Evaluation & Benchmarks · 2023

Chatbot Arena / LLM-as-Judge (MT-Bench/AlpacaEval)

Lianmin Zheng, Wei-Lin Chiang, Ion Stoica, Xuechen Li, Yann Dubois, Tatsunori B. Hashimoto

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

Source record

Provenance

Record ID
P-447
Record created
2026-07-13
Last reviewed
2026-07-14
Record version
2

Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.