These are publications and preprint/unpublished manuscripts I am involved in. Note: This may not be a complete list. You can find my up-to-date papers on my Google Scholar.

* indicates equal contribution.

2025

• Yun Zhu, Jia-Chen Gu, Caitlin Sikora, Ho Ko, Yinxiao Liu, Chu-Cheng Lin, Lei Shu, Liangchen Luo, Lei Meng, Bang Liu, Jindong Chen. Accelerating Inference of Retrieval-Augmented Generation via Sparse Context Selection. To appear in Proc. of ICLR 2025, Singapore. [arXiv] [bib] [open review]

2024

• Zihan Wang, Yunxuan Li, Yuexin Wu, Liangchen Luo, Le Hou, Hongkun Yu, Jingbo Shang. Multi-Step Problem Solving Through a Verifier: An Empirical Analysis on Model-Induced Process Supervision. In Findings of EMNLP 2024, Miami, Florida, US. [arXiv] [bib]
• Lei Shu, Nevan Wichers, Liangchen Luo, Yun Zhu, Yinxiao Liu, Jindong Chen, Lei Meng. Fusion-Eval: Integrating Assistant Evaluators with LLMs. In Proc. of EMNLP (Industry Track) 2024, Miami, Florida, US. [arXiv] [bib]
• Yun Zhu, Yinxiao Liu, Felix Stahlberg, Shankar Kumar, Yu-hui Chen, Liangchen Luo, Lei Shu, Renjie Liu, Jindong Chen, Lei Meng. Towards an On-Device Agent for Text Rewriting. In Findings of NAACL 2024, Mexico City, Mexico. [arXiv] [bib]
• Liangchen Luo*, Yinxiao Liu*, Rosanne Liu, Samrat Phatale, Harsh Lara, Yunxuan Li, Lei Shu, Yun Zhu, Lei Meng, Jiao Sun, Abhinav Rastogi. Improve Mathematical Reasoning in Language Models by Automated Process Supervision. arXiv preprint. [arXiv] [bib]
• Lei Shu, Liangchen Luo, Yun Zhu, Yinxiao Liu, Simon Tong, Jindong Chen, Lei Meng. RewriteLM: An Instruction-Tuned Large Language Model for Text Rewriting. In Proc. of AAAI 2024, Vancouver, Canada. [arXiv] [bib] [code]

2023

• Yun Zhu, Nevan Wichers, Chu-Cheng Lin, Xinyi Wang, Tianlong Chen, Lei Shu, Han Lu, Canoee Liu, Liangchen Luo, Jindong Chen, Lei Meng. SiRA: Sparse Mixture of Low Rank Adaptation. arXiv preprint. [arXiv] [bib]
• Liangchen Luo, Zi Lin, Yinxiao Liu, Lei Shu, Yun Zhu, Jingbo Shang, Lei Meng. Critique Ability of Large Language Models. arXiv preprint. [arXiv] [bib]

2021

• Marco Fornoni, Chaochao Yan, Liangchen Luo, Kimberly Wilber, Alex Stark, Yin Cui, Boqing Gong, Andrew Howard. Bridging the Gap Between Object Detection and User Intent via Query-Modulation. arXiv preprint. [arXiv] [bib]

2020

• Liangchen Luo, Mark Sandler, Zi Lin, Andrey Zhmoginov, Andrew Howard. Large-Scale Generative Data-Free Distillation. arXiv preprint. [arXiv] [bib]
• Mark Sandler, Andrey Zhmoginov, Liangchen Luo, Alexander Mordvintsev, Ettore Randazzo, Blaise Agúera y Arcas. Image Segmentation via Cellular Automata. arXiv preprint. [arXiv] [bib]

2019

• Guangxiang Zhao, Xu Sun, Jingjing Xu, Zhiyuan Zhang, Liangchen Luo. MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning. arXiv preprint. [arXiv] [bib] [code]
• Liangchen Luo*, Yuanhao Xiong*, Yan Liu, Xu Sun. Adaptive Gradient Methods with Dynamic Bound of Learning Rate. In Proc. of ICLR 2019, New Orleans, Louisiana. [arXiv] [bib] [code] [open review] [poster] [slides]
• Liangchen Luo, Wenhao Huang, Qi Zeng, Zaiqing Nie, Xu Sun. Learning Personalized End-to-End Goal-Oriented Dialog. In Proc. of AAAI 2019, Honolulu, Hawaii. [arXiv] [bib] [poster]
• Qi Zeng*, Liangchen Luo*, Wenhao Huang, Yang Tang. Text Assisted Insight Ranking Using Context-Aware Memory Network. In Proc. of AAAI 2019, Honolulu, Hawaii. [arXiv] [bib] [poster]

2018

• Liangchen Luo*, Jingjing Xu*, Junyang Lin, Qi Zeng, Xu Sun. An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation. In Proc. of EMNLP 2018, Brussels, Belgium. [arXiv] [bib] [code] [poster]