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Found 8 papers, 3 papers with code
Considering Nested Tree Structure in Sentence Extractive Summarization with Pre-trained Transformer
Sentence extractive summarization shortens a document by selecting sentences for a summary while preserving its important contents.
Ranked #4 on
Extractive Text Summarization
on CNN / Daily Mail
Making Your Tweets More Fancy: Emoji Insertion to Texts
The results demonstrate that the position of emojis in texts is a good clue to boost the performance of emoji label prediction.
A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
To promote and further develop RST-style discourse parsing models, we need a strong baseline that can be regarded as a reference for reporting reliable experimental results.
Ranked #1 on
Discourse Parsing
on Instructional-DT (Instr-DT)
Improving Neural RST Parsing Model with Silver Agreement Subtrees
We then pre-train a neural RST parser with the obtained silver data and fine-tune it on the RST-DT.
Ranked #2 on
Discourse Parsing
on RST-DT
(using extra training data)
Toward Neural-Network-Guided Program Synthesis and Verification
Another application is to a new program development framework called oracle-based programming, which is a neural-network-guided variation of Solar-Lezama's program synthesis by sketching.
A Cyclic Proof System for HFLN
A cyclic proof system allows us to perform inductive reasoning without explicit inductions.
Top-Down RST Parsing Utilizing Granularity Levels in Documents
To obtain better discourse dependency trees, we need to improve the accuracy of RST trees at the upper parts of the structures.
Ranked #3 on
Discourse Parsing
on RST-DT
Split or Merge: Which is Better for Unsupervised RST Parsing?
The first one builds the optimal tree in terms of a dissimilarity score function that is defined for splitting a text span into smaller ones.
