ACL.2014 - Long Papers

#1 Learning Ensembles of Structured Prediction Rules

#2 Representation Learning for Text-level Discourse Parsing

#3 Text-level Discourse Dependency Parsing

#4 Discovering Latent Structure in Task-Oriented Dialogues

#5 Learning Structured Perceptrons for Coreference Resolution with Latent Antecedents and Non-local Features

#6 Multilingual Models for Compositional Distributed Semantics

#7 Simple Negation Scope Resolution through Deep Parsing: A Semantic Solution to a Semantic Problem

#8 Logical Inference on Dependency-based Compositional Semantics

#9 A practical and linguistically-motivated approach to compositional distributional semantics

#10 Lattice Desegmentation for Statistical Machine Translation

#11 Bilingually-constrained Phrase Embeddings for Machine Translation

#12 Learning New Semi-Supervised Deep Auto-encoder Features for Statistical Machine Translation

#13 Learning Topic Representation for SMT with Neural Networks

#14 Tagging The Web: Building A Robust Web Tagger with Neural Network

#15 Unsupervised Solution Post Identification from Discussion Forums

#16 Weakly Supervised User Profile Extraction from Twitter

#17 The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter

#18 Inferring User Political Preferences from Streaming Communications

#19 Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees

#20 Sparser, Better, Faster GPU Parsing

#21 Shift-Reduce CCG Parsing with a Dependency Model

#22 Less Grammar, More Features

#23 Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors

#24 Metaphor Detection with Cross-Lingual Model Transfer

#25 Learning Word Sense Distributions, Detecting Unattested Senses and Identifying Novel Senses Using Topic Models