30 citations · 121 across the 19 of their papers we have counts for
8 papers · 1 filter
Can Language Representation Models Think in Bets?
Zhisheng Tang, Mayank Kejriwal
In recent years, transformer-based language representation models (LRMs) have achieved state-of-the-art results on difficult natural language understanding problems, such as questi…
Understanding Substructures in Commonsense Relations in ConceptNet
Ke Shen, Mayank Kejriwal
Acquiring commonsense knowledge and reasoning is an important goal in modern NLP research. Despite much progress, there is still a lack of understanding (especially at scale) of th…
Understanding Prior Bias and Choice Paralysis in Transformer-based Language Representation Models through Four Experimental Probes
Ke Shen, Mayank Kejriwal
Recent work on transformer-based neural networks has led to impressive advances on multiple-choice natural language understanding (NLU) problems, such as Question Answering (QA) an…
Do Fine-tuned Commonsense Language Models Really Generalize?
Mayank Kejriwal, Ke Shen
Recently, transformer-based methods such as RoBERTa and GPT-3 have led to significant experimental advances in natural language processing tasks such as question answering and comm…
An Experimental Study of The Effects of Position Bias on Emotion CauseExtraction
Jiayuan Ding, Mayank Kejriwal
Emotion Cause Extraction (ECE) aims to identify emotion causes from a document after annotating the emotion keywords. Some baselines have been proposed to address this problem, suc…
Low-supervision urgency detection and transfer in short crisis messages
Mayank Kejriwal, Peilin Zhou
Humanitarian disasters have been on the rise in recent years due to the effects of climate change and socio-political situations such as the refugee crisis. Technology can be used…