7 citations · 8 across the 9 of their papers we have counts for
6 papers · 1 filter
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning
Zheyuan Zhang, Shane Storks, Fengyuan Hu +4
Pre-trained language models (PLMs) have shown impressive performance in various language tasks. However, they are prone to spurious correlations, and often generate illusory inform…
NLP Reproducibility For All: Understanding Experiences of Beginners
Shane Storks, Keunwoo Peter Yu, Ziqiao Ma +1
As natural language processing (NLP) has recently seen an unprecedented level of excitement, and more people are eager to enter the field, it is unclear whether current research re…
Reproducibility Beyond the Research Community: Experience from NLP Beginners
Shane Storks, Keunwoo Peter Yu, Joyce Chai
As NLP research attracts public attention and excitement, it becomes increasingly important for it to be accessible to a broad audience. As the research community works to democrat…
Best of Both Worlds: A Hybrid Approach for Multi-Hop Explanation with Declarative Facts
Shane Storks, Qiaozi Gao, Aishwarya Reganti +1
Language-enabled AI systems can answer complex, multi-hop questions to high accuracy, but supporting answers with evidence is a more challenging task which is important for the tra…
Beyond the Tip of the Iceberg: Assessing Coherence of Text Classifiers
Shane Storks, Joyce Chai
As large-scale, pre-trained language models achieve human-level and superhuman accuracy on existing language understanding tasks, statistical bias in benchmark data and probing stu…
Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches
Shane Storks, Qiaozi Gao, Joyce Y. Chai
In the NLP community, recent years have seen a surge of research activities that address machines' ability to perform deep language understanding which goes beyond what is explicit…