Papers by Benjamin Yao
Joint Goal Segmentation and Goal Success Prediction on Multi-Domain Conversations (2022.coling-1)
Copied to clipboard
| Challenge: | Existing metrics to measure the performance of conversational AI assistants are difficult to establish due to their slow nature. |
| Approach: | They propose an automatic dialogue evaluation framework that performs goal segmentation and success prediction by adding multi-task learning heads. |
| Outcome: | The proposed model achieves on-par with human annotation compared to a gold annotation benchmark. |
KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Pre-trained language models (PLMs) have shown their superiority by pre-training on unstructured text corpus and then fine-tuning on downstream tasks. |
| Approach: | They propose a Knowledge-Enhanced Pre-trained LanguagE model with Topic entity awareness that incorporates the interactions between tokens and mentioned entities in pre-training. |
| Outcome: | The proposed model incorporates the interactions between tokens and mentioned entities in pre-training and is more effective on entity-centric tasks. |
Improving Summarization with Human Edits (2023.emnlp-main)
Copied to clipboard
| Challenge: | Existing studies have shown the promise of learning with human feedback paradigms to produce human-determined high-quality text. |
| Approach: | They propose a novel technique to use both human-edited and model-generated data together in the training loop. |
| Outcome: | The proposed technique outperforms the conventional RLHF method (designed for human preferences) when applied to human-edit data. |