32 citations · 300 across the 54 of their papers we have counts for
8 papers · 1 filter
SemEval-2017 Task 3: Community Question Answering
Preslav Nakov, Doris Hoogeveen, Lluís Màrquez +4
We describe SemEval-2017 Task 3 on Community Question Answering. This year, we reran the four subtasks from SemEval-2016:(A) Question-Comment Similarity,(B) Question-Question Simil…
Improved Document Modelling with a Neural Discourse Parser
Fajri Koto, Jey Han Lau, Timothy Baldwin
Despite the success of attention-based neural models for natural language generation and classification tasks, they are unable to capture the discourse structure of larger document…
Deep Ordinal Regression for Pledge Specificity Prediction
Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin
Many pledges are made in the course of an election campaign, forming important corpora for political analysis of campaign strategy and governmental accountability. At present, ther…
Evaluating the Utility of Document Embedding Vector Difference for Relation Learning
Jingyuan Zhang, Timothy Baldwin
Recent work has demonstrated that vector offsets obtained by subtracting pretrained word embedding vectors can be used to predict lexical relations with surprising accuracy. Inspir…
Semi-supervised Stochastic Multi-Domain Learning using Variational Inference
Yitong Li, Timothy Baldwin, Trevor Cohn
Supervised models of NLP rely on large collections of text which closely resemble the intended testing setting. Unfortunately matching text is often not available in sufficient qua…
Target Based Speech Act Classification in Political Campaign Text
Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin
We study pragmatics in political campaign text, through analysis of speech acts and the target of each utterance. We propose a new annotation schema incorporating domain-specific s…