Papers with user-centered conversation agents
Towards LLM-powered Attentive Listener: A Pragmatic Approach through Quantity Self-Repair (2025.acl-short)
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| Challenge: | Quantity Maxims dictates that human speakers aim for optimal quantity of information during conversation. |
| Approach: | They propose to use heuristic path-finding to enable decoder-only LLMs to travel among multiple "Q-alternatives" and search for optimal quantity in coordination with a conversation goal. |
| Outcome: | The proposed techniques are based on heuristic path-finding and can be used to construct human-like, user-centered conversation agents. |