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Yi Chen

Yi Chen has 5 papers in our library, in 2023–2026, most of them on Reasoning, Language models & pretraining, Multilingual & cross-lingual NLP; often with Rui Wang, Boyang Xue, Hongru Wang.

5 papers in our library · 2023–2026

OpenAlex · h-index 0 · 4 works · 0 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 64 times in our library · ⭐ Paper Stars ranking: #6405

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

🎓New Jersey Institute of TechnologyNewark · United States2026 · 2 paperscurrent

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

 Fields, topics and concepts

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

📚 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 · 3 worksInformation Systems · 1 workSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 2 worksEvaluation & benchmarks · 1 workReasoning · 3 worksBias, fairness & safety · 1 workMultilingual & cross-lingual NLP · 1 work

 Works by year

2020s

20263 papers20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study (2023 · 113 citations)
    The paper asks whether large language models, mainly ChatGPT, can judge the quality of generated text without human-written references, and which way of prompting them works best.
  2. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models (2025 · 16 citations)
    Large Reasoning Models such as OpenAI o1, DeepSeek R1 and QwQ solve hard math and coding problems by producing long chains of thought.
  3. MR-ALIGN: Meta-Reasoning Informed Factuality Alignment for Large Reasoning Models (2026 · 2 citations)
    Large reasoning models (LRMs) handle multi-step problems well, but extended thinking adds little on fact-based questions.
  4. WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models (2026 · 1 citation)
    Deep Research agents need more than retrieval. They must combine scattered, heterogeneous evidence through multi-step reasoning. Existing training and evaluation resources mostly reward locating a single entity, so agents learn to call tools often instead of reasoning carefully.
  5. Multilingual Disparities in LLM-Based Safety Judgments: Evidence from Brand Safety Applications (2026)
    The paper tests a common assumption about multilingual LLM judges: that the same content gets the same verdict whatever its language. The authors study this in brand safety, where automated ratings decide whether advertisers place ads next to news. That decision affects publisher income and advertiser reputation.

 Co-authors here

12 of 29 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 64 times (of the 149,439 papers whose bibliographies we read); 20 citing papers with a page here →.

Updated

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