Evaluation & Benchmarks · 2023
Chatbot Arena / LLM-as-Judge (MT-Bench/AlpacaEval)
Introduced Chatbot Arena and MT-Bench, establishing crowd-sourced pairwise human voting and a strong-model-as-judge protocol as scalable ways to rank chat models on open-ended quality where fixed benchmarks fall short.
Editorial record
Plain-language summary
Chatbot Arena collects anonymous head-to-head comparisons: users chat with two unnamed models, vote for the better response, and the votes feed an Elo-style rating that ranks models. MT-Bench is a set of multi-turn questions scored by a strong model acting as an automated judge, which the paper validates against human preferences while also documenting judge biases such as favoring longer answers or the first response shown. Together they gave the field a way to evaluate conversational quality and instruction following that static multiple-choice benchmarks cannot capture.
Knowledge graph
Relationships
Antecedents
ChallengesEvidence: Direct
The Evaluation Crisis (contamination/saturation/judge-bias)
Judge bias feeds eval crisis
P-449
Source record
Provenance
- Record ID
- P-447
- Record created
- 2026-07-13
- Last reviewed
- 2026-07-14
- Record version
- 2
- https://arxiv.org/abs/2403.04132
- arXiv:2403.04132
Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.