Search: “framework”

From Attribution to Abstention: Training-Free Attention-Based Auditing for Clinical Summarization

arXiv:2601.16397v2 Announce Type: replace Abstract: Deploying multimodal large language models (MLLMs) for clinical summarization demands not only fluent generation but also transparency about where e

researcharxiv-cs-cl

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From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration

DGX agent

arXiv:2604.16462v1 Announce Type: new Abstract: High-resolution Multimodal Large Language Models (MLLMs) face prohibitive computational costs during inference due to the explosion of visual tokens. Ex

model-releasesarxiv-cs-cv

21 Apr 2026

Tutorials

Generalizable Radio-Frequency Radiance Fields for Spatial Spectrum Synthesis

arXiv:2502.05708v3 Announce Type: replace-cross Abstract: We present GRaF, Generalizable Radio-Frequency (RF) Radiance Fields, a framework that models RF signal propagation to synthesize spatial spect

tutorialsarxiv-cs-lg

GoCoMA: Hyperbolic Multimodal Representation Fusion for Large Language Model-Generated Code Attribution

arXiv:2604.16377v1 Announce Type: new Abstract: Large Language Models (LLMs) trained on massive code corpora are now increasingly capable of generating code that is hard to distinguish from human-writ

researcharxiv-cs-cl

GS-STVSR: Ultra-Efficient Continuous Spatio-Temporal Video Super-Resolution via 2D Gaussian Splatting

arXiv:2604.18047v1 Announce Type: new Abstract: Continuous Spatio-Temporal Video Super-Resolution (C-STVSR) aims to simultaneously enhance the spatial resolution and frame rate of videos by arbitrary

safetyarxiv-cs-cv

Applications

Hybrid Quantum Neural Networks for Enhanced Breast Cancer Thermographic Classification: A Novel Quantum-Classical Integration Approach

arXiv:2604.16953v1 Announce Type: cross Abstract: Breast cancer diagnosis through thermographic image analysis remains a critical challenge in medical AI, with classical deep learning approaches facin

applicationsarxiv-cs-cv

Instant Colorization of Gaussian Splats

arXiv:2604.17155v1 Announce Type: new Abstract: Gaussian Splatting has recently become one of the most popular frameworks for photorealistic 3D scene reconstruction and rendering. While current raster

KaLDeX: Kalman Filter based Linear Deformable Cross Attention for Retina Vessel Segmentation

arXiv:2410.21160v2 Announce Type: replace-cross Abstract: Background and Objective: In the realm of ophthalmic imaging, accurate vascular segmentation is paramount for diagnosing and managing various

Learning-Based Sparsification of Dynamic Graphs in Robotic Exploration Algorithms

arXiv:2604.16509v1 Announce Type: cross Abstract: Many robotic exploration algorithms rely on graph structures for frontier-based exploration and dynamic path planning. However, these graphs grow rapi

safetyarxiv-cs-lg

Learning residue level protein dynamics with multiscale Gaussians

arXiv:2509.01038v2 Announce Type: replace-cross Abstract: Many methods have been developed to predict static protein structures, however understanding the dynamics of protein structure is essential fo

Learning to Trade Like an Expert: Cognitive Fine-Tuning for Stable Financial Reasoning in Language Models

arXiv:2604.16862v1 Announce Type: new Abstract: Recent deployments of large language models (LLMs) as autonomous trading agents raise questions about whether financial decision-making competence gener

agentsarxiv-cs-lg

Leveraging Kernel Symmetry for Joint Compression and Error Mitigation in Edge Model Transfer

arXiv:2604.17371v1 Announce Type: cross Abstract: This paper investigates communication-efficient neural network transmission by exploiting structured symmetry constraints in convolutional kernels. In

LexRel: Benchmarking Legal Relation Extraction for Chinese Civil Cases

model-releasesarxiv-cs-cl

arXiv:2512.12643v2 Announce Type: replace Abstract: Legal relations serve as an important analytical framework for dispute resolution in civil cases. However, legal relations in Chinese civil cases re

Motion-Guided Semantic Alignment with Negative Prompts for Zero-Shot Video Action Recognition

arXiv:2604.17062v1 Announce Type: new Abstract: Zero-shot action recognition is challenging due to the semantic gap between seen and unseen classes. We present a novel framework that enhances CLIP wit

safetyarxiv-cs-cv

Multi-Label Phase Diagram Prediction in Complex Alloys via Physics-Informed Graph Attention Networks

arXiv:2604.16468v1 Announce Type: new Abstract: Accurate phase equilibria are foundational to alloy design because they encode the underlying thermodynamics governing stability, transformations, and p

Multi-View Hierarchical Graph Neural Network for Sketch-Based 3D Shape Retrieval

arXiv:2604.18019v1 Announce Type: new Abstract: Sketch-based 3D shape retrieval (SBSR) aims to retrieve 3D shapes that are consistent with the category of the input hand-drawn sketch. The core challen

Multimodal Fusion of Histopathology Images and Electronic Health Records for Early Breast Cancer Diagnosis

arXiv:2604.17122v1 Announce Type: new Abstract: Breast cancer is a leading cause of cancer-related mortality worldwide, and timely accurate diagnosis is critical to improving survival outcomes. While

MultiWorld: Scalable Multi-Agent Multi-View Video World Models

arXiv:2604.18564v1 Announce Type: new Abstract: Video world models have achieved remarkable success in simulating environmental dynamics in response to actions by users or agents. They are modeled as

agentsarxiv-cs-cv

NCO4CVRP: Neural Combinatorial Optimization for the Capacitated Vehicle Routing Problem

arXiv:2604.16581v1 Announce Type: new Abstract: Neural Combinatorial Optimization (NCO) has emerged as a powerful framework for solving combinatorial optimization problems by integrating deep learning

local-aiarxiv-cs-lg

OASIS: On-Demand Hierarchical Event Memory for Streaming Video Reasoning

arXiv:2604.17052v1 Announce Type: new Abstract: Streaming video reasoning requires models to operate in a setting where history grows without bound while meaningful evidence remains scarce. In such a

Oblivion: Self-Adaptive Agentic Memory Control through Decay-Driven Activation

arXiv:2604.00131v2 Announce Type: replace Abstract: Human memory adapts through selective forgetting: experiences become less accessible over time but can be reactivated by reinforcement or contextual

agentsarxiv-cs-cl

Tutorials

OC-Distill: Ontology-aware Contrastive Learning with Cross-Modal Distillation for ICU Risk Prediction

arXiv:2604.16878v1 Announce Type: new Abstract: Early prediction of severe clinical deterioration and remaining length of stay can enable timely intervention and better resource allocation in high-acu

tutorialsarxiv-cs-lg

OmniVLA-RL: A Vision-Language-Action Model with Spatial Understanding and Online RL

arXiv:2604.17706v1 Announce Type: new Abstract: Visual-Language-Action (VLA) models represent a paradigm shift in embodied AI, yet existing frameworks often struggle with imprecise spatial perception,

safetyarxiv-cs-ro

Tutorials

Optimally Bridging Semantics and Data: Generative Semantic Communication via Schrodinger Bridge

arXiv:2604.17802v1 Announce Type: cross Abstract: Generative Semantic Communication (GSC) is a promising solution for image transmission over narrow-band and high-noise channels. However, existing GSC

tutorialsarxiv-cs-cv

Penny Wise, Pixel Foolish: Bypassing Price Constraints in Multimodal Agents via Visual Adversarial Perturbations

model-releasesarxiv-cs-cv

arXiv:2604.16515v1 Announce Type: new Abstract: The rapid proliferation of Multimodal Large Language Models (MLLMs) has enabled mobile agents to execute high-stakes financial transactions, but their a

PoliLegalLM: A Technical Report on a Large Language Model for Political and Legal Affairs

arXiv:2604.17543v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success in general-domain tasks, yet their direct application to the legal domain remains challeng

safetyarxiv-cs-cl

PPEDCRF: Dynamic-CRF-Guided Selective Perturbation for Background-Based Location Privacy in Video Sequences

model-releasesarxiv-cs-cv

arXiv:2604.17163v1 Announce Type: new Abstract: We propose PPEDCRF, a calibrated selective perturbation framework that protects background-based location privacy in released video frames against galle

Privacy-R1: Privacy-Aware Multi-LLM Agent Collaboration via Reinforcement Learning

arXiv:2510.16054v2 Announce Type: replace-cross Abstract: When users submit queries to Large Language Models (LLMs), their prompts can often contain sensitive data, forcing a difficult choice: Send th

local-aiarxiv-cs-cl

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction

arXiv:2506.01770v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved tremendous success in various tasks, yet concerns about their safety and security have emerged. In

safetyarxiv-cs-lg

SafeLM: Unified Privacy-Aware Optimization for Trustworthy Federated Large Language Models

arXiv:2604.16606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains, yet a unified treatment of their overlapping safety challenges remains

safetyarxiv-cs-lg

Safer Trajectory Planning with CBF-guided Diffusion Model for Unmanned Aerial Vehicles

arXiv:2604.17527v1 Announce Type: new Abstract: Safe and agile trajectory planning is essential for autonomous systems, especially during complex aerobatic maneuvers. Motivated by the recent success o

safetyarxiv-cs-ro

Safety, Security, and Cognitive Risks in State-Space Models: A Systematic Threat Analysis with Spectral, Stateful, and Capacity Attacks

arXiv:2604.16424v1 Announce Type: cross Abstract: State-Space Models (SSMs) -- structured SSMs (S4, S4D, DSS, S5), selective SSMs (Mamba, Mamba-2), and hybrid architectures (Jamba) -- are deployed in

safetyarxiv-cs-cl

Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration

model-releasesarxiv-cs-cl

arXiv:2505.21471v2 Announce Type: replace Abstract: With the rapid advancement of post-training techniques for reasoning and information seeking, large language models (LLMs) can incorporate a large q

SemMorph3D: Unsupervised Semantic-Aware 3D Morphing via Mesh-Guided Gaussians

model-releasesarxiv-cs-cv

arXiv:2510.02034v2 Announce Type: replace Abstract: We introduce METHODNAME, a novel framework for semantic-aware 3D shape and texture morphing directly from multi-view images. While 3D Gaussian Splat

Sensorimotor Self-Recognition in Multimodal Large Language Model-Driven Robots

arXiv:2505.19237v2 Announce Type: replace-cross Abstract: Self-recognition -- the ability to maintain an internal representation of one's own body within the environment -- underpins intelligent, auto

agentsarxiv-cs-ro

SentiAvatar: Towards Expressive and Interactive Digital Humans

arXiv:2604.02908v2 Announce Type: replace Abstract: We present SentiAvatar, a framework for building expressive interactive 3D digital humans, and use it to create SuSu, a virtual character that speak

StableMTL: Repurposing Latent Diffusion Models for Multi-Task Learning from Partially Annotated Synthetic Datasets

arXiv:2506.08013v2 Announce Type: replace Abstract: Multi-task learning for dense prediction is limited by the need for extensive annotation for every task, though recent works have explored training

Stochastic Control Methods for Optimization

model-releasesarxiv-cs-lg

arXiv:2601.01248v4 Announce Type: replace-cross Abstract: In this work, we investigate a stochastic control framework for global optimization over both Euclidean spaces and the Wasserstein space of pr

Structure-Adaptive Sparse Diffusion in Voxel Space for 3D Medical Image Enhancement

arXiv:2604.17773v1 Announce Type: new Abstract: Three-dimensional (3D) medical image enhancement, including denoising and super-resolution, is critical for clinical diagnosis in CT, PET, and MRI. Alth

The Global Neural World Model: Spatially Grounded Discrete Topologies for Action-Conditioned Planning

arXiv:2604.16585v1 Announce Type: new Abstract: We present the Global Neural World Model (GNWM), a self-stabilizing framework that achieves topological quantization through balanced continuous entropy

agentsarxiv-cs-lg

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

arXiv:2509.02547v5 Announce Type: replace-cross Abstract: The emergence of agentic reinforcement learning (Agentic RL) marks a paradigm shift from conventional reinforcement learning applied to large

agentsarxiv-cs-cl

Applications

Towards Intelligent Legal Document Analysis: CNN-Driven Classification of Case Law Texts

arXiv:2604.17674v1 Announce Type: new Abstract: Legal practitioners and judicial institutions face an ever-growing volume of case-law documents characterised by formalised language, lengthy sentence s

applicationsarxiv-cs-cl

TrianguLang: Geometry-Aware Semantic Consensus for Pose-Free 3D Localization

arXiv:2603.08096v3 Announce Type: replace Abstract: Localizing objects and parts from natural language in 3D space is essential for robotics, AR, and embodied AI, yet existing methods face a trade-off

Universal Diffusion-Based Probabilistic Downscaling

arXiv:2602.11893v3 Announce Type: replace Abstract: We introduce a universal diffusion-based downscaling framework that lifts deterministic low-resolution weather forecasts into probabilistic high-res

VC-Inspector: Advancing Reference-free Evaluation of Video Captions with Factual Analysis

arXiv:2509.16538v3 Announce Type: replace-cross Abstract: We propose VC-Inspector, a lightweight, open-source large multimodal model (LMM) for reference-free evaluation of video captions, with a focus

researcharxiv-cs-cl

VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models

arXiv:2508.15229v3 Announce Type: replace Abstract: Small Language Models (SLMs) provide computational advantages in resource-constrained environments, yet memory limitations remain a critical bottlen

local-aiarxiv-cs-cl

Adapting in the Dark: Efficient and Stable Test-Time Adaptation for Black-Box Models

arXiv:2604.15609v1 Announce Type: cross Abstract: Test-Time Adaptation (TTA) for black-box models accessible only via APIs remains a largely unexplored challenge. Existing approaches such as post-hoc

20 Apr 2026

Adaptive Spatio-temporal Estimation on the Graph Edges via Line Graph Transformation

arXiv:2311.00656v4 Announce Type: replace-cross Abstract: Spatial-temporal estimation of signals on graph edges is challenging because most conventional Graph Signal Processing techniques are defined