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FastOMOP: A Foundational Architecture for Reliable Agentic Real-World Evidence Generation on OMOP CDM data

arXiv:2604.24572v1 Announce Type: new Abstract: The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), maintained by the Observational Health Data Sciences and Informatics (OHDSI

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Human DGX agent

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FDIM: A Feature-distance-based Generic Video Quality Metric for Versatile Codecs

DGX agent

arXiv:2604.24123v1 Announce Type: new Abstract: Video technology is advancing toward Ultra High Definition (UHD) and High Dynamic Range (HDR), which intensifies the need for higher compression efficie

model-releasesarxiv-cs-cv

28 Apr 2026

Fed-DLoRA: Efficient Wireless Federated Learning with Dynamic Low-Rank Adaptation

arXiv:2604.24103v1 Announce Type: new Abstract: Federated learning (FL) offers a promising distributed learning paradigm for internet of vehicles (IoV) applications. However, it faces challenges from

Federated Cross-Modal Retrieval with Missing Modalities via Semantic Routing and Adapter Personalization

arXiv:2604.22885v1 Announce Type: cross Abstract: Federated cross-modal retrieval faces severe challenges from heterogeneous client data, particularly non-IID semantic distributions and missing modali

Applications

FedRef: Bayesian Fine-Tuning using a Reference Model to Mitigate Catastrophic Forgetting for Heterogeneous Federated Learning

arXiv:2506.23210v5 Announce Type: replace-cross Abstract: Federated learning (FL) enables collaborative model training across distributed clients while preserving data privacy. However, data and syste

applicationsarxiv-cs-ai

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection

arXiv:2604.24012v1 Announce Type: new Abstract: Federated learning enables a population of clients to collaboratively train machine learning models without exchanging their raw data, but standard algo

Few-Shot Cross-Device Transfer for Quantum Noise Modeling on Real Hardware

arXiv:2604.24397v1 Announce Type: cross Abstract: In the noisy intermediate-scale quantum (NISQ) regime, quantum devices contain hardware-specific noise sources which restrict device-invariant error m

Fine-R1: Make Multi-modal LLMs Excel in Fine-Grained Visual Recognition by Chain-of-Thought Reasoning

arXiv:2602.07605v3 Announce Type: replace-cross Abstract: Any entity in the visual world can be hierarchically grouped based on shared characteristics and mapped to fine-grained sub-categories. While

Tutorials

Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective

arXiv:2604.23267v1 Announce Type: new Abstract: Large language models (LLMs) operate in two fundamental learning modes - fine-tuning (FT) and in-context learning (ICL) - raising key questions about wh

tutorialsarxiv-cs-cl

FinGround: Detecting and Grounding Financial Hallucinations via Atomic Claim Verification

arXiv:2604.23588v1 Announce Type: new Abstract: Financial AI systems must produce answers grounded in specific regulatory filings, yet current LLMs fabricate metrics, invent citations, and miscalculat

Fix Initial Codes and Iteratively Refine Textual Directions Toward Safe Multi-Turn Code Correction

arXiv:2604.23989v1 Announce Type: cross Abstract: Recent work on large language models (LLMs) has emphasized the importance of scaling inference compute. From this perspective, the state-of-the-art me

Fixed-Reservoir vs Variational Quantum Architectures for Chaotic Dynamics: Benchmarking QRC and QPINN on the Lorenz System

arXiv:2604.23743v1 Announce Type: cross Abstract: Deploying quantum machine learning on NISQ devices requires architectures where training overhead does not negate computational advantages. We systema

FlashOverlap: Minimizing Tail Latency in Communication Overlap for Distributed LLM Training

arXiv:2604.24013v1 Announce Type: cross Abstract: The rapid growth in the size of large language models has necessitated the partitioning of computational workloads across accelerators such as GPUs, T

Flexible Deep Neural Networks for Partially Linear Survival Data: Estimation and Survival Inference

arXiv:2512.10570v2 Announce Type: replace-cross Abstract: We propose a flexible deep neural network (DNN) framework for modeling survival data within a partially linear regression structure. The appro

Flickering Multi-Armed Bandits

arXiv:2602.17315v2 Announce Type: replace-cross Abstract: We introduce Flickering Multi-Armed Bandits (FMAB) to model sequential decision-making in environments with changing action availability, wher

FlowPlace: Flow Matching for Chip Placement

arXiv:2604.23658v1 Announce Type: cross Abstract: Chip placement plays an important role in physical design. While generative models like diffusion models offer promising learning-based solutions, cur

FOCUS: Fused Observation of Channels for Unveiling Spectra

arXiv:2507.14787v2 Announce Type: replace-cross Abstract: Hyperspectral imaging (HSI) captures hundreds of narrow, contiguous wavelength bands, making it a powerful tool in biology, agriculture, and e

Focus on What Matters: Two-Stage ROI-Aware Refinement for Anatomy-Preserving Fetal Ultrasound Reconstruction

arXiv:2604.23839v1 Announce Type: cross Abstract: Measurement-critical ultrasound tasks often depend on a small anatomical region, making global reconstruction metrics an unreliable proxy for clinical

Follow the TRACE: Exploiting Post-Click Trajectories for Online Delayed Conversion Rate Prediction

arXiv:2604.23197v1 Announce Type: new Abstract: Delayed feedback poses a core challenge for online CVR prediction, forcing a trade-off between label accuracy and data freshness. Existing methods addre

Food4All: A Multi-Agent Framework for Real-time Free Food Discovery with Integrated Nutritional Metadata

arXiv:2510.18289v2 Announce Type: replace Abstract: Food insecurity remains a persistent public health emergency in the United States, tightly interwoven with chronic disease, mental illness, and opio

agentsarxiv-cs-cl

For-Value: Efficient Forward-Only Data Valuation for finetuning LLMs and VLMs

model-releasesarxiv-cs-cl

arXiv:2508.10180v3 Announce Type: replace Abstract: Data valuation is essential for enhancing the transparency and accountability of large language models (LLMs) and vision-language models (VLMs). How

Forecasting Commencing Enrolments Under Data Sparsity: A Zero-Shot Time Series Foundation Models Framework for Higher Education Planning

arXiv:2602.12120v3 Announce Type: replace Abstract: Effective resource allocation in higher education depends on reliable enrolment forecasts, yet institutional planners frequently face data series di

FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in Lean

arXiv:2604.23002v1 Announce Type: new Abstract: Formalising informal mathematical reasoning into formally verifiable code is a significant challenge for large language models. In scientific fields suc

Franca: Nested Matryoshka Clustering for Scalable Visual Representation Learning

model-releasesarxiv-cs-cv

arXiv:2507.14137v4 Announce Type: replace Abstract: We present Franca (pronounced Fran-ka): free one; the first fully open-source (data, code, weights) vision foundation model that matches and in many

Applications

Fraud Detection in Cryptocurrency Markets with Spatio-Temporal Graph Neural Networks

arXiv:2604.24590v1 Announce Type: new Abstract: Technological advancements in cryptocurrency markets have increased accessibility for investors, but concurrently exposed them to the risks of market ma

applicationsarxiv-cs-lg

Hardware

FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost

arXiv:2604.24073v1 Announce Type: cross Abstract: Modern industrial Deep Learning Recommendation Models typically extract user preferences through the analysis of sequential interaction histories, sub

hardwarearxiv-cs-ai

FreqCache: Accelerating Embodied VLN Models with Adaptive Frequency-Guided Token Caching

arXiv:2604.24391v1 Announce Type: new Abstract: Vision-Language-Navigation (VLN) models exhibit excellent navigation accuracy but incur high computational overhead. Token caching has emerged as a prom

researcharxiv-cs-ro

FreqFormer: Hierarchical Frequency-Domain Attention with Adaptive Spectral Routing for Long-Sequence Video Diffusion Transformers

arXiv:2604.22808v1 Announce Type: cross Abstract: Long-sequence video diffusion transformers hit a quadratic self-attention cost that dominates runtime and memory for very long token sequences. Most e

Tutorials

From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents

arXiv:2604.23194v1 Announce Type: new Abstract: Large language model-based agents have recently emerged as powerful approaches for solving dynamic and multi-step tasks. Most existing agents employ pla

tutorialsarxiv-cs-ai

From Edges to Depth: Probing the Spatial Hierarchy in Vision Transformers

arXiv:2604.23452v1 Announce Type: new Abstract: Vision Transformers trained only on image classification routinely transfer to tasks that demand spatial understanding, yet they receive no spatial supe

Applications

From Equations to Algorithms and Data: Transforming Microwave Engineering and Education with Machine Learning

arXiv:2604.22792v1 Announce Type: cross Abstract: Conventional microwave engineering education relies heavily on analytical methods, canonical circuit topologies, and intuition-driven design, which ha

applicationsarxiv-cs-lg

From Noisy Historical Maps to Time-Series Oil Palm Mapping Without Annotation in Malaysia and Indonesia (2020-2024)

arXiv:2604.23776v1 Announce Type: cross Abstract: Accurate monitoring of oil palm plantations is critical for balancing economic development with environmental conservation in Southeast Asia. However,

From Optimization to Prediction: Transformer-Based Path-Flow Estimation to the Traffic Assignment Problem

arXiv:2510.19889v2 Announce Type: replace-cross Abstract: The traffic assignment problem is essential for traffic flow analysis, traditionally solved using mathematical programs under the Equilibrium

From Pixels to Explanations: Interpretable Diabetic Retinopathy Grading with CNN-Transformer Ensembles, Visual Explainability and Vision-Language Models

arXiv:2604.23079v1 Announce Type: cross Abstract: The quality of diabetic retinopathy (DR) screening relies on the ability to correctly grade severity; however, many deep-learning (DL) classifiers can

From Rights to Rites: Expectations Management in Smart-Home AI

arXiv:2604.23635v1 Announce Type: cross Abstract: Domestic voice assistants and smart-home devices are increasingly embedded in everyday routines, yet their ethics are often treated as an afterthought

From Similarity to Structure: Training-free LLM Context Compression with Hybrid Graph Priors

arXiv:2604.23277v1 Announce Type: cross Abstract: Long-context large language models remain computationally expensive to run and often fail to reliably process very long inputs, which makes context co

From Skeletons to Pixels: Few-Shot Precise Event Spotting via Representation and Prediction Distillation

arXiv:2604.22839v1 Announce Type: cross Abstract: Precise Event Spotting (PES) is essential in fast-paced sports such as tennis, where fine-grained events occur within very short temporal windows. Acc

From Skill Text to Skill Structure: The Scheduling-Structural-Logical Representation for Agent Skills

arXiv:2604.24026v1 Announce Type: cross Abstract: LLM agents increasingly rely on reusable skills, capability packages that combine instructions, control flow, constraints, and tool calls. In most cur

From Stateless Queries to Autonomous Actions: A Layered Security Framework for Agentic AI Systems

arXiv:2604.23338v1 Announce Type: cross Abstract: Agentic AI systems face security challenges that stateless large language models do not. They plan across extended horizons, maintain persistent memor

safetyarxiv-cs-lg

From Static to Interactive: Authoring Interactive Visualizations via Natural Language

arXiv:2601.17736v2 Announce Type: replace-cross Abstract: Interactivity is crucial for effective data visualizations. However, it is often challenging to implement interactions for existing static vis

FunRec: Reconstructing Functional 3D Scenes from Egocentric Interaction Videos

arXiv:2604.05621v2 Announce Type: replace Abstract: We present FunRec, a method for reconstructing functional 3D digital twins of indoor scenes directly from egocentric RGB-D interaction videos. Unlik

FUSER: Feed-Forward MUltiview 3D Registration Transformer and SE(3)^N Diffusion Refinement

arXiv:2512.09373v2 Announce Type: replace Abstract: Registration of multiview point clouds conventionally relies on extensive pairwise matching to build a pose graph for global synchronization, which

GA2-CLIP: Generic Attribute Anchor for Efficient Prompt Tuningin Video-Language Models

arXiv:2511.22125v2 Announce Type: replace Abstract: Visual and textual soft prompt tuning can effectively improve the adaptability of Vision-Language Models (VLMs) in downstream tasks. However, fine-t

Game-Time: Evaluating Temporal Dynamics in Spoken Language Models

arXiv:2509.26388v3 Announce Type: replace-cross Abstract: Conversational Spoken Language Models (SLMs) are emerging as a promising paradigm for real-time speech interaction. However, their capacity of

GAMED.AI: A Hierarchical Multi-Agent Framework for Automated Educational Game Generation

arXiv:2604.23947v1 Announce Type: new Abstract: We introduce GameDAI, a hierarchical multi-agent framework that transforms instructor-provided questions into fully playable, pedagogically grounded edu

GAMMAF: A Common Framework for Graph-Based Anomaly Monitoring Benchmarking in LLM Multi-Agent Systems

arXiv:2604.24477v1 Announce Type: cross Abstract: The rapid integration of Large Language Models (LLMs) into Multi-Agent Systems (MAS) has significantly enhanced their collaborative problem-solving ca

Gated Tree Cross-Attention for Checkpoint-Compatible Syntax Injection in Decoder-Only LLMs

arXiv:2602.15846v2 Announce Type: replace Abstract: Decoder-only large language models achieve strong broad performance but are brittle to minor grammatical perturbations, undermining reliability for

researcharxiv-cs-cl

GCP: Guarded Collaborative Perception with Spatial-Temporal Aware Malicious Agent Detection

model-releasesarxiv-cs-cv

arXiv:2501.02450v2 Announce Type: replace Abstract: Collaborative perception significantly enhances autonomous driving safety by extending each vehicle's perception range through message sharing among