Search Results for author:
Found 16 papers, 3 papers with code
Scalable Prompt Generation for Semi-supervised Learning with Language Models
In this paper, we propose two methods to automatically design multiple prompts and integrate automatic verbalizer in SSL settings without sacrificing performance.
C1 at SemEval-2020 Task 9: SentiMix: Sentiment Analysis for Code-Mixed Social Media Text using Feature Engineering
In today's interconnected and multilingual world, code-mixing of languages on social media is a common occurrence.
Jointly Learning Author and Annotated Character N-gram Embeddings: A Case Study in Literary Text
An author{'}s way of presenting a story through his/her writing style has a great impact on whether the story will be liked by readers or not.
A Multi-task Approach for Named Entity Recognition in Social Media Data
Named Entity Recognition for social media data is challenging because of its inherent noisiness.
Ranked #21 on
Named Entity Recognition (NER)
on WNUT 2017
A Genre-Aware Attention Model to Improve the Likability Prediction of Books
Likability prediction of books has many uses.
Folksonomication: Predicting Tags for Movies from Plot Synopses Using Emotion Flow Encoded Neural Network
Folksonomy of movies covers a wide range of heterogeneous information about movies, like the genre, plot structure, visual experiences, soundtracks, metadata, and emotional experiences from watching a movie.
Language Identification and Analysis of Code-Switched Social Media Text
In this paper, we detail our work on comparing different word-level language identification systems for code-switched Hindi-English data and a standard Spanish-English dataset.
Letting Emotions Flow: Success Prediction by Modeling the Flow of Emotions in Books
Books have the power to make us feel happiness, sadness, pain, surprise, or sorrow.
MPST: A Corpus of Movie Plot Synopses with Tags
In this paper, we set out to the task of collecting a corpus of movie plot synopses and tags.
Detecting Nastiness in Social Media
Although social media has made it easy for people to connect on a virtually unlimited basis, it has also opened doors to people who misuse it to undermine, harass, humiliate, threaten and bully others.
RiTUAL-UH at SemEval-2017 Task 5: Sentiment Analysis on Financial Data Using Neural Networks
In this paper, we present our systems for the {``}SemEval-2017 Task-5 on Fine-Grained Sentiment Analysis on Financial Microblogs and News{''}.
A Multi-task Approach to Predict Likability of Books
We investigate the value of feature engineering and neural network models for predicting successful writing.
CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings
The evaluation results of our system on the test set is 88. 1{\%} (79. 0{\%} for TRUE only) f-measure for Task-1 on detecting semantic similarity, and 76. 0{\%} (42. 3{\%} when excluding RANDOM) for Task-2 on identifying finer-grained semantic relations.
