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Jingwei Cheng

Jingwei Cheng has 4 papers in our library, in 2025–2026, most of them on Language models & pretraining, Knowledge graphs & ontologies, Vision & language; often with Fu Zhang, Jiashun Peng, Xiaoke Wang.

4 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 14 · 111 works · 881 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 5 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #10477

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

🎓Northeastern UniversityShenyang · China2007–2026 · 96 papersEducation 2007–2011 · Dr., College of Computer Science and Engineeringcurrent🎓Northeastern UniversityBoston · United States2008–2026 · 10 paperscurrent🏢Hefei General Machinery Research InstituteHefei · China2025 · 2 papers
🏛️Northeatern UniversityShenyang · China2011Employment since 2011 · Lecturer, College of Computer Science and Engineering

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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).Artificial Intelligence · 4 worksComputer Science · 4 worksArts and Humanities · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 2 worksVision & language · 2 worksKnowledge graphs & ontologies · 2 worksInformation extraction · 1 workReasoning · 1 work

 Works by year

2020s

20263 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. RRHF-V: Ranking Responses to Mitigate Hallucinations in Multimodal Large Language Models with Human Feedback (2025 · 5 citations)
    Multimodal large language models (MLLMs) often hallucinate, describing objects, colours, counts or positions that are not in the image.
  2. Critic Rule Induction: Improving Temporal Knowledge Graph Forecasting with Generator-Critic Language Models (2026)
    The paper addresses forecasting future events in temporal knowledge graphs (TKGs) using explicit logical rules.
  3. From Local Perspective to Global Reasoning: A Neuro-Symbolic Framework for Zero-Shot Relation Extraction (2026)
    Zero-Shot Relation Extraction (ZSRE) requires labelling entity pairs in sentences with relations never seen during training.
  4. Not All Modalities at Once: Dynamic Dropout and Bidirectional Fusion for Robust Multi-modal Knowledge Graph Completion (2026)
    Multi-modal knowledge graph completion (MKGC) predicts missing entities in triples by combining graph structure with entity descriptions and images.

All works

6 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. RRHF-V: Ranking Responses to Mitigate Hallucinations in Multimodal Large Language Models with Human FeedbackInternational Conference on Computational Linguistics (COLING)Guoqing Chen, Fu Zhang, Jinghao Lin, et al.2025 · 5 citations
  2. Critic Rule Induction: Improving Temporal Knowledge Graph Forecasting with Generator-Critic Language ModelsFindings of the Association for Computational LinguisticsYingsong Ning, Fu Zhang, Jingwei Cheng, et al.2026
  3. From Local Perspective to Global Reasoning: A Neuro-Symbolic Framework for Zero-Shot Relation ExtractionFindings of the Association for Computational LinguisticsKailun Lyu, Fu Zhang, Zehan Li, et al.2026
  4. Not All Modalities at Once: Dynamic Dropout and Bidirectional Fusion for Robust Multi-modal Knowledge Graph CompletionFindings of the Association for Computational LinguisticsJiashun Peng, Fu Zhang, Hongzhi Chen, et al.2026
  5. ATGL: An Adaptive-Threshold Global Loss for Document-level Relation Extraction ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetHuangming Xu et al.2026
  6. DEBAR: Mitigating Contextual Bias in Cross-Document Relation Extraction via Dual-Stream Decoupling ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetZhixuan Yang et al.2026

 Co-authors here

6 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 5 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

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