Papers by Victor De Lima
YIELD: A Large-Scale Dataset and Evaluation Framework for Information Elicitation Agents (2026.acl-long)
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| Challenge: | Existing conversational agents (CAs) are designed to satisfy user needs through user-driven interactions. however, many real-world settings, such as academic interviewing, require agents that can elicit information from users. |
| Approach: | They propose to support Information Elicitation Agents (IEAs) in which the agent’s goal is to elicit information from users to support the agent's institutional or task-oriented objectives. |
| Outcome: | The proposed agent-based model improves the performance of a 26M-token dataset of 2,281 human-to-human dialogues on multiple foundation LLMs and human evaluation confirms the results. |