🧑‍🔬 Tong Yu

🏛️ Affiliations

🏢Adobe SystemsSan Jose · United States2021–2026 · 63 paperscurrent🎓Anhui Jianzhu UniversityHefei · China2023–2026 · 2 paperscurrent🎓Carnegie Mellon UniversityPittsburgh · United States2016–2023 · 15 papers🎓Norwegian University of Science and TechnologyTrondheim · Norway2022–2024 · 5 papers🎓Hunan Police AcademyChangsha · China2008–2017 · 3 papers🎓PLA Information Engineering UniversityZhengzhou · China2023–2025 · 2 papers🏢SamsungSeoul · South Korea2020 · 2 papers🎓National Taiwan UniversityTaipei · Taiwan2013–2015 · 2 papers🎓Nanjing UniversityNanjing · China2011–2012 · 2 papers🎓Zhejiang UniversityHangzhou · China2008–2009 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 20 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Bias and Fairness in Large Language Models: A Survey (2023 · 1,082 citations)
   Large language models learn from enormous, mostly uncurated web text. Along the way they absorb social biases and can even amplify them: stereotypes, toxic or exclusionary wording, and weak handling of some dialects. These harms fall hardest on groups that are already marginalized. This survey, accepted at…
2. From Selection to Generation: A Survey of LLM-based Active Learning (2025 · 22 citations)
   Active learning (AL) traditionally lowers labeling effort by picking the most useful unlabeled examples with metrics such as uncertainty or diversity.
3. Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs (2025 · 19 citations)
   Chain-of-Thought (CoT) prompting showed that LLMs reason better when they write out intermediate steps before giving an answer.
4. Doc-React: Multi-page Heterogeneous Document Question-answering (2025 · 6 citations)
   Doc-React tackles question answering over long documents whose pages mix text, charts and images in irregular layouts.
5. Embedding-Informed Adaptive Retrieval-Augmented Generation of Large Language Models (2025 · 5 citations)
   Retrieval-augmented LLMs do not always benefit from external documents. When a model already knows the answer, retrieval adds cost and latency and can even hurt quality. Adaptive RAG (ARAG) tries to retrieve only when needed. Earlier ARAG methods either count entity frequencies in the pre-training corpus, which is…
6. Skill Discovery for Software Scripting Automation via Offline Simulations with LLMs (2026 · 3 citations)
   The paper addresses how to make software scripting accessible to users who lack programming skills or knowledge of an application's API.
7. CachePrune: Teaching LLMs What Not to Follow via KV-Cache Editing (2026)
   The paper addresses indirect prompt injection, where an LLM obeys commands hidden inside supplied context (e.g., a retrieved passage) instead of answering the user's actual request.

All works

10 works of theirs in our library, the most cited first; 7 with a page here, the others link their original until we summarise them.

1. Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,082 citations
2. Towards Language-Free Training for Text-to-Image Generation ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetYufan Zhou et al.2022 · 216 citations
3. EI-CLIP: Entity-aware Interventional Contrastive Learning for E-commerce Cross-modal Retrieval ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetHaoyu Ma et al.2022 · 63 citations
4. Personalization of Large Language Models: A Survey ↗arXiv (Cornell University) · no summary yetZhehao Zhang et al.2024 · 61 citations
5. From Selection to Generation: A Survey of LLM-based Active LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie, et al.2025 · 22 citations
6. Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMsInternational Conference on Computational Linguistics (COLING)Yu Xia, Rui Wang, Xu Liu, et al.2025 · 19 citations
7. Doc-React: Multi-page Heterogeneous Document Question-answeringAnnual Meeting of the Association for Computational Linguistics (ACL)Junda Wu, Yu Xia, Tong Yu, et al.2025 · 6 citations
8. Embedding-Informed Adaptive Retrieval-Augmented Generation of Large Language ModelsInternational Conference on Computational Linguistics (COLING)Chengkai Huang, Yu Xia, Rui Wang, et al.2025 · 5 citations
9. Skill Discovery for Software Scripting Automation via Offline Simulations with LLMsFindings of the Association for Computational LinguisticsPaiheng Xu, Gang Wu, Xiang Chen, et al.2026 · 3 citations
10. CachePrune: Teaching LLMs What Not to Follow via KV-Cache EditingAnnual Meeting of the Association for Computational Linguistics (ACL)Rui Wang, Junda Wu, Yu Xia, et al.2026

🤝 Co-authors here

12 of 27 co-authors with a page, the most papers together first.

• Yu Xia ×5
• Julian McAuley ×4
• Franck Dernoncourt ×3
• Junda Wu ×3
• Rui Wang ×3
• Ruiyi Zhang ×3
• Ryan A. Rossi ×3
• Xiang Chen ×3
• Joe Barrow ×2
• Lina Yao ×2
• Sungchul Kim ×2
• Branislav Kveton

Venues

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

• Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026, ACL 2025 ×2
• International Conference on Computational Linguistics (COLING) ×2: COLING 2025 ×2
• IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings ×2
• Computational Linguistics: Computational Linguistics 2023
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026

🔗 Cited by

Papers of our library cite their works 490 times (of the 149,439 papers whose bibliographies we read); 105 citing papers with a page here →.

Updated 1 November 2026

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/tong-yu/