Framing is a sophisticated form of discourse in which the speaker tries to induce a cognitive bias through consistent linkage between a topic and a specific context (frame). We b...
Precisely evaluating the quality of a translation against human references is a challenging task due to the flexible word ordering of a sentence and the existence of a large numb...
Understanding open-domain text is one of the primary challenges in NLP. Machine comprehension evaluates the system’s ability to understand text through a series of question-answ...
Mrinmaya Sachan, Kumar Dubey, Eric P. Xing, Matthe...
Languages using Chinese characters are mostly processed at word level. Inspired by recent success of deep learning, we delve deeper to character and radical levels for Chinese lan...
Coverage maximization with bigram concepts is a state-of-the-art approach to unsupervised extractive summarization. It has been argued that such concepts are adequate and, in cont...
This paper considers the problem of embedding Knowledge Graphs (KGs) consisting of entities and relations into lowdimensional vector spaces. Most of the existing methods perform t...
In this paper, we apply the concept of pretraining to hidden-unit conditional random fields (HUCRFs) to enable learning on unlabeled data. We present a simple yet effective pre-t...
Social media has attracted attention because of its potential for extraction of information of various types. For example, information collected from Twitter enables us to build u...
Automatic resolution of Crossword Puzzles (CPs) heavily depends on the quality of the answer candidate lists produced by a retrieval system for each clue of the puzzle grid. Previ...
Kernel-based learning algorithms have been shown to achieve state-of-the-art results in many Natural Language Processing (NLP) tasks. We present KELP, a Java framework that suppor...
Simone Filice, Giuseppe Castellucci, Danilo Croce,...