Search: “framework”

Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis

arXiv:2607.04636v1 Announce Type: new Abstract: Key Information Extraction (KIE) converts visually rich documents into structured data, but practical deployment remains challenging: strong performance

local-aiarxiv-cs-cv

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Enhancing the Forecasting Capability of Multi-Model Blending Algorithms for Extreme Precipitation via Joint Use of Station and Gridded Observations

DGX agent

arXiv:2607.04862v1 Announce Type: new Abstract: Accurate extreme precipitation forecasting is critical for disaster mitigation but remains challenging for numerical weather prediction (NWP) models due

safetyarxiv-cs-lg

7 Jul 2026

Enhancing Video Physical Consistency via Role-aware Joint Training and Modality-decoupled Denoising

arXiv:2607.04653v1 Announce Type: new Abstract: While modern video diffusion models excel in visual fidelity, maintaining long-range physical consistency remains a formidable challenge. Conventional p

Environmental Drivers of Respiratory Disease: A District Level Analysis

arXiv:2607.04416v1 Announce Type: new Abstract: Sri Lanka has experienced a decade of progressive forest degradation and rising atmospheric pollution, yet district-level respiratory admissions have pa

safetyarxiv-cs-lg

Equivalence of Context and Parameter Updates in Modern Transformer Blocks

model-releasesarxiv-cs-lg

arXiv:2511.17864v3 Announce Type: replace Abstract: Recent research has established that the impact of context in a vanilla transformer can be represented implicitly by forming a token-dependent, rank

Evaluating Agentic Harness Systems for Autonomous Computational Pathology

arXiv:2607.02598v1 Announce Type: new Abstract: Autonomous computational pathology (ACP) converts high-level pathology analysis goals into executable, traceable and clinically bounded workflows. Reali

Agents

Evaluating Generative Agents with Actions Grounded in Socially Distributed Task Environments using Incognita

arXiv:2607.02975v1 Announce Type: new Abstract: Effective agency in social environments depends on when an agent seeks knowledge, when it acts, and whether its actions are justified by acquired inform

agentsarxiv-cs-ai

Evaluating Large Language Models for Antisemitic Incident Classification

model-releasesarxiv-cs-cl

arXiv:2607.04890v1 Announce Type: new Abstract: Addressing hate and violence in society requires timely detection of hateful events from public reporting, but automated identification of hateful event

Evaluating the Effect of Linguistic Relatedness on Cross-Lingual Transfer in Large Multilingual Automatic Speech Recognition

arXiv:2607.04814v1 Announce Type: cross Abstract: Extending automatic speech recognition (ASR) to low-resource African languages is constrained by the prohibitive demands of data collection at scale.

Evaluating Time Series Foundation Models for Electricity Price Forecasting: Contamination Risk, Distributional Shifts, and Covariate Dependence

arXiv:2607.02623v1 Announce Type: new Abstract: Time series foundation models (TSFMs) have shown strong zero-shot forecasting performance, but their generalization in covariate-driven, non-stationary

researcharxiv-cs-lg

EVAS: Efficient Multimodal Temporal Forgery Localization via Audio-Visual Synergy and Steered Boundary Calibration

arXiv:2607.04472v1 Announce Type: new Abstract: The rapid proliferation of artificial intelligence-generated content necessitates reliable multimodal forensics. Beyond video-level binary classificatio

EventCoT: Event-centric Video Chain-of-thought for Reasoning Temporal Localization

model-releasesarxiv-cs-ai

arXiv:2607.04872v1 Announce Type: cross Abstract: Reasoning temporal localization (RTL) requires a model to generate an answer that itself contains the time interval supporting it, so high-level reaso

EvoXplain: When Machine Learning Models Agree on Predictions but Disagree on Why -- Measuring Mechanistic Multiplicity Across Training Runs

arXiv:2512.22240v5 Announce Type: replace-cross Abstract: Machine learning models are primarily judged by predictive performance, especially in applied genomics, where explanations are read as biologi

Tutorials

Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks

arXiv:2503.10496v2 Announce Type: replace-cross Abstract: Modeling natural phenomena with artificial neural networks (ANNs) often provides highly accurate predictions. However, ANNs often suffer from

tutorialsarxiv-cs-ai

Explainable Novel Category Discovery in Semantic Concept Space

arXiv:2607.04548v1 Announce Type: cross Abstract: Novel category discovery aims to identify unseen classes from unlabeled data by transferring knowledge from labeled categories, but most existing meth

Explainable Reinforcement Learning for Adaptive Traffic Signal Control

arXiv:2607.03703v1 Announce Type: new Abstract: Reinforcement Learning (RL) has emerged as a powerful paradigm for adaptive traffic signal control. However, in safety-critical infrastructure like traf

safetyarxiv-cs-ai

Exploring the Rashomon Set for Concept-Based Models

arXiv:2511.19636v2 Announce Type: replace-cross Abstract: In many machine learning problems, there may exist multiple models that achieve nearly identical predictive performance while relying on funda

FairFlow: Demystifying and Mitigating Stereotype Bias in Text-to-Image Diffusion Transformers

arXiv:2607.03180v1 Announce Type: new Abstract: Multimodal diffusion transformers (MM-DiTs) have emerged as the prevalent backbone for modern text-to-image generation systems. However, they exhibit cr

FDR-Occ: Factorized Dense Routing for Full-Spectrum 3D Occupancy Prediction

arXiv:2607.03822v1 Announce Type: new Abstract: Vision-based 3D occupancy prediction fundamentally relies on the 2D-to-3D view transformation. Current paradigms predominantly utilize explicit physical

local-aiarxiv-cs-cv

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging

arXiv:2607.04158v1 Announce Type: cross Abstract: Federated learning (FL) is severely hindered by statistical heterogeneity due to variations in scanners, acquisition protocols, and patient population

FedSPM: Routing-Enabled Federated Learning under Dual Heterogeneity via Semiparametric Mixture

arXiv:2607.04085v1 Announce Type: cross Abstract: Routing-prediction federated learning has emerged as a new paradigm that reframes inter-client heterogeneity as a resource for system-level intelligen

local-aiarxiv-cs-ai

Few-Shot Demonstration-Driven Task Coordination and Trajectory Execution for Multi-Robot Systems

arXiv:2510.15686v2 Announce Type: replace Abstract: Learning coordinated behaviors for multi-robot systems from only a few demonstrations is difficult because temporal task dependencies and spatial tr

safetyarxiv-cs-ro

Fine-Grained Computation Offload for Off-the-Shelf Servers in Tens of Lines

arXiv:2607.02630v1 Announce Type: cross Abstract: Hardware accelerators now sit on the critical path of online serving. GPUs, FPGAs, and increasingly remote services such as hardware security modules,

applicationsarxiv-cs-ai

Fixed-Confidence Best-Arm Identification for Causal Mediation Analysis

arXiv:2607.04315v1 Announce Type: cross Abstract: This paper studies the problem of identifying the treatment that maximizes the expected natural direct potential outcome (NDPO), which captures the po

applicationsarxiv-cs-ai

Flex-Forcing: Towards a Unified Autoregressive and Bidirectional Video Diffusion Model

arXiv:2607.03509v1 Announce Type: new Abstract: Recent progress in large-scale generative models has substantially advanced video generation, yet existing methods remain constrained by a rigid inferen

safetyarxiv-cs-cv

FLOAT Drone for Physical Interaction: Lateral Airflow Reduction, Wrench Modeling, and Adaptive Control

arXiv:2607.04260v1 Announce Type: new Abstract: Aerial physical interaction represents a promising direction for next-generation unmanned aerial vehicles (UAVs), but it requires an aerial platform tha

safetyarxiv-cs-ro

FlowEval: Reference-Based Evaluation of Generated User Interfaces

researchapple-ml-research

While large language models (LLMs) and coding agents are often applied to user interface (UI) development, developers find it difficult to reliably assess their proficiency in visual and interaction d

Agents

FOI-O: An NZ-first ontology and verification methods package for Freedom of Information process modelling

arXiv:2607.02947v1 Announce Type: cross Abstract: Public official-information request records contain process signals. They can support research, workflow review, and human-supervised agent help. Yet

agentsarxiv-cs-cl

Folding, Reasoning, and Scaling with Open-source Drug Discovery Engine

arXiv:2607.03787v1 Announce Type: new Abstract: Accurately modeling biomolecular interactions is a central bottleneck in biology and therapeutic discovery. Here, we introduce Open Drug Discovery Engin

Foundations of Equivariant Deep Learning: Unifying Graph and Sheaf Neural Networks

arXiv:2607.03798v1 Announce Type: cross Abstract: Symmetry is everywhere in nature and society. Geometric deep learning exploits symmetries in data to improve the performance and efficiency of deep le

From General Actions to Domain-Specific Monitoring: Prior-Adaptive Transfer for Skeleton-Based Action Recognition

arXiv:2607.03327v1 Announce Type: new Abstract: Skeleton-based action recognition models have recently shown strong performance on large-scale benchmarks with general actions. However, directly transf

From Global to Local: Efficient Regional Weather Downscaling with Global Weather Foundation Model

arXiv:2607.03279v1 Announce Type: new Abstract: Accurate regional weather prediction requires resolving fine-scale structure while remaining consistent with global dynamics. Traditional limited area m

local-aiarxiv-cs-lg

From Judgments to Issues: Structured Extraction of Legal Reasoning with Citation-Hallucination Control

model-releasesarxiv-cs-ai

arXiv:2607.03325v1 Announce Type: cross Abstract: We present an automated pipeline that decomposes Italian tax-court judgments into individual legal issues and extracts, for each issue, a structured X

From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning

arXiv:2606.18089v2 Announce Type: replace Abstract: Post-training pipelines that combine supervised fine-tuning (SFT) with reinforcement learning (RL) have emerged as the key recipe for transforming l

local-aiarxiv-cs-lg

From Tensor Buffer to Distributed Memory Hierarchy: A Survey of KV Cache Management for LLM Serving

arXiv:2607.02574v1 Announce Type: cross Abstract: The key-value (KV) cache has become a first-order memory object in LLM serving rather than a temporary per-request tensor. This survey classifies more

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection

arXiv:2607.05176v1 Announce Type: new Abstract: Small object detection (SOD) remains a challenging task in real-world applications. Despite recent advances, existing detectors remain limited by rigid

applicationsarxiv-cs-cv

Full Glyph Images Beat Token Embeddings: A Controlled Study for Transformers

arXiv:2607.03994v1 Announce Type: cross Abstract: Modern language models generally represent text as sequences of discrete token embeddings, an assumption deeply rooted in current practice but rarely

Full-Stack FP4: Stable LLM Pretraining with Quantized Projections, Optimizers, and Attention

arXiv:2607.04422v1 Announce Type: cross Abstract: Recent NVFP4 pretraining methods mainly target transformer linear layers, leaving optimizer states, optimizer arithmetic and attention underexplored i

safetyarxiv-cs-ai

Fully Rotation-Equivariant Spectral-Spatial Learning for Multispectral Object Detection

arXiv:2607.05148v1 Announce Type: new Abstract: Existing multispectral detectors are limited by discrete spectral processing, a scale-dependent shift in the relative reliability of spectral and spatia

Function-Space Diffusion for Motion Planning

arXiv:2607.02977v1 Announce Type: new Abstract: Diffusion-based motion planners have demonstrated strong performance in generating diverse and high-quality robot trajectories in cluttered environments

researcharxiv-cs-ro

G^2TAM: Geometry Grounded Track Anything Model

arXiv:2607.03789v1 Announce Type: new Abstract: Human spatial understanding arises from jointly perceiving geometry and semantics, enabling consistent object identification and localization across vie

local-aiarxiv-cs-cv

G2VD: Generalizable AI-Generated Video Detection via Counterfactual Intervention and Causal Disentanglement

arXiv:2607.04607v1 Announce Type: cross Abstract: The rapid advancement of AI-generated videos poses increasing security risks and calls for robust detectors with strong cross-domain generalization. A

safetyarxiv-cs-ai

G3Splat: Geometrically Consistent Generalizable Gaussian Splatting

arXiv:2512.17547v2 Announce Type: replace Abstract: 3D Gaussians have become a powerful scene representation for real-time splatting and high-quality novel-view synthesis. This has motivated generaliz

Generative Pseudo-Labeling for Pre-Ranking with LLMs

arXiv:2602.20995v2 Announce Type: replace-cross Abstract: Pre-ranking is a critical stage in industrial recommendation systems, tasked with efficiently scoring thousands of recalled items for downstre

safetyarxiv-cs-cl

GeoFlow: Geo-Aware Modeling of Inter-Area Relationships in Origin-Destination Flow Prediction and Generation

arXiv:2607.05257v1 Announce Type: new Abstract: Origin-destination (OD) flow modeling underpins urban planning and mobility analysis, but prevailing graph-based methods often neglect salient geographi

researcharxiv-cs-lg

Geometric Causal Models

arXiv:2607.05153v1 Announce Type: cross Abstract: Scientists often seek to draw causal inferences from structured data that is not independently and identically distributed, such as spatial data, netw

applicationsarxiv-cs-lg

Geometric Reciprocity: Unlocking Self-Supervision for Stereoscopic Video Generation

arXiv:2607.05354v1 Announce Type: new Abstract: Monocular-to-stereo conversion synthesizes stereoscopic content from 2D videos for immersive 3D experiences. In modern Depth-Image-Based Rendering (DIBR

researcharxiv-cs-cv

Geometry-Aware Visual Odometry for Bronchoscopic Navigation via High-Gain Observer Fusion

arXiv:2607.05162v1 Announce Type: new Abstract: Navigational bronchoscopy is critical for pulmonary interventions, yet current platforms depend heavily on pre-operative CT or external sensors, limitin

researcharxiv-cs-ro