Joint Optimization

System combination has emerged as a powerful method for machine translation (MT). This paper pursues a joint optimization strategy for combining outputs from multiple MT systems, where word alignment, ordering, …...

Part-of-speech (POS) is an indispensable fea- ture in dependency parsing. Current research usually models POS tagging and dependency parsing independently. This may suffer from error propagation problem. Our experiments show …...

Recent study shows that parsing accuracy can be largely improved by the joint optimization of part-of-speech (POS) tagging and dependency parsing. However, the POS tagging task does not benefit much …...

We propose NEURAL ENQUIRER — a neu- ral network architecture for answering natural language (NL) questions given a knowledge base (KB) table. Unlike previous work on end-to-end training of semantic …...

AbstractIn this paper, we propose an extractive multi-document summarization (MDS) system using joint optimization and active learning for content selection grounded in user feedback. Our method interactively obtains user feedback …...

AbstractExisting approaches to active learning maximize the system performance by sampling unlabeled instances for annotation that yield the most efficient training. However, when active learning is integrated with an end-user …...

AbstractWord embedding learning is the task to map each word into a low-dimensional and continuous vector based on a large corpus. To enhance corpus based word embedding models, researchers utilize …...

AbstractWe study knowledge-grounded dialogue generation with pre-trained language models. To leverage the redundant external knowledge under capacity constraint, we propose equipping response generation defined by a pre-trained language model with …...

Since traditional tokenizers are isolated from a downstream task and model, they cannot out- put an appropriate tokenization depending on the task and model, although recent studies im- ply that …...

AbstractMulti-hop reasoning requires aggregating multiple documents to answer a complex question. Existing methods usually decompose the multi-hop question into simpler single-hop questions to solve the problem for illustrating the explainable …...