Papers by Yilun Hua
Success and Cost Elicit Convention Formation for Efficient Communication (2026.acl-long)
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| Challenge: | ad hoc conventions allow people to coordinate on short, less costly utterances that are understood using shared conversational context. |
| Approach: | They propose a method to train large multimodal models to form conventions . they use simulated reference games to produce training data . |
| Outcome: | The proposed method reduces message length by up to 41% while increasing success by 15% over the course of the interaction. |
Improving Long Dialogue Summarization with Semantic Graph Representation (2023.findings-acl)
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| Challenge: | Existing algorithms for abstractive summarization of short dialogues are challenging . however, they can generate high-quality summaries for long dialogues . |
| Approach: | They propose an algorithm that processes complete dialogues into topic-segment-level Abstract Meaning Representation graphs . they propose a pretrained LLM that exploits the text to leverage graph semantics a new text-graph attention . |
| Outcome: | The proposed algorithm outperforms state-of-the-art models on multiple long dialogue summarization datasets . it also generates additional training signals that facilitate graph feature encoding and content selection. |
How did we get here? Summarizing conversation dynamics (2024.naacl-long)
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Yilun Hua, Nicholas Chernogor, Yuzhe Gu, Seoyeon Jeong, Miranda Luo, Cristian Danescu-Niculescu-Mizil
| Challenge: | Throughout a conversation, the way participants interact with each other is in constant flux. |
| Approach: | They propose to summarize conversations by constructing human-written summaries and exploring automated baselines. |
| Outcome: | The summarizing tools help both humans and automated systems forecast toxic behavior in conversations. |