36 citations · 53 across the 6 of their papers we have counts for
6 papers
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…
Rethinking Self-Supervision Objectives for Generalizable Coherence Modeling
Prathyusha Jwalapuram, Shafiq Joty, Xiang Lin
Given the claims of improved text generation quality across various pre-trained neural models, we consider the coherence evaluation of machine generated text to be one of the princ…
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…
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…
Hierarchical Pointer Net Parsing
Linlin Liu, Xiang Lin, Shafiq Joty +2
Transition-based top-down parsing with pointer networks has achieved state-of-the-art results in multiple parsing tasks, while having a linear time complexity. However, the decoder…
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…