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Bing Xiang

41 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 author11
  • last author30

Across the 41 of 41 papers where every author was matched, so the position is known.

fields
  • cs.CL33
  • cs.IR3
  • cs.LG2
  • cs.AI1
  • cs.CV1
  • cs.NE1
same name
  • Bing Xiang — 4 papers, h 4
  • Bing Xiang — 3 papers
  • Bing Xiang — 2 papers
  • Bing Xiang — 2 papers, h 3

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 · 1.8k across the 27 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

cs.CL2017★ 1 cited

Group Sparse CNNs for Question Classification with Answer Sets

Mingbo Ma, Liang Huang, Bing Xiang +1

Question classification is an important task with wide applications. However, traditional techniques treat questions as general sentences, ignoring the corresponding answer data. I…

cs.CL2017★ 5 cited

Jointly Trained Sequential Labeling and Classification by Sparse Attention Neural Networks

Mingbo Ma, Kai Zhao, Liang Huang +2

Sentence-level classification and sequential labeling are two fundamental tasks in language understanding. While these two tasks are usually modeled separately, in reality, they ar…

cs.CL2017★ 53 cited

Improved Neural Relation Detection for Knowledge Base Question Answering

Mo Yu, Wenpeng Yin, Kazi Saidul Hasan +3

Relation detection is a core component for many NLP applications including Knowledge Base Question Answering (KBQA). In this paper, we propose a hierarchical recurrent neural netwo…

cs.CL2017★ 1.5k cited

A Structured Self-attentive Sentence Embedding

Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos +4

This paper proposes a new model for extracting an interpretable sentence embedding by introducing self-attention. Instead of using a vector, we use a 2-D matrix to represent the em…

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