Binghuai Lin

Evaluation & Benchmarks · 2023

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Evaluation & Benchmarks — 14 citations into it
• Natural Language Processing — 12 citations into it

Whom Binghuai Lin trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Chin-Yew Lin (in Evaluation & Benchmarks)
2. M. McHugh (in Evaluation & Benchmarks)

Papers from Binghuai Lin's perspective

Ordered by how strongly the researchers Binghuai Lin trusts endorse each paper. Same corpus, a different order for every researcher.

1. Bleu: a Method for Automatic Evaluation of Machine Translation
2. Training language models to follow instructions with human feedback (Neural Information Processing Systems)
3. Chain of Thought Prompting Elicits Reasoning in Large Language Models (Neural Information Processing Systems)
4. Training Verifiers to Solve Math Word Problems
5. ROUGE: A Package for Automatic Evaluation of Summaries
6. Scaling Instruction-Finetuned Language Models (Journal of machine learning research)
7. GPT-4 Technical Report
8. Self-Consistency Improves Chain of Thought Reasoning in Language Models
9. The Pile: An 800GB Dataset of Diverse Text for Language Modeling
10. PaLM 2 Technical Report

Their papers

• Large Language Models are not Fair Evaluators (2023) — 1,116 citations
• Making Large Language Models Better Reasoners with Alignment (2023) — 91 citations