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Yuchen Li

4 papers hereh-index 221 citations6 works total

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

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.CL1
  • cs.LG1
  • cs.NE1
same name
  • Yuchen Li — 12 papers, h 5
  • Yuchen Li — 11 papers, h 25
  • Yuchen Li — 8 papers, h 3
  • Yuchen Li — 7 papers
  • Yuchen Li — 7 papers, h 12
  • Yuchen Li — 5 papers, h 13

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedExpanding Horizons of Level Diversity via Multi-objective Evolutionary Learning

2 citations · 2 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2025★ 2 cited

Expanding Horizons of Level Diversity via Multi-objective Evolutionary Learning

Qingquan Zhang, Ziqi Wang, Yuchen Li +3

In recent years, the generation of diverse game levels has gained increasing interest, contributing to a richer and more engaging gaming experience. A number of level diversity met…

cs.CL2025

Ethical Considerations of Large Language Models in Game Playing

Qingquan Zhang, Yuchen Li, Bo Yuan +3

Large language models (LLMs) have demonstrated tremendous potential in game playing, while little attention has been paid to their ethical implications in those contexts. This work…

cs.AI2025

GVGAI-LLM: Evaluating Large Language Model Agents with Infinite Games

Yuchen Li, Cong Lin, Muhammad Umair Nasir +3

We introduce GVGAI-LLM, a video game benchmark for evaluating the reasoning and problem-solving capabilities of large language models (LLMs). Built on the General Video Game AI fra…

cs.NE2024

Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation

Qingquan Zhang, Yuchen Li, Yuhang Lin +2

This paper presents an interactive platform to interpret multi-objective evolutionary algorithms. Sokoban level generation is selected as a showcase for its widespread use in proce…

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