Papers by Yanze Wang
Should I Trust You? Detecting Deception in Negotiations using Counterfactual RL (2025.findings-acl)
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Wichayaporn Wongkamjan, Yanze Wang, Feng Gu, Denis Peskoff, Jonathan K. Kummerfeld, Jonathan May, Jordan Lee Boyd-Graber
| Challenge: | Future human-AI interaction tools can build on our methods for deception detection by triggering friction to give users a chance to interrogate suspicious proposals. |
| Approach: | They propose to use CTRL-D to detect deception in a board game called Diplomacy . CTRL is a counterfactual RL that has a good recall and almost perfect precision . future tools could build on this to reevaluate trust in suspicious negotiations . |
| Outcome: | The proposed method detects human deception with a high precision when compared to a Large Language Model approach that flags many true messages as deceptive. |
More Victories, Less Cooperation: Assessing Cicero’s Diplomacy Play (2024.acl-long)
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Wichayaporn Wongkamjan, Feng Gu, Yanze Wang, Ulf Hermjakob, Jonathan May, Brandon Stewart, Jonathan Kummerfeld, Denis Peskoff, Jordan Boyd-Graber
| Challenge: | Diplomacy is a boardgame that offers a challenge for communicative and cooperative AI. |
| Approach: | They run two dozen games with Cicero and annotate in-game communication with abstract meaning representation to separate in- game tactics from general language. |
| Outcome: | The proposed method can outperform Cicero in communicating with humans, but it's difficult to deceive and persuade AI. |