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Benjamin Liu
de0cee191c
* docs(cases): add three researcher workflow examples Add use cases under cases/ that exercise the recently-landed researcher-friendly adapters: - daily-rl-research-monitor.md uses arxiv recent + openreview venue + hf top to compress a morning paper-skim into one shell pipeline. - find-paper-implementation.md chains arxiv search/paper + dblp search + hf top + openreview search to map a paper's canonical record, follow-ups, and community uptake. - track-conference-papers.md walks openreview venue + reviews to shortlist accepted papers and digest review threads in batch. Each file is a real workflow built on commands from #1289 (arxiv recent), #1294 (openreview), and #1299 (dblp). * docs(cases): correct venue ids and forum example to ones that return data The first revision used "ICLR.cc/2026/Conference" and "ICLR 2026 oral" as venue strings. Both return EMPTY_RESULT today because the venue is not open. Update each case to use natural-language venue text that OpenReview currently exposes ("ICLR 2024 oral", "NeurIPS 2025 oral") and a real forum id (KS8mIvetg2, "Proving Test Set Contamination in Black-Box Language Models") in the reviews / paper drill-down. Note the arxiv free-text-search ranking quirk so the worked DPO example makes sense.
58 lines
3.4 KiB
Markdown
58 lines
3.4 KiB
Markdown
# Find a paper's implementation and follow-up work
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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.
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## What I wanted
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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:
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1. Has anyone already implemented or fine-tuned on top of it (Hugging Face)?
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2. Who has cited or extended it (dblp / OpenReview)?
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3. What is the canonical bibliographic record (dblp key for citation, full arxiv metadata for reading)?
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Doing this in a browser means three tabs and two minutes of context-switching. The point is to compress that into one shell pipeline.
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## Commands
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Worked example: "Direct Preference Optimization" (DPO).
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```bash
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# 1. Canonical arxiv record (full abstract, authors, pdf url, categories).
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# Note: arxiv free-text search ranks by recency, so the original DPO
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# paper does not always come back first. When the canonical id is
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# already known, hit `arxiv paper <id>` directly.
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opencli arxiv search "Direct Preference Optimization" --limit 5 -f json
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opencli arxiv paper 2305.18290 -f json
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# 2. dblp bibliography record + co-authors + venue history
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opencli dblp search "Direct Preference Optimization" --limit 5 -f json
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# 3. Community uptake on Hugging Face: trending Daily Papers that mention DPO
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opencli hf top --period monthly --limit 50 -f json | jq '.[] | select(.title | test("DPO|preference"; "i"))'
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# 4. Conference review record (if posted to OpenReview)
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opencli openreview search "Direct Preference Optimization" --limit 5 -f json
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```
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Three of the four are public-strategy adapters, no browser session needed. The OpenReview call also lands without auth for public venues.
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## What I do with the output
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For DPO the chain produces:
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- arxiv record: paper id `2305.18290`, full abstract, pdf link.
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- dblp record: canonical key `conf/nips/RafailovSMMEF23`, NeurIPS 2023, co-author list (useful to find related work by same lab).
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- 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".
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- 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).
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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.
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## Why this is worth a CLI chain
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- 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.
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- 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 <new-id>` immediately.
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- Survives use inside an agent loop. Same chain runs unattended for a batch of 20 papers from a reading list.
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- Zero token cost for the discovery half. Only the final summary step pays for inference.
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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.
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