Yankai Chen
Yankai Chen has 5 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning; often with Henry Peng Zou, Weizhi Zhang, Hanrong Zhang.
OpenAlex · ORCID · Wikidata · h-index 16 · 82 works · 1,009 citations OpenAlex, 2026-10-14
📄 5 works in our library · 🔗 Cited 26 times in our library · ⭐ Paper Stars ranking: #8153
Affiliations
Fields, topics and concepts
📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 5 worksComputer Science · 5 worksArtificial Intelligence · 5 worksLanguage and Linguistics · 5 worksComputer Vision and Pattern Recognition · 2 worksInformation Systems · 1 workBusiness, Management and Accounting · 1 workManagement Information Systems · 1 work
🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 2 works
Works by year
2020s
Papers
- Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs (2025 · 17 citations)
Large language models face two linked weaknesses. Their stored knowledge is fixed and can be wrong, and they struggle with problems that need several reasoning steps. Retrieval-Augmented Generation (RAG) addresses the first, and reasoning techniques such as Chain-of-Thought address the second. This survey argues that… - LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey (2026 · 12 citations)
Fully autonomous LLM agents remain hard to trust in practice. They hallucinate, especially across chained actions. They also falter on long, expertise-heavy tasks and raise safety, bias and accountability concerns in areas such as finance or healthcare. This survey argues for keeping people in the loop and gives what… - GAM: Hierarchical Graph-based Agentic Memory for LLM Agents (2026 · 5 citations)
LLM agents in long conversations must absorb new information without letting passing chatter corrupt what they already know. - FinReporting: An Agentic Workflow for Localized Reporting of Cross-Jurisdiction Financial Disclosure (2026 · 3 citations)
Most LLM tools that extract and condense corporate financial statements are built for one market. They assume a single accounting taxonomy and filing format, which fails investors studying foreign firms. Across markets, similarly named line items can differ in meaning, equivalent concepts can carry different labels… - LightReasoner: Can Small Language Models Teach Large Language Models Reasoning? (2026 · 1 citation)
Standard supervised fine-tuning for reasoning is expensive. It typically uses rejection sampling against ground-truth answers and then updates every token equally, even though most tokens are routine. LightReasoner addresses this by letting a weaker "Amateur" model help train a stronger "Expert" model. At each step…
Co-authors here
- Henry Peng Zou ×3
- Weizhi Zhang ×3
- Hanrong Zhang ×2
- Wei-Chieh Huang ×2
- Yaozu Wu ×2
- Chao Huang
- Chunkit Chan
- Chunyu Miao
- Fan Zhang
- Georgi Nenkov Georgiev
- Hoang H Nguyen
- Hongwei Wang
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026 ×3
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
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