Jing Qian
Jing Qian has 2 papers in our library, in 2019–2022, most of them on Sentiment & emotion, Text generation, Evaluation & benchmarks; often with Anna Bethke, Elizabeth Belding, Furu Wei.
OpenAlex · ORCID · h-index 9 · 91 works · 342 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 256 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #3663
Affiliations
Concepts, shelves and topics
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksSocial Sciences · 1 workSociology and Political Science · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work
🧭 Topics 4Research subjects and languages the work is about.Text generation · 1 workBias, fairness & safety · 1 workEvaluation & benchmarks · 1 workSentiment & emotion · 1 work
Works by year
2020s
2010s
Papers
- A Benchmark Dataset for Learning to Intervene in Online Hate Speech (2019 · 292 citations)
Most NLP work on online hate speech stops at detection, and existing datasets usually label single posts with no surrounding discussion. - Controllable Natural Language Generation with Contrastive Prefixes (2022 · 128 citations)
The paper addresses steering a frozen GPT2 toward chosen text attributes, such as sentiment, topic or non-toxicity, without costly fine-tuning or slow decoding.
All works
- A Benchmark Dataset for Learning to Intervene in Online Hate SpeechConference on Empirical Methods in Natural Language Processing (EMNLP)Jing Qian, Anna Bethke, Yinyin Liu, et al.2019 · 292 citations
- Controllable Natural Language Generation with Contrastive PrefixesFindings of the Association for Computational LinguisticsJing Qian, Li Dong, Yelong Shen, et al.2022 · 128 citations
- Explanations from Large Language Models Make Small Reasoners Better ↗arXiv:2210.06726 · no summary yetShiyang Li et al.2022 · 119 citations
Co-authors here
Venues
- Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2019
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2022
Cited by
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