LMR-BENCH at EMNLP 2025 tests whether LLM agents can reproduce real LLM research
ZhiyuChen4 · x · 2026-10-16
LMR-BENCH, a benchmark from UT Dallas accepted to EMNLP 2025, tackles a foundational question behind the current recursive self-improvement (RSI) boom: can LLM agents understand and reproduce real LLM research?
- Setup: the agent receives an NLP paper plus a repository with key code masked, and must implement the target function based on the paper.
- Evaluation combines unit tests, an LLM judge, and human judges.
- It joins recent RSI-focused initiatives like Scale AI Labs' RSI Bench and OpenRSI.
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