Papers with social interaction
SOTOPIA-π: Interactive Learning of Socially Intelligent Language Agents (2024.acl-long)
Copied to clipboard
Ruiyi Wang, Haofei Yu, Wenxin Zhang, Zhengyang Qi, Maarten Sap, Yonatan Bisk, Graham Neubig, Hao Zhu
| Challenge: | Existing studies on building language agents have not addressed this social learning gap. |
| Approach: | They propose an interactive learning method that improves the social intelligence of language agents by using behavior cloning and self-reinforcement based training on filtered social interaction data. |
| Outcome: | The proposed method allows a 7B LLM to reach the social goal completion ability of an expert model (GPT-4-based agent) without the loss of more generic abilities, such as the ability to answer knowledge-based questions. |
Simple Agents, Biased Judges: Efficient Multi-Party Dialogue Generation & The Evaluation Gap (2026.acl-long)
Copied to clipboard
| Challenge: | Multiparty social dialogue is difficult to formalize and expensive to evaluate, especially at scale. |
| Approach: | They propose a lightweight and controllable multi-party dialoguegeneration framework as an experimental instrument for studying generation and evaluation in social interaction. |
| Outcome: | The proposed framework shows that human judgments against state-of-the-art LLM judges are consistent with human preferences for naturalness, engagingness, and overall quality in multi-party social dialogue. |