Papers by Richard He Bai
Training Bilingual LMs with Data Constraints in the Targeted Language (2025.findings-acl)
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| Challenge: | a large number of languages have insufficient data for pretraining, but most non-English models are trained on scrapes of the web. |
| Approach: | They propose to use data from an auxiliary language to boost model performance . they quantify the performance gap between training with data in a data-rich auxiliary and training in the target language . |
| Outcome: | The proposed method boosts model performance in a target language with insufficient data . it also explores the benefits of translation systems and the limitations of model scaling when data is limited. |
From Past To Path: Masked History Learning for Next-Item Prediction in Generative Recommendation (2026.acl-long)
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Kaiwen Wei, Kejun he, Xiaomian Kang, Jie Zhang, null Ymyang, Li Jin, Zhenyang Li, Jiang Zhong, Richard He Bai, Junnan Zhu
| Challenge: | Generative recommendation models inherently bias towards local contexts, failing to capture deeper historical dependencies necessary for understanding complex user intents. |
| Approach: | They propose a training framework that shifts the objective from simple next-step prediction to deep comprehension of history by entropy-guided masking policy and a curriculum learning scheduler to enhance the framework. |
| Outcome: | The proposed framework outperforms state-of-the-art generative models on three public datasets and shows that it is more accurate than current models. |