Search Results for author:
Found 31 papers, 5 papers with code
SODA: Story Oriented Dense Video Captioning Evaluation Framework
This paper proposes a new evaluation framework, Story Oriented Dense video cAptioning evaluation framework (SODA), for measuring the performance of video story description systems.
WikiSplit++: Easy Data Refinement for Split and Rephrase
The task of Split and Rephrase, which splits a complex sentence into multiple simple sentences with the same meaning, improves readability and enhances the performance of downstream tasks in natural language processing (NLP).
Can we obtain significant success in RST discourse parsing by using Large Language Models?
Recently, decoder-only pre-trained large language models (LLMs), with several tens of billion parameters, have significantly impacted a wide range of natural language processing (NLP) tasks.
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)
Sequential Span Classification with Neural Semi-Markov CRFs for Biomedical Abstracts
Dividing biomedical abstracts into several segments with rhetorical roles is essential for supporting researchers{'} information access in the biomedical domain.
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
Recovery command generation towards automatic recovery in ICT systems by Seq2Seq learning
With the increase in scale and complexity of ICT systems, their operation increasingly requires automatic recovery from failures.
Generating Natural Anagrams: Towards Language Generation Under Hard Combinatorial Constraints
An anagram is a sentence or a phrase that is made by permutating the characters of an input sentence or a phrase.
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.
NTT's Machine Translation Systems for WMT19 Robustness Task
This paper describes NTT's submission to the WMT19 robustness task.
Automatic Pyramid Evaluation Exploiting EDU-based Extractive Reference Summaries
This paper tackles automation of the pyramid method, a reliable manual evaluation framework.
Higher-Order Syntactic Attention Network for Longer Sentence Compression
To solve this problem, we propose a higher-order syntactic attention network (HiSAN) that can handle higher-order dependency features as an attention distribution on LSTM hidden states.
Ranked #3 on
Sentence Compression
on Google Dataset
Pruning Basic Elements for Better Automatic Evaluation of Summaries
We propose a simple but highly effective automatic evaluation measure of summarization, pruned Basic Elements (pBE).
Provable Fast Greedy Compressive Summarization with Any Monotone Submodular Function
This approach is known to have three advantages: its applicability to many useful submodular objective functions, the efficiency of the greedy algorithm, and the provable performance guarantee.
Supervised Attention for Sequence-to-Sequence Constituency Parsing
The sequence-to-sequence (Seq2Seq) model has been successfully applied to machine translation (MT).
Oracle Summaries of Compressive Summarization
This paper derives an Integer Linear Programming (ILP) formulation to obtain an oracle summary of the compressive summarization paradigm in terms of ROUGE.
Enumeration of Extractive Oracle Summaries
To analyze the limitations and the future directions of the extractive summarization paradigm, this paper proposes an Integer Linear Programming (ILP) formulation to obtain extractive oracle summaries in terms of ROUGE-N. We also propose an algorithm that enumerates all of the oracle summaries for a set of reference summaries to exploit F-measures that evaluate which system summaries contain how many sentences that are extracted as an oracle summary.
Exploring Text Links for Coherent Multi-Document Summarization
Existing methods focus on the extraction of key information, but often neglect coherence.
