deep-researchlisted

# deep-research A benchmark task that exercises an agent's deep web-research loop: starting from partial author hints and a vague topic description, locate the exact target paper and emit a structured answer. This is one of the SkillsBench tasks I wrote. The original — including the full sandbox environment, scripts, solution, and verifier — lives at [BenchFlow-Hub/galaxies-bingran/tasks/deep-research](https://github.com/BenchFlow-Hub/galaxies-bingran/tree/main/tasks/deep-research). What you'll find here is the **instruction** and the **task config** — the parts that define what the agent has to do. ## Instruction > Find a paper published before 06/2024. This paper is about quantum > networks and fast ion string transportation and second-order > correlation functions. For the 2 first authors, one of them has gotten > PhD degree in NYU and become postdoc of UC Berkeley. And another > finished undergraduate study in China. > > Put answer to `/root/final_answer.md` as a markdown file. It has 4 > lines: > > 1. The complete title of the paper > 2. The DOI of the paper (only DOI string, no prefix) > 3. The DOI of the first co-author (only DOI string, no prefix) > 4. The DOI of the second co-author (only DOI string, no prefix) ## Task config ```toml version = "1.0" [metadata] author_name = "Bingran You" author_email = "bingran.you@berkeley.edu" difficulty = "medium" category = "deep-research" tags = ["web-search", "deep-research"] [verifier] timeout_sec = 900.0 [agent] time