engineering
awesome-loop-engineering
Awesome Loop Engineering Dataset
A structured dataset of 1025 papers, official docs, tools, benchmarks, patterns, critiques, and implementation guides for recurring AI-agent systems.
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Dataset Summary
Each row connects an original source to its contribution, novelty, impact, publication details, lifecycle stages, audience, evidence type, link status, and… See the full description on the dataset page: https://huggingface.co/datasets/cy0307/awesome-loop-engineering.engineering-docsprompt-engineering-papersAudio-Video-Engineering-Agentic-Tasks-1M
Audio/Video Engineering Agentic Tasks (1M)
Abstract
A highly specialized dataset comprising 1,029,459 in-context troubleshooting prompts and execution commands built for the deepest levels of media production. Unlike standard datasets that simulate clean, theoretical instructions, this matrix captures the chaotic, highly-detailed, and conversational reality of professional audio engineers, composers, and video editors mid-session. It is engineered to train multimodal AI… See the full description on the dataset page: https://huggingface.co/datasets/yatin-superintelligence/Audio-Video-Engineering-Agentic-Tasks-1M.ontolearner-materials_science_and_engineering
Materials Science And Engineering Domain Ontologies
Overview
Materials Science and Engineering is a multidisciplinary domain that focuses on the study and application of materials, emphasizing their structure, properties, processing, and performance in engineering contexts. This field is pivotal for advancing knowledge representation, as it integrates principles from physics, chemistry, and engineering to innovate and optimize materials for diverse technological… See the full description on the dataset page: https://huggingface.co/datasets/SciKnowOrg/ontolearner-materials_science_and_engineering.prompt-engineering-guide-papers\
