Papers by Yiwei Lou
EVIT: Event-Oriented Instruction Tuning for Event Reasoning (2024.findings-acl)
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| Challenge: | Large language models (LLMs) have made significant advances in event reasoning . however, smaller instruction-tuned models do not consistently demonstrate exceptional proficiency . |
| Approach: | They propose an event-oriented instruction tuning technique to train a large language model . they propose a structure named event quadruple which contains the structure and semantics of events . |
| Outcome: | The proposed model achieves competitive performances on event reasoning tasks. |
DatawiseAgent: A Notebook-Centric LLM Agent Framework for Adaptive and Robust Data Science Automation (2025.emnlp-main)
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| Challenge: | Existing large language model (LLM) agents for data science automation are limited by narrow task scopes, limited generalization across tasks and models, and over-reliance on state-of-the-art (SOTA) LLMs. |
| Approach: | They propose a notebook-centric LLM agent framework for adaptive and robust data science automation. |
| Outcome: | The proposed framework surpasses baselines such as AutoGen and TaskWeaver in performance tests across diverse data science scenarios and models. |