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Pei Ke

Pei Ke has 5 papers in our library, in 2020–2024, most of them on Language models & pretraining, Bias, fairness & safety; often with Minlie Huang, Bosi Wen, Hongning Wang.

5 papers in our library · 2020–2024

OpenAlex · ORCID · h-index 15 · 47 works · 1,007 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 435 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #3457

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of Electronic Science and Technology of ChinaChengdu · China2025–2026 · 6 paperscurrent🎓Tsinghua UniversityBeijing · China2018–2024 · 33 papers🔬Beijing National Research Center for Information Science and TechnologyBeijing · China2018–2023 · 15 papers🔬State Key Laboratory of Intelligent Technology and SystemsBeijing2019–2023 · 13 papers🔬Viện Trí tuệ nhân tạoHanoi · Vietnam2019–2023 · 7 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 5 worksComputer Science · 5 worksArtificial Intelligence · 5 worksLanguage and Linguistics · 5 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 4 worksBias, fairness & safety · 2 works

 Works by year

2020s

20241 paperDefending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization20233 papersPei Ke's papers of 202320201 paperCPM: A Large-scale Generative Chinese Pre-trained Language Model

 Papers

The most cited first (OpenAlex and our library).

  1. CPM: A Large-scale Generative Chinese Pre-trained Language Model (2020 · 149 citations)
    GPT-3 demonstrated strong few-shot and zero-shot abilities, but it is of limited use for Chinese because its training data is overwhelmingly English and its weights are closed.
  2. Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization (2024 · 112 citations)
    The paper argues that jailbreaking attacks on LLMs succeed because models are tuned for two competing objectives, helpfulness and safety, without being told which one wins when they clash.
  3. AlignBench: Benchmarking Chinese Alignment of Large Language Models (2023 · 73 citations)
    Chinese benchmarks such as C-Eval and CMMLU score exam-style knowledge. They do not show whether an instruction-tuned model handles real user requests well. LLM-as-Judge suites like AlpacaEval and MT-Bench, meanwhile, exist only in English. AlignBench fills this gap with 683 Chinese queries taken mostly from an…
  4. Unveiling the Implicit Toxicity in Large Language Models (2023 · 71 citations)
    Most red-teaming work on large language models looks for overtly abusive outputs, which standard toxicity detectors catch easily.
  5. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation (2023 · 68 citations)
    LLM-based evaluators trained on critiques that GPT-4 produces through direct prompting often give vague, generic judgments. The problem is worst when no reference answer is available. This paper presents Eval-Instruct, a pipeline for building more informative training data for critique generation.

All works

9 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

  1. CPM: A Large-scale Generative Chinese Pre-trained Language ModelZhengyan Zhang, Xu Han, Hao Zhou, et al.AI Open · 149 citations
  2. JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs · original ↗ · no summary yet · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021Pei Ke et al.2021 · 131 citations
  3. Defending Large Language Models Against Jailbreaking Attacks Through Goal PrioritizationZhexin Zhang, Junxiao Yang, Pei Ke, et al.Annual Meeting of the Association for Computational Linguistics (ACL) · 112 citations
  4. CPM-2: Large-scale Cost-effective Pre-trained Language Models · original ↗ · no summary yet · arXiv:2106.10715Zhengyan Zhang et al.2021 · 102 citations
  5. AlignBench: Benchmarking Chinese Alignment of Large Language ModelsXiao Liu, Xuanyu Lei, Shengyuan Wang, et al.arXiv:2311.18743 · 73 citations
  6. Unveiling the Implicit Toxicity in Large Language ModelsJiaxin Wen, Pei Ke, Hao Sun, et al.Conference on Empirical Methods in Natural Language Processing (EMNLP) · 71 citations
  7. Black-Box Prompt Optimization: Aligning Large Language Models without Model Training · original ↗ · no summary yet · Proceedings of the 62nd Annual Meeting of the Association for Computational…Jiale Cheng et al.2024 · 70 citations
  8. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model GenerationPei Ke, Bosi Wen, Zhuoer Feng, et al.arXiv:2311.18702 · 68 citations
  9. Click: Controllable Text Generation with Sequence Likelihood Contrastive Learning · original ↗ · no summary yet · Findings of the Association for Computational Linguistics: ACL 2023Chujie Zheng et al.2023 · 28 citations

 Co-authors here

12 of 29 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 435 times (of the 141,840 papers whose bibliographies we read); 39 citing papers with a page here →.

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