1 citations · 1 across the 4 of their papers we have counts for
4 papers
Leveraging Structured Information for Explainable Multi-hop Question Answering and Reasoning
Ruosen Li, Xinya Du
Neural models, including large language models (LLMs), achieve superior performance on multi-hop question-answering. To elicit reasoning capabilities from LLMs, recent works propos…
POE: Process of Elimination for Multiple Choice Reasoning
Chenkai Ma, Xinya Du
Language models (LMs) are capable of conducting in-context learning for multiple choice reasoning tasks, but the options in these tasks are treated equally. As humans often first e…
Probing Representations for Document-level Event Extraction
Barry Wang, Xinya Du, Claire Cardie
The probing classifiers framework has been employed for interpreting deep neural network models for a variety of natural language processing (NLP) applications. Studies, however, h…
AGent: A Novel Pipeline for Automatically Creating Unanswerable Questions
Son Quoc Tran, Gia-Huy Do, Phong Nguyen-Thuan Do +2
The development of large high-quality datasets and high-performing models have led to significant advancements in the domain of Extractive Question Answering (EQA). This progress h…