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Tianjian Li

Tianjian Li has 2 papers in our library, in 2025, most of them on Multilingual & cross-lingual NLP, Code & programming languages; often with Daniel Khashabi, David R. Mortensen, David Yarowsky.

2 papers in our library · 2025

OpenAlex · h-index 2 · 14 works · 13 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 20 times in our library · ⭐ Paper Stars ranking: #8830

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

🎓Johns Hopkins UniversityBaltimore · United States2022–2025 · 13 paperscurrent🎓University of Notre DameNotre Dame · United States2024–2025 · 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 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 2Research subjects and languages the work is about.Code & programming languages · 1 workMultilingual & cross-lingual NLP · 1 work

 Works by year

2020s

20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Benchmarking Language Model Creativity: A Case Study on Code Generation (2025 · 17 citations)
    Most studies of LLM creativity focus on open-ended tasks such as story writing. This leaves open how creative models are when they solve problems. Two things have been missing: a way to push models beyond repetitive outputs, and a grounded, quantitative metric. Drawing on cognitive science, the authors treat…
  2. The Translation Barrier Hypothesis: Multilingual Generation with Large Language Models Suffers from Implicit Translation Failure (2025 · 7 citations)
    LLMs often generate poorly in mid- and low-resource languages, but the reasons are unclear. The authors argue that generation inside the model runs as an implicit two-stage process. Middle layers first work out the answer concept in a way largely independent of the target language. Final layers then render that…

 Co-authors here

10 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 20 times (of the 149,439 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated

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