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Xiang Lin

School of Computer Science and Engineering, Nanyang Technological University

4 papers hereh-index 6392 citations7 works total

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

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
affiliations
  • School of Computer Science and Engineering, Nanyang Technological University
Homepage
same name
  • Xiang Lin — 4 papers
  • Xiang Lin — 2 papers
  • Xiang Lin — 2 papers
  • Xiang Lin — 1 paper
  • Xiang Lin — 1 paper, h 6
  • Xiang Lin — 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
20192022
most citedA Unified Linear-Time Framework for Sentence-Level Discourse Parsing

8 citations · 17 across the 3 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2022★ 6 cited

Chart-to-Text: A Large-Scale Benchmark for Chart Summarization

Shankar Kantharaj, Rixie Tiffany Ko Leong, Xiang Lin +4

Charts are commonly used for exploring data and communicating insights. Generating natural language summaries from charts can be very helpful for people in inferring key insights t…

cs.CL2021★ 3 cited

Straight to the Gradient: Learning to Use Novel Tokens for Neural Text Generation

Xiang Lin, Simeng Han, Shafiq Joty

Advanced large-scale neural language models have led to significant success in many language generation tasks. However, the most commonly used training objective, Maximum Likelihoo…

cs.CL2019

Resurrecting Submodularity for Neural Text Generation

Simeng Han, Xiang Lin, Shafiq Joty

Submodularity is desirable for a variety of objectives in content selection where the current neural encoder-decoder framework is inadequate. However, it has so far not been explor…

cs.CL2019★ 8 cited

A Unified Linear-Time Framework for Sentence-Level Discourse Parsing

Xiang Lin, Shafiq Joty, Prathyusha Jwalapuram +1

We propose an efficient neural framework for sentence-level discourse analysis in accordance with Rhetorical Structure Theory (RST). Our framework comprises a discourse segmenter t…

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