiarxiv-cs-cv

Predicting blood clot growth from sparse post-onset measurements with latent neural differential equations

arXiv:2608.08165v1 Announce Type: new Abstract: Computational models of blood clotting improve understanding of thrombus formation, but their clinical application remains limited because many model in

Applications

Protecting patient privacy in clinical foundation models: Technical and legal perspectives

arXiv:2608.07705v1 Announce Type: new Abstract: Clinical foundation models trained on large-scale patient data are increasingly used for decision support, screening, and public health. As deployment e

applicationsarxiv-cs-ai

RA-FinBERT: Rule-aware LoRA adaptation for low-resource financial sentiment classification

model-releasesarxiv-cs-cl

arXiv:2608.09834v1 Announce Type: new Abstract: Financial sentiment analysis converts unstructured financial news into quantitative signals that can support market analysis and decision-making. Existi

ReMIND: Orchestrating Modular Large Language Models for Controllable Serendipity A REM-Inspired System Design for Emergent Creative Ideation

arXiv:2601.07121v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used not only for problem solving but also for creative ideation; however, generating ideas that

researcharxiv-cs-ai

RL-Native Distillation: Exploiting Scored Trajectories for Few-Step Image Generation

arXiv:2608.09226v1 Announce Type: cross Abstract: Efficient text-to-image generation requires both reinforcement-learning (RL)-based reward alignment and few-step distillation, yet these procedures ar

Tutorials

Robust Reputation-Driven Crowdsourced Federated Learning

arXiv:2608.08574v1 Announce Type: new Abstract: Crowdsourced Federated Learning (CrowdFL) extends traditional federated learning by enabling open and heterogeneous participation through a crowdsourcin

tutorialsarxiv-cs-lg

RouteGuard: Certifying Routing Gain in LLM Multi-Agent Systems When Complementarity Is Not Enough

arXiv:2608.07583v1 Announce Type: cross Abstract: Multi-agent LLM systems route among model-backed advisors, yet a deployer rarely knows before shipping whether routing will help at all. Prevailing ro

SAFE-CHEM: Uncertainty-Aware Policy Switching for Robust Robotic Chemistry

arXiv:2608.09303v1 Announce Type: cross Abstract: The deployment of autonomous robotic systems in chemistry laboratories is accelerating experimental workflows and providing the foundational data for

safetyarxiv-cs-lg

SkillsMetric: Mapping the Detection Boundary of Static Analysis for Malicious Agent Skills

arXiv:2608.08468v1 Announce Type: cross Abstract: Agent Skills---structured packages of instructions and scripts that augment LLM-based agents---are rapidly proliferating, yet their security propertie

SLAP: Selective Local Vision-Language Alignment for Fish Re-Identification via Partial Optimal Transport

arXiv:2608.08840v1 Announce Type: new Abstract: Individual fish re-identification (ReID) is a fine-grained recognition problem in which identity-discriminative cues are often localized to specific bod

local-aiarxiv-cs-cv

SurgLAT: Surgical Latent Attention Tracking for Depth-Aware Robotic Laparoscope Control

arXiv:2608.07876v1 Announce Type: new Abstract: Autonomous laparoscopic camera control requires continuous understanding of the surgeon's operative intent in dynamic surgical scenes, where the target

SurveyReview: A Reviewer-Aligned Benchmark for Survey Evaluators

model-releasesarxiv-cs-cl

arXiv:2608.07641v1 Announce Type: new Abstract: The rapid advancement of large language models has transformed survey writing from a months-long manual effort into an automated process. As generation

TeaMatch: Teachable Cross-Modal Representation Learning for 2D-3D Matching

arXiv:2608.09590v1 Announce Type: new Abstract: Learning reliable correspondences between images and point clouds is fundamental for 2D-3D matching. Despite recent progress in detection-free methods,

researcharxiv-cs-cv

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers

model-releasesarxiv-cs-cl

arXiv:2608.08809v1 Announce Type: new Abstract: A single model scale challenges the flexibility of a production retrieval system: some settings need it faster, others need a smaller index, and the rig

The Anatomy of a Prompt Injection: A Component Model for Structured Analysis

arXiv:2608.07808v1 Announce Type: cross Abstract: Four years after prompt injection was first identified in 2022, attacks are still predominantly documented as verbatim strings rather than structured

Applications

Three Generations of Healthcare IT: From the Digital Record to the Computable Care Process

arXiv:2608.08806v1 Announce Type: new Abstract: Objective. Healthcare IT is usually organized by the technologies it adopts. We instead organize it by the unit of information a system makes computable

applicationsarxiv-cs-ai

Towards Realistic Guarantees: A Probabilistic Certificate for SmoothLLM

arXiv:2511.18721v4 Announce Type: replace-cross Abstract: The SmoothLLM defense provides a certification guarantee against jailbreaking attacks, but it relies on a strict 'k-unstable' assumption that

Transformers for Multimodal Brain State Decoding: Integrating Functional Magnetic Resonance Imaging Data and Medical Metadata

arXiv:2512.08462v2 Announce Type: replace Abstract: Decoding brain states from functional magnetic resonance imaging (fMRI) data is vital for advancing neuroscience and clinical applications. While tr

researcharxiv-cs-lg

TrustRoboReward: Preference-Ordered Isotonic Score Editing for Multi-Paradigm Robot Reward Models

arXiv:2608.08491v1 Announce Type: new Abstract: Reward models are a bottleneck for reinforcement learning in embodied AI. Long-horizon robotic manipulation requires scalable vision feedback beyond han

VCU-Bridge: Hierarchical Visual Connotation Understanding via Semantic Bridging

arXiv:2511.18121v2 Announce Type: replace-cross Abstract: While Multimodal Large Language Models (MLLMs) excel on benchmarks, their processing paradigm differs from the human ability to integrate visu

Applications

View-Adaptive Renderer for View-Consistent 2D-to-3D Generation

arXiv:2608.09110v1 Announce Type: new Abstract: Reconstructing 3D shapes from a single image remains a fundamental yet challenging problem in computer vision. Traditional monocular 3D generation pipel

applicationsarxiv-cs-cv

VTO: Visual Tool Orchestration for Video Anomaly Detection

arXiv:2608.08219v1 Announce Type: cross Abstract: Video anomaly detection (VAD) is a critical yet challenging task due to the complex and diverse nature of real-world scenarios. Traditional deep learn

When should we trust the annotation? Selective prediction for molecular structure retrieval from mass spectra

arXiv:2603.10950v2 Announce Type: replace Abstract: Machine learning methods for identifying molecular structures from tandem mass spectra (MS/MS) have advanced rapidly, yet current approaches still e

Wisdom in Unity: The Role of Multilingual Training in Figurative Language Identification in Proverbs

arXiv:2608.08090v1 Announce Type: new Abstract: Although multilingual approaches to figurative language identification are not new, the shift beyond language homogeneous training data requires a clear

researcharxiv-cs-cl

Agentic Planning for Symbolic Execution

arXiv:2608.06397v1 Announce Type: cross Abstract: Symbolic execution seeks to explore feasible program paths, yet a practical run may exhaust its resources while much program behaviour remains unreach

Certified Interpolation Oversampling: Per-Instance Safety Guarantees for Imbalanced Learning

arXiv:2501.15790v2 Announce Type: replace Abstract: Synthetic minority oversampling is typically designed and evaluated against a predictive objective, generating samples that improve downstream class

Cloud-Boosted Low-Compute Multi-Channel Speech Enhancement

arXiv:2608.07423v1 Announce Type: cross Abstract: Low-latency, low-compute speech enhancement is essential for wearable devices with real-time communication requirements, but strict computational cons

local-aiarxiv-cs-lg

CoBa: Cost-Effective Test-Time Scaling via Compute-Balanced Routing

arXiv:2608.07424v1 Announce Type: new Abstract: Test-time scaling is often implemented by spending more compute along one axis: sampling more solutions, extending a chain of thought, or applying a str

ControlRef: Efficient Layout-Guided Multi-Instance Generation via Anchored 4D-RoPE

arXiv:2608.06878v1 Announce Type: new Abstract: Layout-guided multi-instance generation is essential for controllable image synthesis in Multi-Modal Diffusion Transformers (MM-DiTs). However, integrat

local-aiarxiv-cs-cv

Counterfactual Shapley Credit Assignment

arXiv:2607.16999v2 Announce Type: replace-cross Abstract: The Credit Assignment Problem (CAP) is fundamental to developing efficient and explainable Reinforcement Learning (RL) agents. Existing framew

Counterfactual Simulation Training for Chain-of-Thought Faithfulness

arXiv:2602.20710v2 Announce Type: replace Abstract: Inspecting Chain-of-Thought reasoning is among the most common means of understanding why an LLM produced its output. But well-known problems with C

researcharxiv-cs-ai

DA-Cal: Towards Cross-Domain Calibration in Semantic Segmentation

arXiv:2602.20860v2 Announce Type: replace Abstract: While existing unsupervised domain adaptation (UDA) methods greatly enhance target domain performance in semantic segmentation, they often neglect n

safetyarxiv-cs-cv

Decentralized Indoor Localization Based on A Sparse Gaussian Process with Reduced-Dimensional Inputs for Real-Time Sensing and Training on IoT Devices

arXiv:2409.00078v2 Announce Type: replace-cross Abstract: As a large number of Internet of Things (IoT) devices are deployed in the field, there arises huge potential of edge computing for indoor loca

local-aiarxiv-cs-lg

Diffusion LLMs as Targets and Adversaries: Mechanistic Safety Exploits

arXiv:2608.07430v1 Announce Type: cross Abstract: Diffusion Large Language Models (DLLMs) replace autoregressive next-token prediction with iterative parallel denoising, yet their internal safety mech

Edge Sparsification via Temporal Forman-Ricci Curvature for Dynamic Graph Learning

arXiv:2608.07158v1 Announce Type: new Abstract: Temporal graph learning has become essential for analyzing real-world systems whose interactions continuously evolve over time, including financial tran

FedTransKD-IDS: Robust Federated Transfer Learning with Knowledge Distillation for Intrusion Detection in IoT

arXiv:2608.06447v1 Announce Type: cross Abstract: In modern distributed network environments, particularly in Internet of Things infrastructures and 5G networks, stringent privacy preservation and sca

researcharxiv-cs-lg

Fixed and Adaptive Topological DeepONets: Functional Measurements on Hausdorff Locally Convex Spaces

arXiv:2608.06428v1 Announce Type: new Abstract: Deep Operator Networks (DeepONets; arXiv:1910.03193) typically encode an input function through point values on a fixed discretization. Building on the

local-aiarxiv-cs-lg

GeoBenchLLM: A Comprehensive Benchmark for Evaluating LLMs on Geo-Related Tasks

arXiv:2608.07411v1 Announce Type: new Abstract: In the context of geodata, existing Large Language Models have often been studied in a homogeneous setting, which has considerably limited insights into

Kimi K2.5: Visual Agentic Intelligence

arXiv:2602.02276v2 Announce Type: replace-cross Abstract: We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint op

Learning to Walk With Less: A Dyna-Style Approach to Quadrupedal Locomotion

arXiv:2509.06296v2 Announce Type: replace-cross Abstract: Traditional on-policy reinforcement learning (RL) controllers for quadrupedal locomotion often suffer from low data efficiency, requiring mill