4 citations · 7 across the 7 of their papers we have counts for
7 papers
Efficient Encoders for Streaming Sequence Tagging
Ayush Kaushal, Aditya Gupta, Shyam Upadhyay +1
A naive application of state-of-the-art bidirectional encoders for streaming sequence tagging would require encoding each token from scratch for each new token in an incremental st…
Discovering Intrinsic Reward with Contrastive Random Walk
Zixuan Pan, Zihao Wei, Yidong Huang +1
The aim of this paper is to demonstrate the efficacy of using Contrastive Random Walk as a curiosity method to achieve faster convergence to the optimal policy.Contrastive Random W…
Improving Top-K Decoding for Non-Autoregressive Semantic Parsing via Intent Conditioning
Geunseob Oh, Rahul Goel, Chris Hidey +4
Semantic parsing (SP) is a core component of modern virtual assistants like Google Assistant and Amazon Alexa. While sequence-to-sequence-based auto-regressive (AR) approaches are…
TableFormer: Robust Transformer Modeling for Table-Text Encoding
Jingfeng Yang, Aditya Gupta, Shyam Upadhyay +3
Understanding tables is an important aspect of natural language understanding. Existing models for table understanding require linearization of the table structure, where row or co…
TIMEDIAL: Temporal Commonsense Reasoning in Dialog
Lianhui Qin, Aditya Gupta, Shyam Upadhyay +3
Everyday conversations require understanding everyday events, which in turn, requires understanding temporal commonsense concepts interwoven with those events. Despite recent progr…
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
Aditya Gupta, Jiacheng Xu, Shyam Upadhyay +2
Disfluencies is an under-studied topic in NLP, even though it is ubiquitous in human conversation. This is largely due to the lack of datasets containing disfluencies. In this pape…