Papers by Sanketh Rangreji
Long-Horizon Dialogue Understanding for Role Identification in the Game of Avalon with Large Language Models (2023.findings-emnlp)
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Simon Stepputtis, Joseph Campbell, Yaqi Xie, Zhengyang Qi, Wenxin Zhang, Ruiyi Wang, Sanketh Rangreji, Charles Lewis, Katia Sycara
| Challenge: | Deception and persuasion play a critical role in long-horizon multi-party dialogues, especially when the interests, goals, and motivations of the participants are not aligned. |
| Approach: | They propose a game in which players must determine each other’s hidden identities to complete their team’s objective. |
| Outcome: | The proposed model can be used to determine the true player identities of six human players in a cooperative-competitive game. |
AI-LieDar : Examine the Trade-off Between Utility and Truthfulness in LLM Agents (2025.naacl-long)
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| Challenge: | LieDar is a framework to study how LLM-based agents navigate these scenarios in a multi-turn interactive setting. |
| Approach: | They propose a framework to study how LLM-based agents navigate these scenarios in an interactive multi-turn setting. |
| Outcome: | The proposed framework shows that all models are truthful less than 50% of the time, although truthfulness and goal achievement rates vary across models. |
Program-Aided Reasoners (Better) Know What They Know (2024.naacl-long)
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| Challenge: | Prior work shows that program-aided reasoning improves accuracy but also requires reasoners to "know what they know". |
| Approach: | They compare the calibration of program-aided language models (PAL) and text-based Chain-of-thought (COT) prompting techniques over 5 datasets and 2 model types . |
| Outcome: | The proposed methods improve accuracy and calibrate the models over 5 datasets and 2 model types. |