Research

Research, evidence gathering, literature, reports, investigation, and synthesis

skills in category: 21,402
pages available: 892

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Showing 11,785–11,808 of 21,402 skills

Semantic Navigation Embedding TrajectoriesASkill for AI agent capabilitiesresearchpythonVotes: 0GitHub stars: 3
Selfimproving Language Models For Evolutionary Program Synthesis A Case Study On ArcagiA**arXiv ID:** 2507.14172 **Authors:** Julien Pourcel, Cédric Colas, Pierre-Yves Oudeyer **Published:** 2025-07-10T15:42:03Z **Abstract:** Many program synthesis tasks prove too challenging for even state-of-the-art language models to solve in single attempts. Search-based evolutionary methods offer a promising alternative by exploring solution spaces iteratively, but their effectiveness remain limited by the fixed capabilities of the underlying generative model. We propose SOAR, a method that...researchgitperformanceVotes: 0GitHub stars: 3
Research Skill ExtractorAMeta-skill that extracts reusable skill patterns from research papers (arxiv), scientific workflows, and knowledge graph analysis. Activates when analyzing papers for skill patterns, creating skills from research methodologies, or mining patterns from scientific literature. Keywords: extract skill from paper, research skill mining, 论文技能提炼, paper to skill, arxiv skill extractor.researchgobashVotes: 0GitHub stars: 3
Research Paper WritingAEnd-to-end pipeline for writing ML/AI research papers — from experiment design through analysis, drafting, revision, and submission. Covers NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Integrates automated experiment monitoring, statistical analysis, iterative writing, and citation verification.researchpythonrustVotes: 0GitHub stars: 3
Research Paper Pattern ExtractorAExtract reusable research skill patterns from knowledge graph paper analysis. Uses PageRank, Louvain, and vector search to identify important papers and research clusters, then distills patterns into new skills. Activation: extract research pattern, research skill extractor, 研究模式提炼, paper pattern analysis.researchpythongoVotes: 0GitHub stars: 3
Requests For Research 20ASkill for AI agent capabilitiesresearchpythongoVotes: 0GitHub stars: 3
Qpinn Trainable EmbeddingsAQPINN Framework with Quantum Trainable Embeddings for PDE solving. Use when building quantum physics-informed neural networks, variational quantum circuits for PDEs, quantum feature maps for scientific computing, or quantum-assisted fluid dynamics simulations. Triggered by: QPINN, quantum PINN, quantum physics-informed neural network, quantum trainable embeddings, quantum PDE solver, quantum neural network for fluid dynamics.researchpythongoVotes: 0GitHub stars: 3
Kg Research WorkflowCEnd-to-end academic research workflow using knowledge graphs. Searches papers from arxiv/web, imports to KG database, generates embeddings, runs graph algorithms (PageRank, vector search), and extracts patterns for skill creation. Use for: automated research workflows, paper analysis pipelines, KG-based literature review.researchpythonrustVotes: 0GitHub stars: 3
Fluid Search Autonomous Research EfficiencyAFluid search methodology for adaptive search efficiency in autonomous research systems. Uses portfolio bandit to dynamically allocate evaluation budget across search processes, optimizing area under Pareto frontier curve.researchgoperformanceVotes: 0GitHub stars: 3
Feature Life History ScaffoldAFeature life history methodology for LLM training dynamics. Identifies the carrier scaffold — ~50 sparse features with stable life histories that organize the model's representational structure. Training follows two phases: selection (first 1%, features emerge/die 40x faster) and calibration (remaining 99%). Use when: analyzing LLM training dynamics, studying feature emergence, identifying core representational structure, sparse feature analysis, cross-layer ablation studies, interpretability...researchpythonperformanceVotes: 0GitHub stars: 3
Evaluation Of Sessionbased Recommendation AlgorithmsA**arXiv ID:** 1803.09587 **Authors:** Malte Ludewig, Dietmar Jannach **Published:** 2018-03-26T13:46:07Z **Abstract:** Recommender systems help users find relevant items of interest, for example on e-commerce or media streaming sites. Most academic research is concerned with approaches that personalize the recommendations according to long-term user profiles. In many real-world applications, however, such long-term profiles often do not exist and recommendations therefore have to be made sole...researchgoperformanceVotes: 0GitHub stars: 3
Domain Paper ResearchAConduct comprehensive domain-specific research paper discovery and compilation. Search across skills, Obsidian vault, and knowledge graph to find relevant papers, then compile into a structured collection with reading order, concept maps, and design decision matrices. Use when user asks for papers on a specific technical domain or wants to build a literature review for a project.researchpythongoVotes: 0GitHub stars: 3
Ddm Time Averaged Drift InconsistencyAProving time-averaged drift approximations are mathematically inconsistent for inference in Drift Diffusion Models (DDMs), with implications for computational neuroscience decision-making models. Activation: drift diffusion model, DDM, evidence accumulation, decision-making, time-varying drift, computational neuroscience, inconsistency, statistical inference.researchpythongoVotes: 0GitHub stars: 3
Autoresearch PipelineASkill for AI agent capabilitiesresearchpythongoVotes: 0GitHub stars: 3
Autoresearch Coding Agents Generalizers Metric Maximizers Quran Recitation DataASkill derived from arXiv:2607.18064 - Autoresearch with Coding Agents: Generalizers and Metric-Maximizers on Quran Recitation DataresearchVotes: 0GitHub stars: 3
Automated Research PipelineALightweight automated research pipeline for searching, filtering, and extracting skills from academic papers without knowledge graph infrastructure. Use for: quick research synthesis, paper-to-skill conversion, domain literature surveys. Activation: automated research, paper to skill, research pipeline, quick literature review, skill extraction from papers.researchpythongoVotes: 0GitHub stars: 3
Arxiv SearchCarXiv paper search skill - search academic papers by keywords, authors, categories. Supports time filtering, category filtering, and paper detail retrieval. Activation: arxiv search, paper search, 论文搜索, search papers, arxiv 论文.researchjavascriptpythonVotes: 0GitHub stars: 3
Arxiv 2608 05876v1 Personalized Deep Research Query Refinement With GA**arXiv ID:** 2608.05876v1 **Authors:** Soojin Yoon, Dongha Lee **URL:** http://arxiv.org/abs/2608.05876v1 **Utility Score:** 1.00researchVotes: 0GitHub stars: 3
Arxiv 2608 05876 Personalized Deep Research Query Refinement With GAPersonalized Deep Research Query Refinement with Graph-Scaffolded Evidence Grounding (arXiv: 2608.05876)researchVotes: 0GitHub stars: 3
Arxiv 2608 05545 Vibe Compiler A Research Logic Synthesis Tool ThatAVibe Compiler: A Research-Logic Synthesis Tool That Runs without Prompt Engineering -Toward Enhancing Metacognition for Sustaining Agency in the Age of Generative AI- (arXiv: 2608.05545)researchVotes: 0GitHub stars: 3
Data Driven Distributed ControlAData-driven distributed controller synthesis using spatial regret optimization. For synthesizing optimal distributed controllers directly from frequency-response data without requiring a parametric system model. Use when: (1) designing distributed control systems from experimental data, (2) comparing spatial regret vs H2/Hinf performance, (3) building data-driven controllers with communication structure constraints, (4) model-free controller synthesis for networked systems.researchperformanceVotes: 0GitHub stars: 3
Dart Q Realtime Qldpc DecodingADART-Q methodology for real-time quantum error correction decoding. Deadline-driven QLDPC decoder framework with queueing theory, EDF scheduling, and admission control for fault-tolerant quantum computing. Activation: real-time decoding, quantum decoder scheduling, QLDPC decoding, deadline-driven quantum, DART-Q.researchpythongoVotes: 0GitHub stars: 3
Cv Qnn Spatial ClassificationAContinuous-variable QNN advantage for spatial classification tasks. Controlled comparison showing CV-QNN outperforms DV-QNN by 18+ percentage points on wafer-map defect classification. CV structured layer captures fine spatial distinctions that DV misses. Use when designing QNNs for image/spatial classification, semiconductor yield, or any task requiring fine spatial pattern recognition.researchperformanceVotes: 0GitHub stars: 3
Cross Subject Eeg DecodingACross-Subject Generalization for EEG Decoding — comprehensive survey of deep learning methods addressing inter-subject variability in EEG-based BCI. Covers domain adaptation, meta-learning, data augmentation, Riemannian geometry, and subject-independent evaluation protocols. Activation: cross-subject EEG, EEG domain adaptation, BCI generalization, subject-independent EEG, EEG transfer learning.researchpythonrustVotes: 0GitHub stars: 3