7 papers
Enhancing Diversity of LLM-Generated Educational Tasks
Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla
Large language models (LLMs) have shown the potential for generating educational content at scale, assisting educators in creating practice tasks or synthesizing data for training…
Uncertainty-Aware Budget Allocation for Adaptive Test-Time Reasoning
Manh Nguyen, Sunil Gupta, Hung Le
Sampling multiple responses improves language model reasoning, but uniform compute allocation is inefficient: easy questions are over-sampled while hard questions remain under-expl…
Beyond Majority Voting: Efficient Best-Of-N with Radial Consensus Score
Manh Nguyen, Sunil Gupta, Hung Le
Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challenging, especially when correctne…
Hear Both Sides: Efficient Multi-Agent Debate via Diversity-Aware Message Retention
Manh Nguyen, Anh Nguyen, Dung Nguyen +2
Multi-Agent Debate has emerged as a promising framework for improving the reasoning quality of large language models through iterative inter-agent communication. However, broadcast…
Prompt Optimization Across Multiple Agents for Representing Diverse Human Populations
Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla
The difficulty and expense of obtaining large-scale human responses make Large Language Models (LLMs) an attractive alternative and a promising proxy for human behavior. However, p…
Partnering with AI: A Pedagogical Feedback System for LLM Integration into Programming Education
Niklas Scholz, Manh Hung Nguyen, Adish Singla +1
Feedback is one of the most crucial components to facilitate effective learning. With the rise of large language models (LLMs) in recent years, research in programming education ha…