CORE-Bench
Harbor: pendingEvaluate how well an LLM Agent is at computationally reproducing the results of a set of scientific papers.
- Samples
- 45
- Released
- 2024
- Scores
- 0
CORE-Bench (EMNLP 2026) Evaluation Code: https://github.
$ npm i -g lettokenburn-cli$ ltb bench info core-bench-hf-bench
External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.
Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs
No sourced scores recorded yet.
Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.
CORE-Bench (EMNLP 2026)
Evaluation Code: https://github.com/zhangfw123/CORE-Bench-Eval CORE-Bench is a benchmark for code retrieval in agentic coding settings. It frames retrieval as requirement-driven repository search: given an issue, feature request, refactoring request, or other development query, a retriever must find the code and repository context needed by a coding agent. The paper defines three evaluation levels:
Level-1: Code Understanding evaluates traditional…