{"adoption": {"forks": 188, "observed_at": "2026-08-28T04:04:24.398241+00:00", "stars": 1332}, "canonical_url": "https://ross.abutalabs.com/products/nlp-paper", "card": {"archived": false, "artifact_type": "learning-resource", "description": "自然语言处理领域下的相关论文（附阅读笔记），复现模型以及数据处理等（代码含TensorFlow和PyTorch两版本）", "domain": ["machine-learning", "deep-learning", "speech-processing", "tutorials", "awesome-lists"], "enriched": true, "function": ["nlp", "machine-learning", "deep-learning", "speech-recognition", "tts", "search-engine"], "health_score": 20, "homepage": null, "language": "Python", "license": "Apache-2.0", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["DengBoCong/nlp-paper"], "name": "DengBoCong/nlp-paper", "platform": ["python", "cross-platform"], "pushed_at": "2024-01-05T06:50:56+00:00", "repo": "DengBoCong/nlp-paper", "stars": 1332, "tags": ["paper-reading-notes", "nlp-papers", "bert", "dialogue-systems", "tensorflow", "pytorch", "paper-reproduction", "chinese", "natural-language-processing"], "topics": ["dialogue", "speech", "nlp-machine-learning", "paper", "tensorflow2", "pytorch", "nlp", "bert"], "urls": [], "use_cases": ["find nlp papers to read", "learn nlp with reading notes", "reproduce nlp model papers in pytorch or tensorflow", "study dialogue system papers", "find bert and pretraining papers", "search a curated nlp paper list", "learn speech recognition and synthesis research"], "what_it_is": "A curated collection of NLP research papers organized by topic and date, with author-written reading notes for classic and novel papers. It includes Python code reproducing models and data processing in both TensorFlow and PyTorch, plus a search tool for finding papers.", "when_to_avoid": ["you need a production-ready NLP library or framework", "you need maintained, tested model implementations rather than study code", "you need papers outside NLP and speech domains"], "when_to_choose": ["you want a curated, categorized NLP paper reading list with notes", "you want reference implementations of NLP models in both TensorFlow and PyTorch", "you are studying dialogue systems, text similarity, or speech topics"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/nlp-paper", "repo": "DengBoCong/nlp-paper", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:04:24.398241+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T04:44:56.459120+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "907bbfcd08c1e8eed22f7274ae3effc0e8de9d1c578478d61978a943ed0789e0", "fetched_at": "2026-08-28T04:04:24.398241+00:00", "kind": "readme", "missing": false, "url": "https://github.com/DengBoCong/nlp-paper"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2188, "days_push": 971, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 32, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}