4 citations · 9 across the 6 of their papers we have counts for
4 papers · 1 filter
Assessing and Enhancing the Robustness of Large Language Models with Task Structure Variations for Logical Reasoning
Qiming Bao, Gael Gendron, Alex Yuxuan Peng +5
Large language models (LLMs), such as LLaMA, Alpaca, Vicuna, GPT-3.5 and GPT-4, have advanced the performance of AI systems on various natural language processing tasks to human-li…
Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models
Qiming Bao, Juho Leinonen, Alex Yuxuan Peng +7
Large language models exhibit superior capabilities in processing and understanding language, yet their applications in educational contexts remain underexplored. Learnersourcing e…
Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning
Qiming Bao, Alex Yuxuan Peng, Zhenyun Deng +10
Combining large language models with logical reasoning enhances their capacity to address problems in a robust and reliable manner. Nevertheless, the intricate nature of logical re…
Input-length-shortening and text generation via attention values
Neşet Özkan Tan, Alex Yuxuan Peng, Joshua Bensemann +4
Identifying words that impact a task's performance more than others is a challenge in natural language processing. Transformers models have recently addressed this issue by incorpo…