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Dayong Wu

Dayong Wu has 2 papers in our library, in 2025, most of them on Language models & pretraining, Question answering, Knowledge graphs & ontologies; often with Baoxin Wang, Bing Qin, Guoping Hu.

2 papers in our library · 2025

OpenAlex · ORCID · h-index 23 · 66 works · 2,262 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 89 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #8688

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

🏛️Chinese Academy of SciencesBeijing · China2001–2026 · 50 paperscurrent🔬Technical Institute of Physics and ChemistryBeijing · China2001–2026 · 44 paperscurrent🏢IFlyTekHefei · China2019–2023 · 5 papers🎓Harbin Institute of TechnologyHarbin · China2010–2020 · 3 papers🎓Hebei University of Science and TechnologyShijiazhuang · China2024–2025 · 2 papers🔬Institute of Computing TechnologyBeijing · China2014–2018 · 2 papers
🏛️?????????????? · ChinaEmployment

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 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.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 2 worksInformation retrieval & search · 1 workKnowledge graphs & ontologies · 1 workQuestion answering · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Ontology engineering · 1 work

 Works by year

2020s

20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering (2025 · 15 citations)
    Approaches that couple large language models with knowledge graphs for question answering (KGQA) typically locate relevant facts through entity embeddings and graph search.
  2. Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization (2025 · 11 citations)
    The paper addresses faithfulness hallucination in retrieval-augmented long-form question answering (LFQA), where a model writes paragraph-length answers containing claims that the retrieved documents do not support or that contradict them.

All works

6 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. NeurJudge: A Circumstance-aware Neural Framework for Legal Judgment Prediction ↗International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · no summary yetLinan Yue et al.2021 · 134 citations
  2. Dynamic Connected Networks for Chinese Spelling Check ↗Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 · no summary yetBaoxin Wang et al.2021 · 73 citations
  3. Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Runxuan Liu, Bei Luo, Jiaqi Li, et al.2025 · 15 citations
  4. IFlyLegal: A Chinese Legal System for Consultation, Law Searching, and Document Analysis ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations · no summary yetZiyue Wang et al.2019 · 12 citations
  5. Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Huang, Xiaocheng Feng, Weitao Ma, et al.2025 · 11 citations
  6. Question Tells You Where the Answer Is: Intention-aware Long-Context KV Cache Compression ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetLiang Zhao et al.2026

 Co-authors here

12 of 14 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 89 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

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