State of the Art Model

We present a novel method for jointly learning compositional and non- compositional phrase embeddings by adaptively weighting both types of em- beddings using a compositionality scoring function. The scoring function …...

AbstractSpoken language understanding (SLU) is an essential component in conversational systems. Most SLU components treats each utterance independently, and then the following components aggregate the multi-turn information in the separate …...

AbstractRecently, neural machine translation (NMT) has emerged as a powerful alternative to conventional statistical approaches. However, its performance drops considerably in the presence of morphologically rich languages (MRLs). Neural engines …...

AbstractMost modern Information Extraction (IE) systems are implemented as sequential taggers and only model local dependencies. Non-local and non-sequential context is, however, a valuable source of information to improve predictions. …...

AbstractDiscourse relation identification has been an active area of research for many years, and the challenge of identifying implicit relations remains largely an unsolved task, especially in the context of …...

AbstractMultilayer architectures are currently the gold standard for large-scale neural machine translation. Existing works have explored some methods for understanding the hidden representations, however, they have not sought to improve …...

AbstractInformation extraction from unstructured texts plays a vital role in the field of natural language processing. Although there has been extensive research into each information extraction task (i.e., entity linking, …...

AbstractText-based games present a unique challenge for autonomous agents to operate in natural language and handle enormous action spaces. In this paper, we propose the Contextual Action Language Model (CALM) …...

AbstractRecent work in cross-topic argument mining attempts to learn models that generalise across topics rather than merely relying on within-topic spurious correlations. We examine the effectiveness of this approach by …...

AbstractEvent factuality indicates the degree of certainty about whether an event occurs in the real world. Existing studies mainly focus on identifying event factuality at sentence level, which easily leads …...

AbstractMost existing reading comprehension datasets focus on single-span answers, which can be extracted as a single contiguous span from a given text passage. Multi-span questions, i.e., questions whose answer is …...

AbstractEvent temporal relation extraction (ETRE) is usually formulated as a multi-label classification task, where each type of relation is simply treated as a one-hot label. This formulation ignores the meaning …...