How to evaluate when you don’t know how to evaluate? Choosing reliable setups for base language model benchmarking
Read the original at arxiv.org→arXiv:2610.19185v1 Announce Type: new Abstract: Evaluation of large language models (LLMs) remains largely pre-scientific: it involves many design decisions, with little guidance on how to make them. These choices...
Original headline: "How to Evaluate When You Don't Know How to Evaluate? Choosing Reliable Setups for Base Language Model Benchmarking"
Coverage timeline
- Oct 15, 04:00 UTC arXiv cs.CL lead source How to Evaluate When You Don't Know How to Evaluate? Choosing Reliable Setups for Base Language Model Benchmarking