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Sanketh Rangreji

3 accepted papers

2025

AI-LieDar : Examine the Trade-off Between Utility and Truthfulness in LLM Agents

NAACL 2025long

Truthfulness (adherence to factual accuracy) and utility (satisfying human needs and instructions) are both fundamental aspects of Large Language Models, yet these goals often conflict (e.g., sell a car with known flaws), making it challenging to achieve both in real-world deployments. We propose AI…

2024

Program-Aided Reasoners (Better) Know What They Know

NAACL 2024long

Prior work shows that program-aided reasoning, in which large language models (LLMs) are combined with programs written in programming languages such as Python, can significantly improve accuracy on various reasoning tasks. However, while accuracy is essential, it is also important for such reasoner…

2023

Long-Horizon Dialogue Understanding for Role Identification in the Game of Avalon with Large Language Models

EMNLP 2023long findings

Deception and persuasion play a critical role in long-horizon dialogues between multiple parties, especially when the interests, goals, and motivations of the participants are not aligned. Such complex tasks pose challenges for current Large Language Models (LLM) as deception and persuasion can easi…

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