4 citations · 6 across the 9 of their papers we have counts for
8 papers · 1 filter
Learning to Persuade Exposes How Easily LLMs Abandon Correct Beliefs
Nimet Beyza Bozdag, Emre Can Acikgoz, Gokhan Tur +1
Persuasion is a core dynamic of natural language communication, shaping how large language models (LLMs) update beliefs, resolve disagreements, and reach decisions. As LLMs increas…
Too Polite to Disagree: Understanding Sycophancy Propagation in Multi-Agent Systems
Vira Kasprova, Amruta Parulekar, Abdulrahman AlRabah +5
Large language models (LLMs) often exhibit sycophancy: agreement with user stance even when it conflicts with the model's opinion. While prior work has mostly studied this in singl…
DialDefer: A Framework for Detecting and Mitigating LLM Dialogic Deference
Parisa Rabbani, Priyam Sahoo, Ruben Mathew +4
LLMs are increasingly used as third-party judges, yet their reliability when evaluating speakers in dialogue remains poorly understood. We show that LLMs judge identical claims dif…
From Fact to Judgment: Investigating the Impact of Task Framing on LLM Conviction in Dialogue Systems
Parisa Rabbani, Nimet Beyza Bozdag, Dilek Hakkani-Tür
LLMs are increasingly employed as judges across a variety of tasks, including those involving everyday social interactions. Yet, it remains unclear whether such LLM-judges can reli…
Language Specific Knowledge: Do Models Know Better in X than in English?
Ishika Agarwal, Nimet Beyza Bozdag, Nisval Patel +1
Often, multilingual language models are trained with the objective to map semantically similar content (in different languages) in the same latent space. In this paper, we show a n…
Must Read: A Comprehensive Survey of Computational Persuasion
Nimet Beyza Bozdag, Shuhaib Mehri, Xiaocheng Yang +7
Persuasion is a fundamental aspect of communication, influencing decision-making across diverse contexts, from everyday conversations to high-stakes scenarios such as politics, mar…
AURA: A Diagnostic Framework for Tracking User Satisfaction of Interactive Planning Agents
Takyoung Kim, Janvijay Singh, Shuhaib Mehri +6
The growing capabilities of large language models (LLMs) in instruction-following and context-understanding lead to the era of agents with numerous applications. Among these, task…
Persuade Me if You Can: A Framework for Evaluating Persuasion Effectiveness and Susceptibility Among Large Language Models
Nimet Beyza Bozdag, Shuhaib Mehri, Gokhan Tur +1
Large Language Models (LLMs) demonstrate persuasive capabilities that rival human-level persuasion. While these capabilities can be used for social good, they also present risks of…