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Found 26 papers, 5 papers with code
Analyzing the Semantic Types of Claims and Premises in an Online Persuasive Forum
Argumentative text has been analyzed both theoretically and computationally in terms of argumentative structure that consists of argument components (e. g., claims, premises) and their argumentative relations (e. g., support, attack).
`Lighter' Can Still Be Dark: Modeling Comparative Color Descriptions
We propose a novel paradigm of grounding comparative adjectives within the realm of color descriptions.
Automatically Tailoring Unsupervised Morphological Segmentation to the Language
Morphological segmentation is beneficial for several natural language processing tasks dealing with large vocabularies.
Where is Your Evidence: Improving Fact-checking by Justification Modeling
Fact-checking is a journalistic practice that compares a claim made publicly against trusted sources of facts.
Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.
Our team finished 6th out of 24 teams on the leader-board based on the preliminary results with a FEVER score of 49. 06 on the blind test set compared to 27. 45 of the baseline system.
ColumbiaNLP at SemEval-2019 Task 8: The Answer is Language Model Fine-tuning
Community Question Answering forums are very popular nowadays, as they represent effective means for communities to share information around particular topics.
Columbia at SemEval-2019 Task 7: Multi-task Learning for Stance Classification and Rumour Verification
The paper presents Columbia team{'}s participation in the SemEval 2019 Shared Task 7: RumourEval 2019.
Rubric Reliability and Annotation of Content and Argument in Source-Based Argument Essays
We present a unique dataset of student source-based argument essays to facilitate research on the relations between content, argumentation skills, and assessment.
Pay ``Attention'' to your Context when Classifying Abusive Language
The goal of any social media platform is to facilitate healthy and meaningful interactions among its users.
Unsupervised Morphological Segmentation for Low-Resource Polysynthetic Languages
Polysynthetic languages pose a challenge for morphological analysis due to the root-morpheme complexity and to the word class {``}squish{''}.
MorphAGram, Evaluation and Framework for Unsupervised Morphological Segmentation
Computational morphological segmentation has been an active research topic for decades as it is beneficial for many natural language processing tasks.
An Evaluation of Subword Segmentation Strategies for Neural Machine Translation of Morphologically Rich Languages
Byte-Pair Encoding (BPE) (Sennrich et al., 2016) has become a standard pre-processing step when building neural machine translation systems.
R\^3: Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledge
We propose an unsupervised approach for sarcasm generation based on a non-sarcastic input sentence.
