Search: “models”

Geodesic Semantic Search: Cartographic Navigation of Citation Graphs with Learned Local Riemannian Maps

arXiv:2602.23665v3 Announce Type: replace-cross Abstract: We present Geodesic Semantic Search (GSS), a retrieval system that learns node-specific Riemannian metrics on citation graphs to enable geomet

local-aiarxiv-cs-lg

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Geometric and Quantum Kernel Methods for Predicting Skeletal Muscle Outcomes in chronic obstructive pulmonary disease

DGX agent

arXiv:2601.00921v2 Announce Type: replace Abstract: Quantum methods are increasingly proposed for healthcare, but translational biomarker studies demand transparent benchmarking and robust small-datas

applicationsarxiv-cs-lg

21 Apr 2026

GRAIL: Autonomous Concept Grounding for Neuro-Symbolic Reinforcement Learning

arXiv:2604.16871v1 Announce Type: cross Abstract: Neuro-symbolic Reinforcement Learning (NeSy-RL) combines symbolic reasoning with gradient-based optimization to achieve interpretable and generalizabl

agentsarxiv-cs-lg

Greedy Kalman-Swarm: Improving State Estimation in Robot Swarms in Harsh Environments

arXiv:2604.16868v1 Announce Type: new Abstract: State estimation is a fundamental requirement in robotics, where the accurate determination of a robot's state is essential for stable operation despite

agentsarxiv-cs-ro

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

HABIT: Chrono-Synergia Robust Progressive Learning Framework for Composed Image Retrieval

arXiv:2604.18037v1 Announce Type: new Abstract: Composed Image Retrieval (CIR) is a flexible image retrieval paradigm that enables users to accurately locate the target image through a multimodal quer

Hyperbolic Enhanced Representation Learning for Incomplete Multi-view Clustering

arXiv:2604.16959v1 Announce Type: cross Abstract: Incomplete Multi-View Clustering (IMVC) faces the challenge of learning discriminative representations from fragmentary observations while maintaining

ICLAD: In-Context Learning with Comparison-Guidance for Audio Deepfake Detection

arXiv:2604.16749v1 Announce Type: cross Abstract: Audio deepfakes pose a significant security threat, yet current state-of-the-art (SOTA) detection systems do not generalize well to realistic in-the-w

Improving reproducibility by controlling random seed stability in machine learning based estimation via bagging

arXiv:2604.17694v1 Announce Type: cross Abstract: Predictions from machine learning algorithms can vary across random seeds, inducing instability in downstream debiased machine learning estimators. We

Improving Speech Recognition of Named Entities in Classroom Speech with LLM Revision and Phonetic-Semantic Context

arXiv:2506.10779v2 Announce Type: replace Abstract: Classroom speech and lectures often contain named entities (NEs) such as names of people and special terminology. While automatic speech recognition

Integrating Feature Selection and Machine Learning for Nitrogen Assessment in Grapevine Leaves using In-Field Hyperspectral Imaging

arXiv:2507.17869v3 Announce Type: replace-cross Abstract: Nitrogen (N) is one of the most critical nutrients in winegrape production, influencing vine vigor, fruit composition, and wine quality. Becau

applicationsarxiv-cs-cv

Is Agentic RAG worth it? An experimental comparison of RAG approaches

arXiv:2601.07711v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems are usually defined by the combination of a generator and a retrieval component that extracts textual c

agentsarxiv-cs-cl

Learning Unanimously Acceptable Lotteries via Queries

arXiv:2604.17505v1 Announce Type: cross Abstract: Many high-stakes AI deployments proceed only if every stakeholder deems the system acceptable relative to their own minimum standard. With randomizati

Tutorials

Learning Whole-Body Humanoid Locomotion via Motion Generation and Motion Tracking

arXiv:2604.17335v1 Announce Type: new Abstract: Whole-body humanoid locomotion is challenging due to high-dimensional control, morphological instability, and the need for real-time adaptation to vario

tutorialsarxiv-cs-ro

Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification

arXiv:2601.21244v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has advanced LLM reasoning, but remains constrained by inefficient exploration under lim

safetyarxiv-cs-cl

LiveGraph: Active-Structure Neural Re-ranking for Exercise Recommendation

arXiv:2602.17036v2 Announce Type: replace-cross Abstract: The continuous expansion of digital learning environments has catalyzed the demand for intelligent systems capable of providing personalized e

applicationsarxiv-cs-lg

LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies

arXiv:2604.16935v1 Announce Type: cross Abstract: Scarce longitudinal evidence examines LLMs' persuasiveness and humanness along time-evolving psychological frameworks. We introduce Talk2AI, a longitu

LookasideVLN: Direction-Aware Aerial Vision-and-Language Navigation

arXiv:2604.17190v1 Announce Type: new Abstract: Aerial Vision-and-Language Navigation (Aerial VLN) enables unmanned aerial vehicles (UAVs) to follow natural language instructions and navigate complex

agentsarxiv-cs-cv

LoRaQ: Optimized Low Rank Approximation for 4-bit Quantization

arXiv:2604.18117v1 Announce Type: new Abstract: Post-training quantization (PTQ) is essential for deploying large diffusion transformers on resource-constrained hardware, but aggressive 4-bit quantiza

LTRR: Learning To Rank Retrievers for LLMs

arXiv:2506.13743v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems typically rely on a single fixed retriever, despite growing evidence that no single retriever performs

Mapping Election Toxicity on Social Media across Issue, Ideology, and Psychosocial Dimensions

arXiv:2604.16765v1 Announce Type: cross Abstract: Online political hostility is pervasive, yet it remains unclear how toxicity varies across campaign issues and political ideology, and what psychosoci

MASPO: Unifying Gradient Utilization, Probability Mass, and Signal Reliability for Robust and Sample-Efficient LLM Reasoning

arXiv:2602.17550v3 Announce Type: replace Abstract: Existing Reinforcement Learning with Verifiable Rewards (RLVR) algorithms, such as GRPO, rely on rigid, uniform, and symmetric trust region mechanis

safetyarxiv-cs-lg

Matched-Learning-Rate Analysis of Attention Drift and Transfer Retention in Fine-Tuned CLIP

arXiv:2604.16410v1 Announce Type: new Abstract: CLIP adaptation can improve in-domain accuracy while degrading out-of-domain transfer, but comparisons between Full Fine-Tuning (Full FT) and LoRA are o

Mechanisms of Multimodal Synchronization: Insights from Decoder-Based Video-Text-to-Speech Synthesis

arXiv:2411.17690v3 Announce Type: replace-cross Abstract: Unified decoder-only transformers have shown promise for multimodal generation, yet the mechanisms by which they synchronize modalities with h

Medial Axis Aware Learning of Signed Distance Functions

arXiv:2604.16512v1 Announce Type: new Abstract: We propose a novel variational method to compute a highly accurate global signed distance function (SDF) to a given point cloud. To this end, the jump s

Migrant Voices, Local News: Insights on Bridging Community Needs with Media Content

arXiv:2604.16651v1 Announce Type: new Abstract: Research shows news consumption differs across demographics, yet little is known about non-mainstream audiences, especially in relation to local media.

MODEST: Multi-Optics Depth-of-Field Stereo Dataset

arXiv:2511.20853v3 Announce Type: replace Abstract: Reliable depth estimation under real optical conditions remains a core challenge for camera vision in systems such as autonomous robotics and augmen

agentsarxiv-cs-cv

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

local-aiarxiv-cs-cv

Neuroscience Inspired Graph Operators Towards Edge-Deployable Virtual Sensing for Irregular Geometries

arXiv:2604.16722v1 Announce Type: new Abstract: Predicting full-field physics through the real-time virtual sensing of engineering systems can enhance limited physical sensors but often requires spars

Novel Algorithms for Smoothly Differentiable and Efficiently Vectorizable Contact Manifold Construction

arXiv:2604.17538v1 Announce Type: new Abstract: Generating intelligent robot behavior in contact-rich settings is a research problem where zeroth-order methods currently prevail. Developing methods th

researcharxiv-cs-ro

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

On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations

arXiv:2604.16518v1 Announce Type: new Abstract: Satellite constellations are transforming space systems from isolated spacecraft into networked, software-defined platforms capable of on-orbit percepti

safetyarxiv-cs-ro

Pearmut: Human Evaluation of Translation Made Trivial

arXiv:2601.02933v3 Announce Type: replace Abstract: Human evaluation is the gold standard for multilingual NLP, but is often skipped in practice and substituted with automatic metrics because it is no

Physics-Informed Tracking (PIT)

arXiv:2604.16895v1 Announce Type: new Abstract: We propose Physics-Informed Tracking (PIT), a video-based framework for tracking a single particle from video, where a neural network autoencoder locali

Preventing overfitting in deep learning using differential privacy

arXiv:2604.16334v1 Announce Type: new Abstract: The use of Deep Neural Network based systems in the real world is growing. They have achieved state-of-the-art performance on many image, speech and tex

applicationsarxiv-cs-lg

Tutorials

PyEPO: A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming

arXiv:2206.14234v3 Announce Type: replace-cross Abstract: In deterministic optimization, it is typically assumed that all problem parameters are fixed and known. In practice, however, some parameters

tutorialsarxiv-cs-lg

Tutorials

Randomly Initialized Networks Can Learn from Peer-to-Peer Consensus

arXiv:2604.18390v1 Announce Type: new Abstract: In self-supervised learning, self-distilled methods have shown impressive performance, learning representations useful for downstream tasks and even dis

tutorialsarxiv-cs-lg

RASP-Tuner: Retrieval-Augmented Soft Prompts for Context-Aware Black-Box Optimization in Non-Stationary Environments

arXiv:2604.18026v1 Announce Type: new Abstract: Many deployed systems expose black-box objectives whose minimizing configuration shifts with an externally observed context. When contexts revisit a sma

applicationsarxiv-cs-lg

Hardware

Real-Time Structural Detection for Indoor Navigation from 3D LiDAR Using Bird's-Eye-View Images

arXiv:2603.19830v2 Announce Type: replace Abstract: Efficient structural perception is essential for mapping and autonomous navigation on resource-constrained robots. Existing 3D methods are computati

hardwarearxiv-cs-ro

Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework

arXiv:2604.18145v1 Announce Type: new Abstract: Automated medical report generation for 3D PET/CT imaging is fundamentally challenged by the high-dimensional nature of volumetric data and a critical s

local-aiarxiv-cs-cv

Rewind-IL: Online Failure Detection and State Respawning for Imitation Learning

arXiv:2604.16683v1 Announce Type: cross Abstract: Imitation learning has enabled robots to acquire complex visuomotor manipulation skills from demonstrations, but deployment failures remain a major ob

local-aiarxiv-cs-cv

RHINO-AR: An Augmented Reality Exhibit for Teaching Mobile Robotics Concepts in Museums

arXiv:2604.16384v1 Announce Type: new Abstract: We present RHINO-AR, an interactive Augmented Reality (AR) museum exhibit that reintroduces the historical mobile robot RHINO into its original exhibiti

researcharxiv-cs-ro

See Through the Noise: Improving Domain Generalization in Gaze Estimation

arXiv:2604.16562v1 Announce Type: new Abstract: Generalizable gaze estimation methods have garnered increasing attention due to their critical importance in real-world applications and have achieved s

Self-Supervised Super-Resolution for Sentinel-5P Hyperspectral Images

arXiv:2604.17652v1 Announce Type: new Abstract: Sentinel-5P (S5P) plays a critical role in atmospheric monitoring; however, its spatial resolution limits fine-scale analysis. Existing super-resolution

Semantic-based Distributed Learning for Diverse and Discriminative Representations

arXiv:2604.18237v1 Announce Type: new Abstract: In large-scale distributed scenarios, increasingly complex tasks demand more intelligent collaboration across networks, requiring the joint extraction o

SemLT3D: Semantic-Guided Expert Distillation for Camera-only Long-Tailed 3D Object Detection

arXiv:2604.18476v1 Announce Type: new Abstract: Camera-only 3D object detection has emerged as a cost-effective and scalable alternative to LiDAR for autonomous driving, yet existing methods primarily

Soft Label Pruning and Quantization for Large-Scale Dataset Distillation

arXiv:2604.18135v1 Announce Type: new Abstract: Large-scale dataset distillation requires storing auxiliary soft labels that can be 30-40x larger on ImageNet-1K and 200x larger on ImageNet-21K than th

Spectral Forensics of Diffusion Attention Graphs for Copy-Move Forgery Detection

arXiv:2604.17287v1 Announce Type: new Abstract: Copy-move forgery, where a region within an image is duplicated to hide or fabricate content, remains a persistent threat to visual media integrity. We