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Tian Shi

Virginia Tech

10 papers hereh-index 201.6k citations50 works total

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

author position
  • first author5
  • middle author4
  • last author1

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CL7
  • cs.IR1
  • cs.LG1
  • math.FA1
affiliations
  • Virginia Tech
same name
  • Tian Shi — 3 papers, h 2
  • Tian Shi — 2 papers, h 0
  • Tian Shi — 2 papers, h 3
  • Tian Shi — 1 paper
  • Tian Shi — 1 paper, h 5
  • Tian Shi — 1 paper, h 2

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
20182022
most citedNeural Abstractive Text Summarization with Sequence-to-Sequence Models

68 citations · 93 across the 9 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CL2020

An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment Analysis

Tian Shi, Ping Wang, Chandan K. Reddy

In recent years, several online platforms have seen a rapid increase in the number of review systems that request users to provide aspect-level feedback. Document-level Multi-aspec…

cs.CL2020★ 7 cited

A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection

Tian Shi, Liuqing Li, Ping Wang +1

Unsupervised aspect detection (UAD) aims at automatically extracting interpretable aspects and identifying aspect-specific segments (such as sentences) from online reviews. However…

cs.IR2020

Corpus-level and Concept-based Explanations for Interpretable Document Classification

Tian Shi, Xuchao Zhang, Ping Wang +1

Using attention weights to identify information that is important for models' decision-making is a popular approach to interpret attention-based neural networks. This is commonly r…

math.FA2020

Strong Convergence Theorems by Generalized CQ Method in Hilbert Spaces

Songnian He, Tian Shi

Recently, CQ method has been investigated extensively. However, it is mainly applied to modify Mann, Ishikawa and Halpern iterations to get strong convergence. In this paper, we st…

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