Richard He Bai

Richard He Bai

Research Scientist at Apple MLR, focused on building efficient and scalable foundation models for sequence modeling, with methods that improve applications across various domains including coding, RAG, recommendation, and cross-modal joint modeling.

I completed my PhD in Computer Science at the University of Waterloo, with a dissertation titled "Novel Methods for Natural Language Modeling and Pretraining", under the supervision of Professor Ming Li. Prior to my doctoral studies, I obtained a Master's degree from the Chinese Academy of Sciences, where I began my NLP research journey under the mentorship of Professor Chengqing Zong.

2026
New Paper

Embarrassingly Simple Self-Distillation Improves Code Generation

Ruixiang Zhang*, Richard He Bai*, Huangjie Zheng*, Navdeep Jaitly, Ronan Collobert, Yizhe Zhang*

Preprint, 2026

*equal contribution

2026
New Paper

CLaRa: Bridging Retrieval and Generation with Continuous Latent Reasoning

Jie He, Richard He Bai, Sinead Williamson, Jeff Z. Pan, Navdeep Jaitly, Yizhe Zhang

Preprint, 2025

2026
New Paper

From Past To Path: Masked History Learning for Next-Item Prediction in Generative Recommendation

Kaiwen Wei, Kejun He, Xiaomian Kang, Jie Zhang, Yuming Yang, Li Jin, Zhenyang Li, Jiang Zhong, Richard He Bai, Junnan Zhu

ACL 2026

2026
New Paper

Closing the Gap Between Text and Speech Understanding in LLMs

Santiago Cuervo, Skyler Seto, Maureen de Seyssel, Richard He Bai, Zijin Gu, Tatiana Likhomanenko, Navdeep Jaitly, Zakaria Aldeneh

ICLR 2026

2025
New Paper

ChipChat: Low-Latency Cascaded Conversational Agent in MLX

Tatiana Likhomanenko*, Luke Carlson*, Richard He Bai*, Zijin Gu*, Han Tran*, Zakaria Aldeneh*, Yizhe Zhang, Ruixiang Zhang, Huangjie Zheng, Navdeep Jaitly

IEEE ASRU 2025 (Best Demo)

*equal contribution

2025
Service

Workshop Organizer: WideningNLP at EMNLP 2025

2025
Service

Workshop Organizer: VLM4RWD at NeurIPS 2025

2025
Service

Workshop Organizer: Embodied AI Workshop at CVPR 2025

2024
New Paper

Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Pratyush Maini, Skyler Seto, Richard He Bai, David Grangier, Yizhe Zhang, Navdeep Jaitly

ACL 2024

2024
New Paper

Divide-or-Conquer? Which Part Should You Distill Your LLM?

Zhuofeng Wu, Richard He Bai, Aonan Zhang, Jiatao Gu, V.G. Vydiswaran, Navdeep Jaitly, Yizhe Zhang

EMNLP 2024

2024
New Paper

How Far Are We from Intelligent Visual Deductive Reasoning?

Y Zhang*, Richard He Bai*, R Zhang*, J Gu, S Zhai, J Susskind, N Jaitly

COLM 2024

*equal contribution

2024
New Paper

Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation

Ali Mousavi*, Xin Zhan*, Richard He Bai*, Peng Shi, Theo Rekatsinas, Benjamin Han, Yunyao Li, Jeff Pound, Josh Susskind, Natalie Schluter, Ihab Ilyas, Navdeep Jaitly

COLING 2024

*equal contribution

2024
New Paper

KGLens: Towards Efficient and Effective Knowledge Probing of Large Language Models with Knowledge Graphs

Shangshang Zheng*, Richard He Bai*, Yizhe Zhang, Yi Su, Xiaochuan Niu, Navdeep Jaitly

ACL 2024 Workshop (KnowLLM)

*equal contribution

2024
Service

Workshop Organizer: Embodied AI Workshop at CVPR 2024

2023
Career

Joined Apple MLR as Machine Learning Researcher

2023
Career

PhD Defense at the University of Waterloo

Dissertation: Novel Methods for Natural Language Modeling and Pretraining

2022
New Paper

XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic Parsing

Peng Shi, Rui Zhang, Richard He Bai, Jimmy Lin

Findings of EMNLP 2022

2022
New Paper

A3T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editing

Richard He Bai*, Renjie Zheng*, Junkun Chen, Mingbo Ma, Xintong Li, Liang Huang

ICML 2022 (spotlight)

*equal contribution

2022
New Paper

Better Language Model with Hypernym Class Prediction

Richard He Bai, Tong Wang, Alessandro Sordoni, Peng Shi

ACL 2022

2022
Award

Outstanding Reviewer Award at ICML 2022

2024
Service

Area Chair for ACL Rolling Review

2021
New Paper

Segatron: Segment-aware Transformer for Language Modeling and Understanding

Richard He Bai, Peng Shi, Jimmy Lin, Yuqing Xie, Luchen Tan, Kun Xiong, Wen Gao, Ming Li

AAAI 2021

2021
New Paper

Cross-Lingual Training with Dense Retrieval for Document Retrieval

Peng Shi, Rui Zhang, Richard He Bai, Jimmy Lin

Preprint, 2021

2021
New Paper

Semantics of the Unwritten: The Effect of End of Paragraph and Sequence Tokens on Text Generation

Richard He Bai, Peng Shi, Jimmy Lin, Luchen Tan, Kun Xiong, Wen Gao, Jie Liu, Ming Li

ACL 2021

2019
New Paper

Memory Consolidation for Contextual Spoken Language Understanding with Dialogue Logistic Inference

Richard He Bai, Yu Zhou, Jiajun Zhang, Chengqing Zong

ACL 2019