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Qi Zhu

12 papers hereh-index 5129 citations15 works total

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

author position
  • middle author4
  • last author7

Across the 11 of 12 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.AI2
  • cs.CR1
  • cs.CV1
  • cs.RO1
same name
  • Qi Zhu — 17 papers, h 16
  • Qi Zhu — 16 papers, h 9
  • Qi Zhu — 13 papers, h 19
  • Qi Zhu — 11 papers, h 11
  • Qi Zhu — 11 papers, h 14
  • Qi Zhu — 10 papers, h 10

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
20232026
most citedEmpowering Autonomous Driving with Large Language Models: A Safety Perspective

7 citations · 8 across the 12 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

Inverse Delayed Reinforcement Learning

Simon Sinong Zhan, Qingyuan Wu, Zhian Ruan +6

Inverse Reinforcement Learning (IRL) has demonstrated effectiveness in a variety of imitation tasks. In this paper, we introduce an IRL framework designed to extract rewarding feat…

cs.LG2024

Enhancing Inverse Reinforcement Learning through Encoding Dynamic Information in Reward Shaping

Simon Sinong Zhan, Philip Wang, Qingyuan Wu +4

In this paper, we aim to tackle the limitation of the Adversarial Inverse Reinforcement Learning (AIRL) method in stochastic environments where theoretical results cannot hold and…

cs.CR2024★ 1 cited

Can We Trust Embodied Agents? Exploring Backdoor Attacks against Embodied LLM-based Decision-Making Systems

Ruochen Jiao, Shaoyuan Xie, Justin Yue +5

Large Language Models (LLMs) have shown significant promise in real-world decision-making tasks for embodied artificial intelligence, especially when fine-tuned to leverage their i…

cs.LG2024

Variational Delayed Policy Optimization

Qingyuan Wu, Simon Sinong Zhan, Yixuan Wang +5

In environments with delayed observation, state augmentation by including actions within the delay window is adopted to retrieve Markovian property to enable reinforcement learning…

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