Text summarization is the process of automatically creating a shorter version of one or more
text documents. It is an important way of finding relevant information in large text libraries or …

Recent work has shown success in using neural network language models (NNLMs) as
features in MT systems. Here, we present a novel formulation for a neural network joint …

Large models, encompassing large language and diffusion models, have shown
exceptional promise in approximating human-level intelligence, garnering significant …

This work focuses on robust speech recognition in air traffic control (ATC) by designing a
novel processing paradigm to integrate multilingual speech recognition into a single …

In silico prediction of self-interacting proteins (SIPs) has become an important part of
proteomics. There is an urgent need to develop effective and reliable prediction methods to …

The use of conventional maximum likelihood estimates hinders the performance of existing
phrase-based translation models. For lack of sufficient training data, most models only …

While vision transformers have been highly successful in improving the performance in
image-based tasks, not much work has been reported on applying transformers to scene text …

How to aggregate multi-view representations of a 3D object into an informative and
discriminative one remains a key challenge for multi-view 3D object retrieval. Existing …

We present a novel machine translation model which models translation by a linear
sequence of operations. In contrast to the “N-gram” model, this sequence includes not only …

Digitized learning materials are a core part of modern education, and analysis of the use can
offer insight into the learning behavior of high and low performing students. The topic of …