Papers by Kellen Tan Cheng
Compact Language Models with Iterative Text Refinement for Health Dialogue Summarization (2026.eacl-long)
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| Challenge: | Health wellness agents typically rely on large language models (LLMs) for response generation, where contextual information from prior conversations can be utilized for response grounding and personalization. |
| Approach: | They propose to use large language models to generate high-quality health dialogue summaries by using iterative feedback. |
| Outcome: | The proposed method outperforms baseline on open-source and proprietary benchmarks and can run on local compute without a GPU. |