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Jiawei Sheng

Jiawei Sheng has 3 papers in our library, in 2025–2026, most of them on Reasoning; often with Tingwen Liu, Wenyuan Zhang, Haifeng Wang.

3 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 13 · 54 works · 776 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 61 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #9873

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

🔬Institute of Information EngineeringBeijing · China2020–2026 · 47 paperscurrent🏛️Chinese Academy of SciencesBeijing · China2020–2026 · 45 paperscurrent🎓University of Chinese Academy of SciencesBeijing · China2020–2026 · 21 paperscurrent🎓Beihang UniversityBeijing · China2024–2025 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 1Research subjects and languages the work is about.Reasoning · 1 work

 Works by year

2020s

20261 paper20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking (2025 · 16 citations)
    Larger LLMs bring diminishing returns, and small models hit capacity limits. Chain-of-Thought style test-time scaling also has a weakness: it only works if the model produces the critical tokens correctly. The authors trained GPT-2 on AQuA and tracked gradient norms layer by layer. Tokens the model gets right settle…
  2. Improving Reasoning Capabilities in Small Models through Mixture-of-layers Distillation with Stepwise Attention on Key Information (2025 · 10 citations)
    Small language models are cheaper to deploy than large ones but reason less well. Chain-of-Thought (CoT) distillation usually just trains them on teacher-written rationales, with every token weighted the same. The authors observe that teacher models such as Llama3-8B shift their attention from step to step toward the…
  3. HyperMem: Hypergraph Memory for Long-Term Conversations (2026)
    Conversational agents need memory that persists across long dialogues, but their context windows are fixed.

All works

5 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. Adaptive Attentional Network for Few-Shot Knowledge Graph Completion ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetJiawei Sheng et al.2020 · 147 citations
  2. CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction ↗Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 · no summary yetJiawei Sheng et al.2021 · 96 citations
  3. Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal ThinkingAnnual Meeting of the Association for Computational Linguistics (ACL)Yilong Chen, Junyuan Shang, Zhenyu Zhang, et al.2025 · 16 citations
  4. Improving Reasoning Capabilities in Small Models through Mixture-of-layers Distillation with Stepwise Attention on Key InformationConference on Empirical Methods in Natural Language Processing (EMNLP)Yao Chen, Jiawei Sheng, Wenyuan Zhang, et al.2025 · 10 citations
  5. HyperMem: Hypergraph Memory for Long-Term ConversationsAnnual Meeting of the Association for Computational Linguistics (ACL)Juwei Yue, Chuanrui Hu, Jiawei Sheng, et al.2026

 Co-authors here

11 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 61 times (of the 149,439 papers whose bibliographies we read); 16 citing papers with a page here →.

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