태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
A task where an algorithm should generate the judgment scores correlating with human judgments.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
This dataset contains 3.3K expert-level pairwise human preferences for model responses generated by 6 models in response to 80 MT-bench questions. The 6 models are GPT-4, GPT-3.5, Claud-v1, Vicuna-13B, Alpaca-13B, and LLaMA-13B. The annotators are mostly graduate students with expertise in the topic areas of each of the questions.
The AlpacaEval set contains 805 instructions form self-instruct, open-assistant, vicuna, koala, hh-rlhf. Those were selected so that the AlpacaEval ranking of models on the AlpacaEval set would be similar to the ranking on the Alpaca demo data.
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.