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Chenglu Li

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CY2
  • cs.CL1
ORCID 0000-0002-1782-0457

identity via Semantic Scholar / OpenAlex

most citedRetrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference

14 citations · 17 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CY2024★ 1 cited

Elementary School Students' and Teachers' Perceptions Towards Creative Mathematical Writing with Generative AI

Yukyeong Song, Jinhee Kim, Wanli Xing +3

While mathematical creative writing can potentially engage students in expressing mathematical ideas in an imaginative way, some elementary school-age students struggle in this pro…

cs.CY2024★ 2 cited

Students' Perceived Roles, Opportunities, and Challenges of a Generative AI-powered Teachable Agent: A Case of Middle School Math Class

Yukyeong Song, Jinhee Kim, Zifeng Liu +2

Ongoing advancements in Generative AI (GenAI) have boosted the potential of applying long-standing learning-by-teaching practices in the form of a teachable agent (TA). Despite the…

cs.CL2023★ 14 cited

Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference

Zachary Levonian, Chenglu Li, Wangda Zhu +4

For middle-school math students, interactive question-answering (QA) with tutors is an effective way to learn. The flexibility and emergent capabilities of generative large languag…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.