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Bing Xiang

68 papers hereh-index 5015.7k citations134 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author23
  • last author45

Across the 68 of 68 papers where every author was matched, so the position is known.

fields
  • cs.CL54
  • cs.LG7
  • cs.IR3
  • cs.AI1
  • cs.CV1
  • cs.NE1
same name
  • Bing Xiang — 4 papers, h 4
  • Bing Xiang — 2 papers, h 3
  • Bing Xiang — 1 paper, h 6
  • Bing Xiang — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152023
most citedA Structured Self-attentive Sentence Embedding

1.5k citations · 3.5k across the 68 of their papers we have counts for

collaborators
Showing 2016 · cs.CLShow all

4 papers · 2 filters

cs.CL2016★ 28 cited

Simple Question Answering by Attentive Convolutional Neural Network

Wenpeng Yin, Mo Yu, Bing Xiang +2

This work focuses on answering single-relation factoid questions over Freebase. Each question can acquire the answer from a single fact of form (subject, predicate, object) in Free…

cs.CL2016★ 324 cited

Attentive Pooling Networks

Cicero dos Santos, Ming Tan, Bing Xiang +1

In this work, we propose Attentive Pooling (AP), a two-way attention mechanism for discriminative model training. In the context of pair-wise ranking or classification with neural…

cs.CL2016★ 371 cited

Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond

Ramesh Nallapati, Bowen Zhou, Cicero Nogueira dos santos +2

In this work, we model abstractive text summarization using Attentional Encoder-Decoder Recurrent Neural Networks, and show that they achieve state-of-the-art performance on two di…

cs.CL2016★ 21 cited

Leveraging Sentence-level Information with Encoder LSTM for Semantic Slot Filling

Gakuto Kurata, Bing Xiang, Bowen Zhou +1

Recurrent Neural Network (RNN) and one of its specific architectures, Long Short-Term Memory (LSTM), have been widely used for sequence labeling. In this paper, we first enhance LS…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.