Papers by Dimitris Papailiopoulos
Prompted LLMs as Chatbot Modules for Long Open-domain Conversation (2023.findings-acl)
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| Challenge: | Using pre-trained large language models (LLMs) as individual modules for long-term consistency and flexibility is a challenge for open-domain chatbots due to the computational burden of updating models with billions of parameters and the scarcity of data in the dialogue domain. |
| Approach: | They propose a method that uses pre-trained large language models as individual modules for long-term consistency and flexibility. |
| Outcome: | The proposed method is on par with fine-tuned chatbot models in open-domain conversations, showing it can create consistent and engaging chatbots. |
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment (2022.findings-emnlp)
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Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris Papailiopoulos, Kangwook Lee
| Challenge: | Recent studies show that unsupervised word translation is more accurate and robust without parallel corpora. |
| Approach: | They propose a method for unsupervised word translation that leverages visual observations and pretrained language-image models to align words. |
| Outcome: | The proposed method improves on the state-of-the-art language-image pretraining method for bilingual word alignment. |