6 papers
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…
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…
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…
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…
ParaStudent: Generating and Evaluating Realistic Student Code by Teaching LLMs to Struggle
Mihran Miroyan, Rose Niousha, Joseph E. Gonzalez +2
Large Language Models (LLMs) have shown strong performance on programming tasks, but can they generate student-like code like real students - imperfect, iterative, and stylisticall…