Search: “framework”

Discovering Crystal Structure Prediction Algorithms with an AI Co-Scientist

arXiv:2606.22866v1 Announce Type: new Abstract: We introduce Human-AI Co-discovery system (HACO) for scientific algorithm discovery through cross-domain search and sparse human steering. Starting from

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Discovering Latent Groups for Robust Classification

DGX agent

arXiv:2606.23609v1 Announce Type: cross Abstract: Machine learning models exploit spurious correlations, achieving high average accuracy but failing disproportionately on underrepresented subgroups. E

researcharxiv-cs-cv

23 Jun 2026

Discrete Geometric Modeling and Extended State Estimation of Continuum Robots

arXiv:2606.21205v1 Announce Type: cross Abstract: In this paper, we present a fully discrete approach for the accurate and numerically efficient dynamical modeling and state estimation of continuum ro

researcharxiv-cs-ro

Discrete State Diffusion Models: A Sample Complexity Perspective

arXiv:2510.10854v3 Announce Type: replace Abstract: Diffusion models have demonstrated remarkable performance in generating high-dimensional samples across domains such as vision, language, and the sc

Distilling Collaborative Dynamics into Latent Space for Implicit Coordination in Decentralized Multi-Agent Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.22982v1 Announce Type: new Abstract: Multi-arm manipulation demands precise spatiotemporal coordination, yet many centralized approaches scale poorly as team size increases. To address this

Distributed Model Predictive Control with Adaptive Safety Zones for Multi-Fleet Drone Operations

model-releasesarxiv-cs-ro

arXiv:2606.20651v1 Announce Type: cross Abstract: Autonomous drone swarms in space-constrained environments such as warehouses, inspection corridors, and urban delivery routes must share limited airsp

Distribution-Aware Diffusion-LLM for Robust Ultra-Long-Term Time Series Forecasting

arXiv:2606.23391v1 Announce Type: new Abstract: Time series forecasting is a fundamental machine learning task. Recent work has explored Large Language Models (LLMs) for this purpose due to their stro

Distribution-Aware Robust Bilevel Optimization: Quantile-Guided Huber Updates in Two-Timescale Stochastic Approximation

arXiv:2606.22436v1 Announce Type: new Abstract: Bilevel optimization (BLO) is fundamental to hierarchical decision-making but suffers from critical instability under heavy-tailed stochastic noise. Exi

DivCon-NeRF: Diverse and Consistent Ray Augmentation for Few-Shot NeRF

arXiv:2503.12947v3 Announce Type: replace Abstract: Neural Radiance Field (NeRF) has shown remarkable performance in novel view synthesis but requires numerous multi-view images, limiting its practica

Do Location Encoders Capture Spatial Effects? A GeoShapley Benchmark Across Scales

arXiv:2606.23453v1 Announce Type: new Abstract: Location encoders transform geographic coordinates into high dimensional embeddings for downstream machine learning, but it is unclear how well these re

Don't Tell the Answer, Truly Guide the Reasoning During RL Rollouts

arXiv:2510.09388v2 Announce Type: replace Abstract: Reinforcement Learning (RL) has become a key driver for enhancing the long chain-of-thought (CoT) reasoning capabilities of Large Language Models (L

DR-Mamba: Automatic Inference-Time Domain Adaptation for Document Image Binarization via Sample-Conditioned Detail-Background Suppression

arXiv:2606.22625v1 Announce Type: new Abstract: Degraded document image binarization is sensitive to domain shifts caused by paper aging, bleed-through, stains, shadows, and uneven illumination, and t

Applications

DreamUV: Unwrap Artist-like UV by End-to-End Flow Matching

arXiv:2606.22445v1 Announce Type: new Abstract: UV parameterization is a fundamental step in 3D content creation, yet producing production-ready UV layouts remains challenging due to the gap between g

applicationsarxiv-cs-cv

DT-GOL: Dual-Track Geometric Online Learning in Nonstationary Environment with Label Delay

arXiv:2606.22950v1 Announce Type: new Abstract: Online learning is crucial for handling complex data streams in big data applications. Recent research has begun to focus on dynamic scenarios, i.e., no

Applications

Durability-Aware Multi-Objective Optimization of the Jansen Linkage: Trading Gait Quality Against Joint Wear

arXiv:2606.22129v1 Announce Type: new Abstract: The Jansen linkage is a single-degree-of-freedom planar leg mechanism whose eleven 'holy numbers' were evolved by Theo Jansen to optimize the foot-path

applicationsarxiv-cs-ro

ECGFlowCMR: Pretraining with ECG-Generated Cine CMR Helps Cardiac Disease Classification and Phenotype Prediction

arXiv:2601.20904v3 Announce Type: replace-cross Abstract: Cardiac Magnetic Resonance (CMR) imaging provides a comprehensive assessment of cardiac structure and function but remains constrained by high

EchoingPixels: Aliasing-Resistant Joint Token Reduction for Audio-Visual LLMs

arXiv:2512.10324v2 Announce Type: replace Abstract: Audio-Visual Large Language Models (AV-LLMs) face prohibitive computational costs of processing massive, redundant audio-visual tokens. Existing uni

Efficient Reinforcement Finetuning via Adaptive Curriculum Learning

arXiv:2504.05520v4 Announce Type: replace Abstract: Reinforcement finetuning (RFT) has shown great potential for enhancing the mathematical reasoning capabilities of large language models (LLMs), but

EgoExo-Con: Exploring View-Invariant Video Temporal Understanding

arXiv:2510.26113v2 Announce Type: replace Abstract: Do Video-LLMs have consistent temporal understanding when videos capture the same event from different viewpoints? To study this question, we introd

Embedding Linear Equality Constraints in Probabilistic Neural Networks for Dynamic Modelling

arXiv:2606.21728v1 Announce Type: new Abstract: Machine learning models are increasingly used to model chemical process systems, yet they often lack principled uncertainty quantification and mechanism

EML Trees Are Universal Approximators

arXiv:2606.23179v1 Announce Type: new Abstract: The recently introduced EML (Exp-Minus-Log) function acts as continuous analogue of NAND gates, providing a compositional building block capable of repr

Agents

Empowering Embodied AI in 6G Networks: Architecture, Enablers, and Open Challenges

arXiv:2606.20592v1 Announce Type: cross Abstract: Embodied artificial intelligence (AI) is emerging as a key driver of the sixth-generation (6G) wireless networks by enabling agents that continuously

agentsarxiv-cs-lg

Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing

arXiv:2606.22496v1 Announce Type: cross Abstract: Large language models (LLMs) offer a natural-language interface for interpreting Internet of Things (IoT) sensor data in smart environments; however,

local-aiarxiv-cs-lg

Energy-based Compositional Diffusion Planning

arXiv:2606.21646v1 Announce Type: new Abstract: Compositional diffusion planners aim to solve long-horizon robotic tasks using short training trajectories. Yet, current approaches often rely on the he

local-aiarxiv-cs-ro

Enhancing IMU-Based Online Handwriting Recognition via Contrastive Learning with Zero Inference Overhead

arXiv:2602.07049v2 Announce Type: replace Abstract: Online handwriting recognition using inertial measurement units opens up handwriting on paper as input for digital devices. Doing it on edge hardwar

safetyarxiv-cs-cv

Enhancing Road Safety: An IoT-Based Accident Detection and Prevention Mechanism

arXiv:2606.22381v1 Announce Type: cross Abstract: Road traffic accidents remain a critical global crisis, consistently serving as a primary driver of preventable mortality and severe injury. These inc

safetyarxiv-cs-cv

Applications

Enhancing Symbolic Regression and Universal Physics-Informed Neural Networks with Dimensional Analysis

arXiv:2411.15919v2 Announce Type: replace Abstract: In engineering and applied mathematics, developing accurate mathematical models to predict and understand real-world phenomena is of utmost importan

applicationsarxiv-cs-lg

EnTrust: Modeling Inter-Modal Conflict for Trustworthy Multimodal Medical Image Analysis

arXiv:2606.21384v1 Announce Type: new Abstract: Multimodal medical imaging fuses complementary anatomical and functional information, yet modalities frequently disagree in pathologically heterogeneous

local-aiarxiv-cs-cv

Evaluating self-supervised echocardiographic representations across downstream extraction strategies for left-ventricular segmentation and ejection fraction estimation

arXiv:2606.22943v1 Announce Type: new Abstract: Self-supervised learning (SSL) is increasingly used in medical imaging to reduce annotation requirements, but representation quality is often judged usi

Evaluation of Medical Vision Language Models HuluMed and MedGemma, and general purpose chatbots Gemma 3, ChatGPT Plus, and Claude Pro on real previously unseen wound images

arXiv:2606.20723v1 Announce Type: new Abstract: Chronic wound assessment remains a clinically challenging task that requires accurate interpretation of wound morphology, tissue composition, vascular c

Evo-RAD: Navigating Rare Retinal Disease Diagnosis via Self-Evolving Agentic Retrieval

arXiv:2606.22955v1 Announce Type: new Abstract: Large-scale pretrained foundation models have revolutionized general medical screening, but often falter on rare diseases because such conditions are un

Evolutionary Optimization Reveals Structural Constraints on Reservoir Architecture for Spatiotemporal Chaos

arXiv:2606.22765v1 Announce Type: cross Abstract: Biological systems maintain function in fluctuating environments by transforming past stimulation into internal dynamical states that support future-o

EvoRubrics: Dynamic Rubrics as Rewards via Adversarial Co-Evolution for LLM Reinforcement Learning

arXiv:2606.23038v1 Announce Type: new Abstract: Rubric-based rewards offer interpretable and fine-grained optimization signals for reinforcement learning in open-ended tasks where verifiable answers a

Expert Consensus on Criteria for the Automated Assessment of Laparoscopic Camera Navigation

arXiv:2606.23131v1 Announce Type: new Abstract: Background: Laparoscopic camera navigation (LCN) is a critical skill, yet its current assessment typically relies on manual rating systems which are tim

safetyarxiv-cs-cv

Explainable Boosting Machine for Predicting Claim Severity and Frequency in Car Insurance

arXiv:2503.21321v2 Announce Type: replace-cross Abstract: With the rapid development of machine learning and deep learning techniques, actuaries and the broader insurance industry face a persistent tr

Factor-Aware Mixture-of-Experts with Pretrained Encoder for Combinatorial Generalization

model-releasesarxiv-cs-ro

arXiv:2606.21100v1 Announce Type: new Abstract: The integration of pretrained encoders with diffusion policies has become a dominant paradigm for visual robotic manipulation. However, it still struggl

Factored Gossip DiLoCo: Reducing Blocking Communication in DiLoCo

arXiv:2606.22768v1 Announce Type: new Abstract: To make large-scale distributed training practical outside high-bandwidth datacenters, we must reduce blocking, high-volume synchronization. While DiLoC

Failure Analysis in Transition: An Industry Survey of Challenges, Priorities, and Standardization Needs in Advanced Packaging and Heterogeneous Integration

arXiv:2606.22149v1 Announce Type: cross Abstract: Failure analysis is being reshaped by heterogeneous integration, chiplet-based architectures, hybrid bonding, backside technologies, & increasingly bu

Fed-CausalDiff: Decoupled Synchronization for Federated Do-Simulation and Policy Evaluation

arXiv:2606.22510v1 Announce Type: new Abstract: While federated learning enables collaborative modelling on decentralised data, standard methods merely fit historical observations. This purely observa

local-aiarxiv-cs-lg

Federated Temporal Attention Intelligence for Cyber-Resilient IoMT: Lightweight Digital Twins and PPO-Driven Honeypot Deception

arXiv:2606.21422v1 Announce Type: new Abstract: The rapid proliferation of Internet of Medical Things (IoMT) devices introduces critical cybersecurity vulnerabilities in healthcare environments where

FedOT: Ownership Verification and Leakage Tracing via Watermarks for Federated LDMs

arXiv:2606.22875v1 Announce Type: new Abstract: Training Latent Diffusion Models (LDMs) within Federated Learning (FL) has attracted increasing attention due to its ability to combine the powerful gen

Feed-forward Motion In-betweening for Any 4D

arXiv:2606.22131v1 Announce Type: new Abstract: 4D dynamics (3D geometry evolving over time) is a fundamental representation of the physical world and plays a crucial role in world modeling (e.g., ani

Hardware

FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism

arXiv:2606.22180v1 Announce Type: cross Abstract: Graph embedding maps graph nodes into low-dimensional vectors to support applications such as recommendation, fraud detection, and graph-based retriev

hardwarearxiv-cs-lg

FetSelect: Task-Specific Architectures and Self-Supervised Learning for Automated Fetal Ultrasound Frame Selection

arXiv:2606.22487v1 Announce Type: new Abstract: Automated frame selection for fetal biometry remains under addressed, with most prior work targeting generic quality assessment or downstream measuremen

Hardware

FGGS-LiDAR: Ultra-Fast, GPU-Accelerated Simulation from General 3DGS Models to LiDAR

arXiv:2509.17390v2 Announce Type: replace Abstract: While 3D Gaussian Splatting (3DGS) has emerged as a strong representation for photorealistic rendering, its vast ecosystem of assets remains difficu

hardwarearxiv-cs-ro

Fidelity- and Perception-Aware Local Implicit Attention for Arbitrary-Scale Image Super-Resolution

arXiv:2606.21910v1 Announce Type: new Abstract: Arbitrary-scale image super-resolution (ASISR) aims to reconstruct high-resolution images from low-resolution inputs over a continuous range of upscalin

FILIC: Dual-Loop Force-Guided Imitation Learning with Impedance Torque Control for Contact-Rich Manipulation Tasks

arXiv:2509.17053v2 Announce Type: replace Abstract: Many contact-rich manipulation tasks require precise force regulation. However, most imitation learning (IL) policies remain position-centric and la

safetyarxiv-cs-ro

Fine-Grained Uncertainty Quantification for Long-Form Language Model Outputs: A Comparative Study

arXiv:2602.17431v2 Announce Type: replace-cross Abstract: Uncertainty quantification has emerged as an effective approach to closed-book hallucination detection for LLMs, but existing methods are larg