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Yunfei Li

ByteDance Seed

4 papers hereh-index 10313 citations20 works total

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

author position
  • first author3
  • middle author1

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

fields
  • cs.LG2
  • cs.RO2
affiliations
  • ByteDance Seed
same name
  • Yunfei Li — 2 papers
  • Yunfei Li — 1 paper
  • Yunfei Li — 1 paper
  • Yunfei Li — 1 paper
  • Yunfei Li — 1 paper
  • Yunfei Li — 1 paper

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

activity
20192022
most citedSolving Compositional Reinforcement Learning Problems via Task Reduction

8 citations · 11 across the 4 of their papers we have counts for

collaborators

4 papers

cs.RO2022

Learning Design and Construction with Varying-Sized Materials via Prioritized Memory Resets

Yunfei Li, Tao Kong, Lei Li +1

Can a robot autonomously learn to design and construct a bridge from varying-sized blocks without a blueprint? It is a challenging task with long horizon and sparse reward -- the r…

cs.RO2021

Learning to Design and Construct Bridge without Blueprint

Yunfei Li, Tao Kong, Lei Li +2

Autonomous assembly has been a desired functionality of many intelligent robot systems. We study a new challenging assembly task, designing and constructing a bridge without a blue…

cs.LG2021★ 8 cited

Solving Compositional Reinforcement Learning Problems via Task Reduction

Yunfei Li, Yilin Wu, Huazhe Xu +2

We propose a novel learning paradigm, Self-Imitation via Reduction (SIR), for solving compositional reinforcement learning problems. SIR is based on two core ideas: task reduction…

cs.LG2019★ 3 cited

Pretrain Soft Q-Learning with Imperfect Demonstrations

Xiaoqin Zhang, Yunfei Li, Huimin Ma +1

Pretraining reinforcement learning methods with demonstrations has been an important concept in the study of reinforcement learning since a large amount of computing power is spent…

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