The Visual Dependency Representation (VDR) is an explicit model of the spatial relationships between objects in an image. In this paper we present an approach to training a VDR Pa...
Semantic role labeling (SRL) is crucial to natural language understanding as it identifies the predicate-argument structure in text with semantic labels. Unfortunately, resources...
Alan Akbik, Laura Chiticariu, Marina Danilevsky, Y...
We present a novel framework for machine translation evaluation using neural networks in a pairwise setting, where the goal is to select the better translation from a pair of hypo...
In this paper, we propose a syllable-based method for tweet normalization to study the cognitive process of non-standard word creation in social media. Assuming that syllable play...
Annotations are increasingly created and shared online and connected with web resources such as databases of real-world entities. Recent collaborative efforts to provide interoper...
Sampo Pyysalo, Jorge Campos, Juan Miguel Cejuela, ...
The recently proposed neural network joint model (NNJM) (Devlin et al., 2014) augments the n-gram target language model with a heuristically chosen source context window, achievin...
Fandong Meng, Zhengdong Lu, Mingxuan Wang, Hang Li...
In order to effectively utilize multiple datasets with heterogeneous annotations, this paper proposes a coupled sequence labeling model that can directly learn and infer two heter...
Zhenghua Li, Jiayuan Chao, Min Zhang, Wenliang Che...
Natural language generation of coherent long texts like paragraphs or longer documents is a challenging problem for recurrent networks models. In this paper, we explore an importa...
We present AutoExtend, a system to learn embeddings for synsets and lexemes. It is flexible in that it can take any word embeddings as input and does not need an additional train...