Papers by Zhi-Yuan Xie
Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators (2021.acl-long)
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| Challenge: | Existing methods for pre-trained language models (PLMs) use parameter reduction techniques. |
| Approach: | They propose a pre-trained language model compression approach based on the matrix product operator from quantum many-body physics. |
| Outcome: | The proposed approach can decompose an original matrix into central tensors and auxiliary tenses . it can be applied to the original or compressed PLMs in a general way, with a lighter network . |
Towards Preference Following in Tool Calling Language Agents (2026.findings-acl)
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| Challenge: | Currently, large language model (LLM)-based agents can't follow user preferences when calling tools. |
| Approach: | They propose a benchmark to evaluate agents' ability to identify personalized user preferences from interaction histories and to adhere to these preferences when calling tools. |
| Outcome: | The proposed model achieves 51.16% accuracy on the APOLLO benchmark, while GPT-4o achieves only 51.13% accuracy. |