Most of the existing point-to-mesh distance query solvers, such as Proxi...
Membership inference attack is one of the most popular privacy attacks i...
Standard decoding approaches for conditional text generation tasks typic...
In recent years, REST API fuzzing has emerged to explore errors on a clo...
Currently, the development of IoT firmware heavily depends on third-part...
Modern natural language generation paradigms require a good decoding str...
Performance of spoken language understanding (SLU) can be degraded with
...
Automated algorithm configuration relieves users from tedious,
trial-and...
Recently, numerous efficient Transformers have been proposed to reduce t...
The propensity of abstractive summarization systems to make factual erro...
Neural text generation models like those used for summarization and
tran...
Pre-trained language models (e.g. BART) have shown impressive results wh...
A reader interested in a particular topic might be interested in summari...
Disfluencies is an under-studied topic in NLP, even though it is ubiquit...
Despite the prominence of neural abstractive summarization models, we kn...
Compressive summarization systems typically rely on a crafted set of
syn...
An advantage of seq2seq abstractive summarization models is that they
ge...
Recently BERT has been adopted in state-of-the-art text summarization mo...
Recent neural network approaches to summarization are largely either
sen...
A hallmark of variational autoencoders (VAEs) for text processing is the...
Generating plausible and fluent sentence with desired properties has lon...
The objective of knowledge graph embedding is to encode both entities an...
Recently, neural networks have achieved great success on sentiment
class...