Papers by Lele Cao
Thread: A Logic-Based Data Organization Paradigm for How-To Question Answering with Retrieval Augmented Generation (2025.emnlp-main)
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Kaikai An, Fangkai Yang, Liqun Li, Junting Lu, Sitao Cheng, Shuzheng Si, Lu Wang, Pu Zhao, Lele Cao, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Baobao Chang
| Challenge: | Recent advances in retrieval-augmented generation (RAG) have substantially improved question-answering systems, particularly for factoid ‘5Ws’ questions. |
| Approach: | They propose a data organization paradigm where large language models transform documents into more structured and loosely interconnected LUs. |
| Outcome: | Experiments in open-domain and industrial settings show that the proposed paradigm outperforms existing paradigms and shows high adaptability across diverse document formats. |
PAUSE: Positive and Annealed Unlabeled Sentence Embedding (2021.emnlp-main)
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Lele Cao, Emil Larsson, Vilhelm von Ehrenheim, Dhiana Deva Cavalcanti Rocha, Anna Martin, Sonja Horn
| Challenge: | Sentence embedding is a set of effective and versatile techniques for converting raw text into numerical vector representations. |
| Approach: | They propose a generic and end-to-end approach to embed sentences from a partially labeled dataset using supervised methods. |
| Outcome: | The proposed approach achieves state-of-the-art results using only a small fraction of labeled sentence pairs on various benchmark tasks. |