Search: “framework”

Function-based Parametric Co-Design Optimization of Dexterous Hands

model-releasesarxiv-cs-ro

arXiv:2604.27557v1 Announce Type: new Abstract: Despite advances in dexterous hand manipulation, robotic hand design is still largely decoupled from task-driven evaluation and control, limiting system

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Hypencoder Revisited: Reproducibility and Analysis of Non-Linear Scoring for First-Stage Retrieval

DGX agent

arXiv:2604.27037v1 Announce Type: cross Abstract: The Hypencoder, proposed by Killingback et al., is a retrieval framework that replaces the fixed inner-product scoring function used in standard bi-en

researcharxiv-cs-cl

1 May 2026

Tutorials

Mapping the Methodological Space of Classroom Interaction Research: Scale, Duration, and Modality in an Age of AI

arXiv:2604.28098v1 Announce Type: new Abstract: Research on classroom interaction has long been divided between large-scale observation and in-depth ethnographic work. We propose a framework mapping t

tutorialsarxiv-cs-ai

Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO

model-releasesarxiv-cs-cl

arXiv:2604.27488v1 Announce Type: new Abstract: We introduce Skills-Coach, a novel automated framework designed to significantly enhance the self-evolution of skills within Large Language Model (LLM)-

WaferSAGE: Large Language Model-Powered Wafer Defect Analysis via Synthetic Data Generation and Rubric-Guided Reinforcement Learning

arXiv:2604.27629v1 Announce Type: new Abstract: We present WaferSAGE, a framework for wafer defect visual question answering using small vision-language models. To address data scarcity in semiconduct

Cheeger--Hodge Contrastive Learning for Structurally Robust Graph Representation Learning

arXiv:2604.26301v1 Announce Type: new Abstract: Graph Contrastive Learning (GCL) has emerged as a prominent framework for unsupervised graph representation learning. However, relying on augmentation d

researcharxiv-cs-lg

Co-Learning Port-Hamiltonian Systems and Optimal Energy-Shaping Control

arXiv:2604.26172v1 Announce Type: cross Abstract: We develop a physics-informed learning framework for energy-shaping control of port-Hamiltonian (pH) systems from trajectory data. The proposed approa

Evaluating the Alignment Between GeoAI Explanations and Domain Knowledge in Satellite-Based Flood Mapping

arXiv:2604.26051v1 Announce Type: cross Abstract: The increasing number of satellites has improved the temporal resolution of Earth observation, making satellite-based flood mapping a promising approa

OMEGA: Optimizing Machine Learning by Evaluating Generated Algorithms

arXiv:2604.26211v1 Announce Type: new Abstract: In order to automate AI research we introduce a full, end-to-end framework, OMEGA: Optimizing Machine learning by Evaluating Generated Algorithms, that

Quantum Gatekeeper: Multi-Factor Context-Bound Image Steganography with VQC Based Key Derivation on Quantum Hardware

arXiv:2604.26413v1 Announce Type: cross Abstract: This paper presents Quantum Gatekeeper, a context-bound image steganography framework where successful payload recovery depends on both cryptographic

[R] Joint Embedding Variational Bayes (TMLR ’26)

researchr-machinelearning

Variational Joint Embedding (VJE) is a framework that synthesizes joint embedding and variational inference to enable self-supervised learning of probabilistic representations in a reconstruction-free

Risk Reporting for Developers' Internal AI Model Use

arXiv:2604.24966v1 Announce Type: cross Abstract: Frontier AI companies first deploy their most advanced models internally, for weeks or months of safety testing, evaluation, and iteration, before a p

Variable Elimination in Hybrid Factor Graphs for Discrete-Continuous Inference & Estimation

arXiv:2601.00545v3 Announce Type: replace Abstract: Many problems in robotics involve both continuous and discrete components, and modeling them together for estimation tasks has been a long standing

applicationsarxiv-cs-ro

BARRED: Synthetic Training of Custom Policy Guardrails via Asymmetric Debate

arXiv:2604.25203v1 Announce Type: new Abstract: Deploying guardrails for custom policies remains challenging, as generic safety models fail to capture task-specific requirements, while prompting LLMs

safetyarxiv-cs-cl

DCD: Decomposition-based Causal Discovery from Autocorrelated and Non-Stationary Temporal Data

arXiv:2602.01433v2 Announce Type: replace Abstract: Multivariate time series in domains such as finance, climate science, and healthcare often exhibit long-term trends, seasonal patterns, and short-te

applicationsarxiv-cs-lg

Frictive Policy Optimization for LLMs: Epistemic Intervention, Risk-Sensitive Control, and Reflective Alignment

arXiv:2604.25136v1 Announce Type: new Abstract: We propose Frictive Policy Optimization (FPO), a framework for learning language model policies that regulate not only what to say, but when and how to

safetyarxiv-cs-cl

Independent-Component-Based Encoding Models of Brain Activity During Story Comprehension

arXiv:2604.24942v1 Announce Type: new Abstract: Encoding models provide a powerful framework for linking continuous stimulus features to neural activity; however, traditional voxelwise approaches are

researcharxiv-cs-cl

Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing

arXiv:2604.24880v1 Announce Type: cross Abstract: This study proposes an anomaly-detection framework for monitoring exposure-length variations in submarine free-span cables using Distributed Acoustic

researcharxiv-cs-lg

Negative Ontology of True Target for Machine Learning: Towards Evaluation and Learning under Democratic Supervision

arXiv:2604.24824v1 Announce Type: new Abstract: This article philosophically examines how shifts in assumptions regarding the existence and non-existence of the true target (TT) give rise to new persp

applicationsarxiv-cs-lg

Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models

arXiv:2604.25636v1 Announce Type: new Abstract: Unified multimodal models (UMMs) integrate visual understanding and generation within a single framework. For text-to-image (T2I) tasks, this unified ca

safetyarxiv-cs-cv

VAE-Inf: A statistically interpretable generative paradigm for imbalanced classification

arXiv:2604.25334v1 Announce Type: new Abstract: Imbalanced classification remains a pervasive challenge in machine learning, particularly when minority samples are too scarce to provide a robust discr

applicationsarxiv-cs-lg

A2DEPT: Large Language Model-Driven Automated Algorithm Design via Evolutionary Program Trees

arXiv:2604.24043v1 Announce Type: new Abstract: Designing heuristics for combinatorial optimization problems (COPs) is a fundamental yet challenging task that traditionally requires extensive domain e

Agent-Aided Design for Dynamic CAD Models

arXiv:2604.15184v2 Announce Type: replace Abstract: In the past year, researchers have created agentic systems that can design real-world CAD-style objects in a training-free setting, a new variety of

Conformal PM2.5 Mapping Under Spatial Covariate Shift: Satellite-Reanalysis Fusion for Africa's Green Industrial Transition

arXiv:2604.22787v1 Announce Type: cross Abstract: Africa's green industrialization imperative demands reliable infrastructure for monitoring air quality. We present a satellite-reanalysis PM2.5 fusion

CyberCane: Neuro-Symbolic RAG for Privacy-Preserving Phishing Detection with Formal Ontology Reasoning

arXiv:2604.23563v1 Announce Type: cross Abstract: Privacy-critical domains require phishing detection systems that satisfy contradictory constraints: near-zero false positives to prevent workflow disr

Dr. RTL: Autonomous Agentic RTL Optimization through Tool-Grounded Self-Improvement

arXiv:2604.14989v2 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have sparked growing interest in automatic RTL optimization for better performance, power, and area

Expert Evaluation of LLM's Open-Ended Legal Reasoning on the Japanese Bar Exam Writing Task

arXiv:2604.23730v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance on legal benchmarks, including multiple-choice components of bar exams. However, their capaci

Failure-Centered Runtime Evaluation for Deployed Trilingual Public-Space Agents

arXiv:2604.23990v1 Announce Type: new Abstract: This paper presents PSA-Eval, a failure-centered runtime evaluation framework for deployed trilingual public-space agents. The central claim is that, wh

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

H-SemiS: Hierarchical Fusion of Semi and Self-Supervised Learning for Knee Osteoarthritis Severity Grading

arXiv:2604.23335v1 Announce Type: new Abstract: Knee osteoarthritis (KOA) is a degenerative joint disease that can lead to chronic pain, reduced mobility, and long-term disability. Automated severity

researcharxiv-cs-cv

Hardware

Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation

arXiv:2604.23632v1 Announce Type: new Abstract: Real-time text-driven joint audio-video avatar generation requires jointly synthesizing portrait video and speech with high fidelity and precise synchro

hardwarearxiv-cs-cv

Information-Theoretic Measures in AI: A Practical Decision Guide

arXiv:2604.23716v1 Announce Type: new Abstract: Information-theoretic (IT) measures are ubiquitous in artificial intelligence: entropy drives decision-tree splits and uncertainty quantification, cross

Interpretable Physics-Informed Load Forecasting for U.S. Grid Resilience: SHAP-Guided Ensemble Validation in Hybrid Deep Learning Under Extreme Weather

arXiv:2604.23500v1 Announce Type: cross Abstract: Accurate short-term electricity load forecasting is a cornerstone of U.S. grid reliability; however, prevailing deep learning models remain opaque, li

K-SENSE: A Knowledge-Guided Self-Augmented Encoder for Neuro-Semantic Evaluation of Mental Health Conditions on Social Media

arXiv:2604.23493v1 Announce Type: cross Abstract: Early detection of mental health conditions, particularly stress and depression, from social media text remains a challenging open problem in computat

Local Ai

Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning

arXiv:2604.22795v1 Announce Type: cross Abstract: This study presents a multi-agent reinforcement learning (MARL) framework for load-constrained wind farm flow control (WFFC). While wake steering can

local-aiarxiv-cs-lg

mKG-RAG: Leveraging Multimodal Knowledge Graphs in Retrieval-Augmented Generation for Knowledge-intensive VQA

arXiv:2508.05318v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for expanding the knowledge capacity of Multimodal Large Language Mo

Model-Free Inference of Investor Preferences: A Relative Entropy IRL Approach

arXiv:2604.24280v1 Announce Type: new Abstract: We present a framework using Relative Entropy Inverse Reinforcement Learning (RE-IRL) to recover investor reward functions from observed investment acti

safetyarxiv-cs-lg

On the Peril of (Even a Little) Nonstationarity in Satisficing Regret Minimization

arXiv:2603.18514v2 Announce Type: replace-cross Abstract: Motivated by the principle of satisficing in decision-making, we study satisficing regret guarantees for nonstationary K-armed bandits. We sho

researcharxiv-cs-lg

OpenVO: Open-World Visual Odometry with Temporal Dynamics Awareness

arXiv:2602.19035v2 Announce Type: replace Abstract: We introduce OpenVO, a novel framework for Open-world Visual Odometry (VO) with temporal awareness under limited input conditions. OpenVO effectivel

agentsarxiv-cs-cv

Personalizing Causal Audio-Driven Facial Motion via Dynamic Multi-modal Retrieval

arXiv:2604.23692v1 Announce Type: cross Abstract: Audio-driven facial animation is essential for immersive digital interaction, yet existing frameworks fail to reconcile real-time streaming with high-

researcharxiv-cs-cv

Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data

arXiv:2503.05587v3 Announce Type: replace-cross Abstract: Robustness has become a critical attribute for the deployment of RAG systems in real-world applications. Existing research focuses on robustne

Tutorials

Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation

arXiv:2510.11541v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) has demonstrated its ability to enhance Large Language Models (LLMs) by integrating external knowledge so

tutorialsarxiv-cs-ai

Local Ai

Resource-Constrained UAV-Based Weed Detection for Site-Specific Management on Edge Devices

arXiv:2604.23442v1 Announce Type: new Abstract: Weeds compete with crops for light, water, and nutrients, reducing yield and crop quality. Efficient weed detection is essential for site-specific weed

local-aiarxiv-cs-cv

See No Evil: Semantic Context-Aware Privacy Risk Detection for AR

arXiv:2604.22805v1 Announce Type: cross Abstract: Augmented reality (AR) systems pose unique privacy risks due to their continuous capture of visual data. Existing AR privacy frameworks lack semantic

Speech Enhancement Based on Drifting Models

arXiv:2604.24199v1 Announce Type: cross Abstract: We propose Speech Enhancement based on Drifting Models (DriftSE), a novel generative framework that formulates denoising as an equilibrium problem. Ra

Tutorials

Structure Guided Retrieval-Augmented Generation for Factual Queries

arXiv:2604.22843v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has been proposed to mitigate hallucinations in large language models (LLMs), where generated outputs may be fact

tutorialsarxiv-cs-ai

The Alignment Target Problem: Divergent Moral Judgments of Humans, AI Systems, and Their Designers

arXiv:2604.24155v1 Announce Type: cross Abstract: The quest to align machine behavior with human values raises fundamental questions about the moral frameworks that should govern AI decision-making. M

Touchless Intraoperative Image Access System Based on Vision-Based Hand Tracking

arXiv:2604.24235v1 Announce Type: new Abstract: Touchless interaction with medical images is becoming increasingly important in the surgical field, where sterility and continuity of the operational wo

researcharxiv-cs-cv