1 citations · 1 across the 9 of their papers we have counts for
9 papers
INSIDE the Student's Mind: Jointly Modeling Latent Reasoning and Action in LLM Student Simulators
Rose Niousha, Minwoo Kang, Narges Norouzi
Large Language Model (LLM)-based simulators often reproduce observable actions but fail to capture the underlying reasoning behind them. In education, where student simulation is i…
Recon: Reconstruction-Guided Reasoning Synthesis for User Modeling
Alan Zhu, Mihran Miroyan, Carolyn Wang +4
User modeling aims to use language models (LMs) to mimic an individual's behavior from a corpus of past context-action pairs (e.g., conversation turns), enabling the simulation of…
Cooperate to Compete: Strategic Coordination in Multi-Agent Conquest
Abigail O'Neill, Alan Zhu, Mihran Miroyan +2
Language Model (LM)-based agents remain largely untested in mixed-motive settings where agents must leverage short-term cooperation for long-term competitive goals (e.g., multi-par…
LeanTutor: Towards a Verified AI Mathematical Proof Tutor
Manooshree Patel, Rayna Bhattacharyya, Thomas Lu +4
This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language,…
EduMod-LLM: A Modular Approach for Designing Flexible and Transparent Educational Assistants
Meenakshi Mittal, Rishi Khare, Mihran Miroyan +2
With the growing use of Large Language Model (LLM)-based Question-Answering (QA) systems in education, it is critical to evaluate their performance across individual pipeline compo…
Are Large Reasoning Models Interruptible?
Tsung-Han Wu, Mihran Miroyan, David M. Chan +3
Real-world applications of Large Reasoning Models (LRMs) often require reasoning about changing prompts or environments. In this work, we challenge the frozen world assumption and…
ParaStudent: Closing the Sim2Real Gap in User Simulators for AI Tutor Evaluation
Rose Niousha, Mihran Miroyan, Abigail O'Neill +4
Evaluating Artificial Intelligence (AI) tutor feedback before deployment requires anticipating student engagement, typically assessed through real interaction data. We introduce Pa…
LeanTutor: Towards a Verified AI Mathematical Proof Tutor
Manooshree Patel, Rayna Bhattacharyya, Thomas Lu +4
This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language,…
Search Arena: Analyzing Search-Augmented LLMs
Mihran Miroyan, Tsung-Han Wu, Logan King +8
Search-augmented language models combine web search with Large Language Models (LLMs) to improve response groundedness and freshness. However, analyzing these systems remains chall…