Papers by Bill Cai
Interactive Text Generation (2023.emnlp-main)
Copied to clipboard
Felix Faltings, Michel Galley, Kianté Brantley, Baolin Peng, Weixin Cai, Yizhe Zhang, Jianfeng Gao, Bill Dolan
| Challenge: | Advances in generative modeling have made it possible to automatically generate high-quality texts, code, and images, but they can be unsatisfactory in many respects. |
| Approach: | They propose a task that allows training generation models interactively without the costs of involving real users. |
| Outcome: | The proposed model trains with Imitation Learning without the cost of involving real users and is superior to non-interactive models. |
Low-Cost Generation and Evaluation of Dictionary Example Sentences (2024.naacl-long)
Copied to clipboard
| Challenge: | Prior studies have shown that language models can be trained to generate example sentences, but they relied on costly customized models and word sense datasets for generation and evaluation. |
| Approach: | They propose a new automatic evaluation metric called OxfordEval that measures the win-rate of generated sentences against existing Oxford Dictionary sentences. |
| Outcome: | The proposed model achieves over 85.1% win rate against baseline sentences compared to 39.8% win rate for prior model-generated sentences. |