activity
20162020
most citedEnd-to-End Answer Chunk Extraction and Ranking for Reading Comprehension

42 citations · 193 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL202011 cited

Improve Transformer Models with Better Relative Position Embeddings

Zhiheng Huang, Davis Liang, Peng Xu +1

Transformer architectures rely on explicit position encodings in order to preserve a notion of word order. In this paper, we argue that existing work does not fully utilize positio…

cs.IR202024 cited

Embedding-based Zero-shot Retrieval through Query Generation

Davis Liang, Peng Xu, Siamak Shakeri +4

Passage retrieval addresses the problem of locating relevant passages, usually from a large corpus, given a query. In practice, lexical term-matching algorithms like BM25 are popul…

cs.CL20203 cited

Augmented Natural Language for Generative Sequence Labeling

Ben Athiwaratkun, Cicero Nogueira dos Santos, Jason Krone +1

We propose a generative framework for joint sequence labeling and sentence-level classification. Our model performs multiple sequence labeling tasks at once using a single, shared…

cs.CL20195 cited

Who did They Respond to? Conversation Structure Modeling using Masked Hierarchical Transformer

Henghui Zhu, Feng Nan, Zhiguo Wang +2

Conversation structure is useful for both understanding the nature of conversation dynamics and for providing features for many downstream applications such as summarization of con…

cs.CL201940 cited

Universal Text Representation from BERT: An Empirical Study

Xiaofei Ma, Zhiguo Wang, Patrick Ng +2

We present a systematic investigation of layer-wise BERT activations for general-purpose text representations to understand what linguistic information they capture and how transfe…

cs.CL201924 cited

Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering

Zhiguo Wang, Patrick Ng, Xiaofei Ma +2

BERT model has been successfully applied to open-domain QA tasks. However, previous work trains BERT by viewing passages corresponding to the same question as independent training…