Jiaxin Qin — accepted AI-conference papers

2024

Why Does New Knowledge Create Messy Ripple Effects in LLMs?

Jiaxin Qin, Zixuan Zhang, Chi Han, Pengfei Yu, Manling Li, Heng Ji

EMNLP 2024main

Extensive previous research has focused on post-training knowledge editing (KE) for language models (LMs) to ensure that knowledge remains accurate and up-to-date. One desired property and open question in KE is to let edited LMs correctly handle ripple effects, where LM is expected to answer its lo…

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2023

H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation

Yanjie Ze, Yuyao Liu, Ruizhe Shi, Jiaxin Qin, Zhecheng Yuan, Jiashun Wang +1

NeurIPS 2023poster

Human hands possess remarkable dexterity and have long served as a source of inspiration for robotic manipulation. In this work, we propose a human $\textbf{H}$and-$\textbf{In}$formed visual representation learning framework to solve difficult $\textbf{Dex}$terous manipulation tasks ($\textbf{H-InDe…

Cited by 21 Source ↗PDF ↗Scholar ↗