Lu Chen
Lu Chen has 4 papers in our library, in 2018–2024, most of them on Language models & pretraining, Dialogue systems, Evaluation & benchmarks; often with Kai Yu, Kaige Xie, Qin Liu.
OpenAlex · ORCID · h-index 54 · 661 works · 10,841 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 268 times in our library · ⭐ Paper Stars ranking: #3094
Affiliations
Concepts, shelves and topics
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksComputer Vision and Pattern Recognition · 1 workHistory and Philosophy of Science · 1 workInformation Systems · 1 work
🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 2 worksDialogue systems · 1 workCode & programming languages · 1 workSemantic parsing & meaning representation · 1 workEvaluation & benchmarks · 1 work
Works by year
2020s
2010s
Papers
- LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations (2021 · 191 citations)
Text-to-SQL systems must jointly encode a natural-language question and a database schema of tables and columns, which form a heterogeneous graph. - Towards Universal Dialogue State Tracking (2018 · 191 citations)
The paper tackles dialogue state tracking (DST), which means estimating a user's goal as slot-value pairs at each turn of a task-oriented spoken dialogue. - Secrets of RLHF in Large Language Models Part I: PPO (2023 · 130 citations)
RLHF is the main way to make LLMs helpful, honest and harmless. Its PPO stage, though, is unstable, sensitive to hyperparameters and costly to debug, and few open implementations existed. This report from the Fudan NLP Group and ByteDance breaks the RLHF pipeline into its stages: SFT, reward model training, and PPO… - Is LLM a Reliable Reviewer? A Comprehensive Evaluation of LLM on Automatic Paper Reviewing Tasks (2024 · 73 citations)
The paper asks whether large language models can be trusted as automatic peer reviewers, a question earlier review datasets did not answer well because they did not verify that generated reviews were correct.
Co-authors here
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2021
- Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2018
- Language Resources and Evaluation Conference (LREC): LREC 2024
Cited by
Updated
This page in Markdown → https://md.research.elamur.ai/free/en/authors/lu-chen/