20 citations · 45 across the 7 of their papers we have counts for
3 papers · 1 filter
Bew: Towards Answering Business-Entity-Related Web Questions
Qingqing Cao, Oriana Riva, Aruna Balasubramanian +1
We present BewQA, a system specifically designed to answer a class of questions that we call Bew questions. Bew questions are related to businesses/services such as restaurants, ho…
Towards Accurate and Reliable Energy Measurement of NLP Models
Qingqing Cao, Aruna Balasubramanian, Niranjan Balasubramanian
Accurate and reliable measurement of energy consumption is critical for making well-informed design choices when choosing and training large scale NLP models. In this work, we show…
DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering
Qingqing Cao, Harsh Trivedi, Aruna Balasubramanian +1
Transformer-based QA models use input-wide self-attention -- i.e. across both the question and the input passage -- at all layers, causing them to be slow and memory-intensive. It…