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  • Reading Notes

  • Sarcasm Detection

    • Detecting Sarcasm is Extremely Easy ;) (Parde & Nielson 2018)

    • Harnessing Context Incongruity for Sarcasm Detection (Joshi et al 2015)

    • Sarcasm as Contrast between a Positive Sentiment and Negative Sentiment

  • Neural Networks

    • Catastrophic Interference in Neural Embedding Models (Dachapally & Jones)

    • Querying word embeddings for word similarity and relatdness

    • Multi-Task Deep Neural Networks for Natural Language Understanding

  • Answer Scoring

    • Riordan et al., 2019

    • Horbach et al., 2019

    • Riordan et al. 2020

  • CLINGDINGS

    • How do you determine the worth of a language?

    • November 6th 2019: Hai, Peng

    • Alan Ridel

    • Hai Hu 02-19-2020

    • Zeeshan 02-19-2020

  • Parsing

    • Overview of the SPMRL 2013 Shared Task:Cross-Framework Evaluation of Parsing Morphologically Rich Languages

    • Dependency Parsing

    • Characterizing the Errors of Data-Driven Dependency Parsing Models

  • Reading Template

  • Professionalization workshop

    • January 17th - Job search

    • Job talk Monica Nesbit

  • Language Modelling

    • BLiMP: A Benchmark of Linguistic Minimal Pairs for English

  • Swahili Syntax

    • Swahili Syntax (Anthony Vitale, 1981)

  • Syntax for "Exotic" languages

    • Developing Universal Dependencies for Wolof

    • Towards a dependency-annotated treebank for Bambara (Aplonova & Tyers 2018)

  • To Read

  • Universal Dependencies

    • A Universal Part-of-Speech Tagset (Petrov, Das, McDonald)

    • Universal Depedencies v1: A Multilingual Treebank Collection

  • CG to Dependency Parse

    • Reusing Grammatical Resources for New Languages

    • Estonian Dependency Treebank: from Constraint Grammar Tagset to Universal Dependencies

  • Bantu NLP

    • Learning Morphosyntactic analyzers from the bible via iterative annotation projection across 26 languages

Books
Reading Notes
Answer Scoring

Answer Scoring

Riordan et al., 2019

How to account for mispellings: Quantifying the benefit of character representations in neural c...

Horbach et al., 2019

The influence of variance in learner answers on automatic content scoring Andrea Horbach and Tor...

Riordan et al. 2020

An empirical investigation of neural methods for content scoring of science explanations NGSS sc...

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Created 5 years ago by kenneth
Updated 5 years ago by kenneth
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