Search: “framework”

AsyncShield: A Plug-and-Play Edge Adapter for Asynchronous Cloud-based VLA Navigation

arXiv:2604.24086v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models have been demonstrated possessing strong zero-shot generalization for robot control, their massive parameter

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Research

B-FIRE: Binning-Free Diffusion Implicit Neural Representation for Hyper-Accelerated Motion-Resolved MRI

DGX agent

arXiv:2601.06166v2 Announce Type: replace Abstract: Accelerated dynamic volumetric magnetic resonance imaging (4DMRI) is essential for applications relying on motion resolution. Existing 4DMRI produce

researcharxiv-cs-cv

28 Apr 2026

Tutorials

Beyond Static: Related Questions Retrieval Through Conversations in Community Question Answering

arXiv:2604.22759v1 Announce Type: cross Abstract: In community question answering (cQA) platforms like Stack Overflow, related question retrieval is recognized as a fundamental task that allows users

tutorialsarxiv-cs-ai

BIMStruct3D: A Fully Automated Hybrid Learning Scan-to-BIM Pipeline with Integrated Topology Refinement

arXiv:2604.24311v1 Announce Type: new Abstract: Automatic generation of Building Information Models (BIM) from building scans is a key challenge in architecture and construction. We present a modular

BitRL: Reinforcement Learning with 1-bit Quantized Language Models for Resource-Constrained Edge Deployment

model-releasesarxiv-cs-lg

arXiv:2604.24273v1 Announce Type: new Abstract: The deployment of intelligent reinforcement learning (RL) agents on resource-constrained edge devices remains a fundamental challenge due to the substan

Agents

BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks

arXiv:2508.08127v2 Announce Type: replace Abstract: The security of LLM-based multi-agent systems (MAS) is critically threatened by propagation vulnerability, where malicious agents can distort collec

agentsarxiv-cs-ai

Applications

Bridging the Domain Divide: Supervised vs. Zero-Shot Clinical Section Segmentation from MIMIC-III to Obstetrics

arXiv:2602.17513v2 Announce Type: replace Abstract: Clinical free-text notes contain vital patient information. They are structured into labelled sections; recognizing these sections has been shown to

applicationsarxiv-cs-cl

BRIEF-Pro: Universal Context Compression with Short-to-Long Synthesis for Fast and Accurate Multi-Hop Reasoning

arXiv:2510.13799v2 Announce Type: replace Abstract: As retrieval-augmented generation (RAG) tackles complex tasks, increasingly expanded contexts offer richer information, but at the cost of higher la

researcharxiv-cs-cl

BVI-Mamba: Video Enhancement Using a Visual State-Space Model for Low-Light and Underwater Environments

arXiv:2604.23655v1 Announce Type: new Abstract: Videos captured in low-light and underwater conditions often suffer from distortions such as noise, low contrast, color imbalance, and blur. These issue

safetyarxiv-cs-cv

Agents

Case-Specific Rubrics for Clinical AI Evaluation: Methodology, Validation, and LLM-Clinician Agreement Across 823 Encounters

arXiv:2604.24710v1 Announce Type: new Abstract: Objective. Clinical AI documentation systems require evaluation methodologies that are clinically valid, economically viable, and sensitive to iterative

agentsarxiv-cs-ai

Certified geometric robustness -- Super-DeepG

arXiv:2604.24379v1 Announce Type: new Abstract: Safety-critical applications are required to perform as expected in normal operations. Image processing functions are often required to be insensitive t

safetyarxiv-cs-ai

Characterizations of Admissible Objective Functions for Hierarchical Clustering

arXiv:2604.23628v1 Announce Type: cross Abstract: Hierarchical clustering is a fundamental task in data analysis, yet for a long time it lacked a principled objective function. Dasgupta [STOC 2016] in

CiteAudit: You Cited It, But Did You Read It? A Benchmark for Verifying Scientific References in the LLM Era

model-releasesarxiv-cs-cl

arXiv:2602.23452v2 Announce Type: replace Abstract: Scientific research relies on accurate citation for attribution and integrity, yet large language models (LLMs) introduce a new risk: fabricated ref

CLIP-Guided Data Augmentation for Night-Time Image Dehazing

arXiv:2604.05500v2 Announce Type: replace Abstract: Nighttime image dehazing faces a more complex degradation pattern than its daytime counterpart, as haze scattering couples with low illumination, no

Local Ai

Code Broker: A Multi-Agent System for Automated Code Quality Assessment

arXiv:2604.23088v1 Announce Type: cross Abstract: We present Code Broker, a multi agent system built with Google Agent Development Kit ADK that analyses Python code from files, local directories, or G

local-aiarxiv-cs-ai

Agents

Collaborative Trajectory Prediction via Late Fusion

arXiv:2604.22973v1 Announce Type: new Abstract: Predicting future trajectories of surrounding traffic agents is critical for safe autonomous navigation and collision avoidance. Despite all advances in

agentsarxiv-cs-ro

Computational Design and Experimental Validation of Photoactive PARP1 Inhibitors

arXiv:2604.24634v1 Announce Type: cross Abstract: Light-activated drugs are a promising way to treat localized diseases for which existing treatments have severe side effects. However, their developme

Cooptimizing Safety and Performance Using Safety Value-Constrained Model Predictive Control

arXiv:2604.23863v1 Announce Type: new Abstract: Autonomous systems are increasingly deployed in real-world environments, where they must achieve high performance while maintaining safety under state a

safetyarxiv-cs-ro

CoreGuard: Safeguarding Foundational Capabilities of LLMs Against Model Stealing in Edge Deployment

arXiv:2410.13903v3 Announce Type: replace-cross Abstract: Proprietary large language models (LLMs) exhibit strong generalization capabilities across diverse tasks and are increasingly deployed on edge

Designing Robots to Support Parent-Child Connections: Opportunities Through Robot-Mediated Communication

arXiv:2604.23976v1 Announce Type: new Abstract: The sense of family connectedness may support positive outcomes including individual well-being, resilience, and healthy family functioning. However, as

researcharxiv-cs-ro

Diffusion Model as a Generalist Segmentation Learner

arXiv:2604.24575v1 Announce Type: new Abstract: Diffusion models are primarily trained for image synthesis, yet their denoising trajectories encode rich, spatially aligned visual priors. In this paper

Discriminator-Guided Adaptive Diffusion for Source-Free Test-Time Adaptation under Image Corruptions

arXiv:2604.23636v1 Announce Type: new Abstract: In this work, we study Source-Free Unsupervised Domain Adaptation under corruption-induced domain shifts, where performance degradation is caused by nat

Efficient Image Annotation via Semi-Supervised Object Segmentation with Label Propagation

arXiv:2604.22992v1 Announce Type: new Abstract: Reliable object perception is necessary for general-purpose service robots. Open-vocabulary detectors struggle to generalize beyond a few classes and fu

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce

arXiv:2604.23993v1 Announce Type: cross Abstract: Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel vi

Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach

model-releasesarxiv-cs-lg

arXiv:2601.18399v2 Announce Type: replace Abstract: Separating liquid-liquid dispersions in gravity settlers is critical in chemical, pharmaceutical, and recycling processes. The dense-packed zone hei

Event-based SLAM Benchmark for High-Speed Maneuvers

model-releasesarxiv-cs-ro

arXiv:2604.24033v1 Announce Type: new Abstract: Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution,

EX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment

model-releasesarxiv-cs-cv

arXiv:2604.22842v1 Announce Type: new Abstract: Face Image Quality Assessment is crucial for reliable face recognition systems, yet existing Vision Transformer-based approaches rely exclusively on fin

EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain

model-releasesarxiv-cs-cl

arXiv:2406.14075v2 Announce Type: replace Abstract: It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, financ

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

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

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 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

safetyarxiv-cs-ai

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

Generative Synthetic Data for Causal Inference: Pitfalls, Remedies, and Opportunities

arXiv:2604.23904v1 Announce Type: cross Abstract: Synthetic data offers a promising tool for privacy-preserving data release, augmentation, and simulation, but its use in causal inference requires pre

Global Context or Local Detail? Adaptive Visual Grounding for Hallucination Mitigation

arXiv:2604.24396v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are frequently undermined by object hallucination--generating content that contradicts visual reality--due to an over-re

Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference

arXiv:2503.10666v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become widely used across various domains spanning search engines, code generation, and text creation. Howev

Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer

arXiv:2604.24062v1 Announce Type: new Abstract: Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and

GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs

arXiv:2604.23366v1 Announce Type: new Abstract: Autonomous multi-agent LLM systems are increasingly deployed to investigate operational incidents and produce structured diagnostic reports. Their trust

HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization

arXiv:2511.08425v3 Announce Type: replace Abstract: Diffusion and flow-matching have emerged as powerful methodologies for generative modeling, with remarkable success in capturing complex data distri

Hierarchical Prototype-based Domain Priors for Multiple Instance Learning in Multimodal Histopathology Analysis

arXiv:2604.23982v1 Announce Type: new Abstract: Digital pathology has fundamentally altered diagnostic workflows by enabling the computational analysis of gigapixel Whole Slide Images (WSIs), yet effe

safetyarxiv-cs-cv

Hierarchical Spatio-Channel Clustering for Efficient Model Compression in Medical Image Analysis

model-releasesarxiv-cs-cv

arXiv:2604.23375v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) have become increasingly difficult to deploy in resource-constrained environments due to their large memory and com

Hybrid JIT-CUDA Graph Optimization for Low-Latency Large Language Model Inference

arXiv:2604.23467v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved strong performance across natural language and multimodal tasks, yet their practical deployment remains con

Implicit Humanization in Everyday LLM Moral Judgments

arXiv:2604.22764v1 Announce Type: cross Abstract: Recent adoption of conversational information systems has expanded the scope of user queries to include complex tasks such as personal advice-seeking.

INHerit-SG: Incremental Hierarchical Semantic Scene Graphs with RAG-Style Retrieval

model-releasesarxiv-cs-ro

arXiv:2602.12971v2 Announce Type: replace Abstract: Driven by recent advancements in foundation models, semantic scene graphs have emerged as a promising paradigm for high-level 3D environmental abstr

Tutorials

Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models

arXiv:2509.20237v2 Announce Type: replace Abstract: Backchannels and fillers are important linguistic expressions in dialogue, but often treated as 'noise' to be bypassed in modern transformer-based l

tutorialsarxiv-cs-cl

KERV: Kinematic-Rectified Speculative Decoding for Embodied VLA Models

arXiv:2603.01581v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models build a token-domain robot control paradigm, yet suffer from low speed. Speculative Decoding (SD) is an op

Hardware

Latent Inter-Frame Pruning: A Training-Free Method Bridging Traditional Video Compression and Modern Diffusion Transformers for Efficient Generation

arXiv:2604.23858v1 Announce Type: new Abstract: Video generation, while capable of generating realistic videos, is computationally expensive and slow, prohibiting real-time applications. In this paper

hardwarearxiv-cs-cv

Leveraging Human Feedback for Semantically-Relevant Skill Discovery

arXiv:2604.24127v1 Announce Type: cross Abstract: Unsupervised skill discovery in reinforcement learning aims to intrinsically motivate agents to discover diverse and useful behaviours. However, uncon