4 citations · 6 across the 11 of their papers we have counts for
12 papers
Learning User Representations to Improve Simulation Fidelity
Shuhaib Mehri, Philippe Laban, Michel Galley +3
User simulators enable interactive training and evaluation of AI assistants at scale. Yet current simulators struggle to reproduce the diverse behaviors of real users, leading to a…
Measuring and Mitigating the Distributional Gap Between Real and Simulated User Behaviors
Shuhaib Mehri, Philippe Laban, Sumuk Shashidhar +4
As user simulators are increasingly used for interactive training and evaluation of AI assistants, it is essential that they represent the diverse behaviors of real users. While ex…
PSI-Bench: Interpretable and Clinically Meaningful Evaluation of Depression Patient Simulators
Nguyen Khoi Hoang, Shuhaib Mehri, Tse-An Hsu +4
Patient simulators are gaining traction in mental health training by providing scalable exposure to complex and sensitive patient interactions. Simulating depressed patients is cha…
User Preference Modeling for Conversational LLM Agents: Weak Rewards from Retrieval-Augmented Interaction
Yuren Hao, Shuhaib Mehri, ChengXiang Zhai +1
Large language models are increasingly used as personal assistants, yet most lack a persistent user model, forcing users to repeatedly restate preferences across sessions. We propo…
Sparking Scientific Creativity via LLM-Driven Interdisciplinary Inspiration
Priyanka Kargupta, Shuhaib Mehri, Dilek Hakkani-Tur +1
Despite interdisciplinary research leading to larger and longer-term impact, most work remains confined to single-domain academic silos. Recent AI-based approaches to scientific di…
MultiSessionCollab: Learning User Preferences with Memory to Improve Long-Term Collaboration
Shuhaib Mehri, Priyanka Kargupta, Tal August +1
As conversational agents accumulate experience collaborating with users, adapting to user preferences is essential for fostering long-term relationships and improving collaboration…
Goal Alignment in LLM-Based User Simulators for Conversational AI
Shuhaib Mehri, Xiaocheng Yang, Takyoung Kim +3
User simulators are essential to conversational AI, enabling scalable agent development and evaluation through simulated interactions. While current Large Language Models (LLMs) ha…
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…
Beyond Sample-Level Feedback: Using Reference-Level Feedback to Guide Data Synthesis
Shuhaib Mehri, Xiusi Chen, Heng Ji +1
High-quality instruction-tuning data is crucial for developing Large Language Models (LLMs) that can effectively navigate real-world tasks and follow human instructions. While synt…
Automatic Evaluation of Generative Models with Instruction Tuning
Shuhaib Mehri, Vered Shwartz
Automatic evaluation of natural language generation has long been an elusive goal in NLP.A recent paradigm fine-tunes pre-trained language models to emulate human judgements for a…