17 citations · 19 across the 3 of their papers we have counts for
3 papers
Entropy-Gated Branching for Efficient Test-Time Reasoning
Xianzhi Li, Ethan Callanan, Abdellah Ghassel +1
Test-time compute methods can significantly improve the reasoning capabilities and problem-solving accuracy of large language models (LLMs). However, these approaches require subst…
Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams
Ethan Callanan, Amarachi Mbakwe, Antony Papadimitriou +6
Large Language Models (LLMs) have demonstrated remarkable performance on a wide range of Natural Language Processing (NLP) tasks, often matching or even beating state-of-the-art ta…
MACQ: A Holistic View of Model Acquisition Techniques
Ethan Callanan, Rebecca De Venezia, Victoria Armstrong +3
For over three decades, the planning community has explored countless methods for data-driven model acquisition. These range in sophistication (e.g., simple set operations to full-…