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researcher

Xuelong Li

25 papers hereh-index 9323 citations27 works total

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

author position
  • middle author4
  • last author20

Across the 24 of 25 papers where every author was matched, so the position is known.

fields
  • cs.RO18
  • cs.LG4
  • cs.AI1
  • cs.CL1
  • cs.IT1
same name
  • Xuelong Li — 74 papers, h 135
  • Xuelong Li — 42 papers, h 21
  • Xuelong Li — 19 papers, h 9
  • Xuelong Li — 19 papers, h 5
  • Xuelong Li — 18 papers, h 4
  • Xuelong Li — 16 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

activity
20242026
most citedTowards Efficient LLM Grounding for Embodied Multi-Agent Collaboration

1 citations · 1 across the 22 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2025

Online Preference Alignment for Language Models via Count-based Exploration

Chenjia Bai, Yang Zhang, Shuang Qiu +3

Reinforcement Learning from Human Feedback (RLHF) has shown great potential in fine-tuning Large Language Models (LLMs) to align with human preferences. Existing methods perform pr…

cs.LG2024

Constrained Ensemble Exploration for Unsupervised Skill Discovery

Chenjia Bai, Rushuai Yang, Qiaosheng Zhang +4

Unsupervised Reinforcement Learning (RL) provides a promising paradigm for learning useful behaviors via reward-free per-training. Existing methods for unsupervised RL mainly condu…

cs.LG2024

Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning

Xiaoyu Wen, Chenjia Bai, Kang Xu +4

Cross-domain offline reinforcement learning leverages source domain data with diverse transition dynamics to alleviate the data requirement for the target domain. However, simply m…

cs.LG2024

Regularized Conditional Diffusion Model for Multi-Task Preference Alignment

Xudong Yu, Chenjia Bai, Haoran He +2

Sequential decision-making is desired to align with human intents and exhibit versatility across various tasks. Previous methods formulate it as a conditional generation process, u…

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