# Find a paper's implementation and follow-up work Given a single paper title or arxiv id, walk three sources in one chain to find the canonical reference, follow-up citations, and any community-fine-tuned models or Spaces that already build on it. ## What I wanted I read a paper abstract, decide it is interesting, and want to answer three questions before deciding to actually re-read the paper or reproduce it: 1. Has anyone already implemented or fine-tuned on top of it (Hugging Face)? 2. Who has cited or extended it (dblp / OpenReview)? 3. What is the canonical bibliographic record (dblp key for citation, full arxiv metadata for reading)? Doing this in a browser means three tabs and two minutes of context-switching. The point is to compress that into one shell pipeline. ## Commands Worked example: "Direct Preference Optimization" (DPO). ```bash # 1. Canonical arxiv record (full abstract, authors, pdf url, categories). # Note: arxiv free-text search ranks by recency, so the original DPO # paper does not always come back first. When the canonical id is # already known, hit `arxiv paper ` directly. opencli arxiv search "Direct Preference Optimization" --limit 5 -f json opencli arxiv paper 2305.18290 -f json # 2. dblp bibliography record + co-authors + venue history opencli dblp search "Direct Preference Optimization" --limit 5 -f json # 3. Community uptake on Hugging Face: trending Daily Papers that mention DPO opencli hf top --period monthly --limit 50 -f json | jq '.[] | select(.title | test("DPO|preference"; "i"))' # 4. Conference review record (if posted to OpenReview) opencli openreview search "Direct Preference Optimization" --limit 5 -f json ``` Three of the four are public-strategy adapters, no browser session needed. The OpenReview call also lands without auth for public venues. ## What I do with the output For DPO the chain produces: - arxiv record: paper id `2305.18290`, full abstract, pdf link. - dblp record: canonical key `conf/nips/RafailovSMMEF23`, NeurIPS 2023, co-author list (useful to find related work by same lab). - HF Daily Papers (last 30 days): every paper whose title mentions DPO or preference. Each one is a candidate "follow-up work I should know about". - OpenReview: the original submission's review thread, if posted (lets me see what reviewers actually pushed back on, which is more useful than the published abstract). I dump all four JSON outputs into a single LLM call with the prompt: *"Build a one-paragraph 'state of the field' summary for this paper as of today. Cite each follow-up by arxiv id."* That gives me a research-debt brief in 30 seconds. ## Why this is worth a CLI chain - Each adapter alone is just "search a website". The value is the chain. Four `opencli` calls feed into one LLM call. No browser, no copy-paste. - Output is identifier-rich (arxiv id, dblp key, venue id, HF paper id). I can re-feed any of those into the next call, e.g. once I find a follow-up arxiv id from HF Daily Papers I run `opencli arxiv paper ` immediately. - Survives use inside an agent loop. Same chain runs unattended for a batch of 20 papers from a reading list. - Zero token cost for the discovery half. Only the final summary step pays for inference. Without `opencli dblp search` (added in #1299) and `opencli openreview search` (added in #1294), this whole pipeline used to require either web scraping in agent code or paying for a research-paper API. Both adapters being public-strategy means they slot in cleanly.