Challenges in building intelligent open-domain dialog systems

M Huang, X Zhu, J Gao - ACM Transactions on Information Systems …, 2020 - dl.acm.org
There is a resurgent interest in developing intelligent open-domain dialog systems due to
the availability of large amounts of conversational data and the recent progress on neural …

A comprehensive review of computational methods for drug-drug interaction detection

Y Qiu, Y Zhang, Y Deng, S Liu… - IEEE/ACM transactions …, 2021 - ieeexplore.ieee.org
The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance,
which provides effective and safe co-prescriptions of multiple drugs. Since laboratory …

Is ChatGPT a general-purpose natural language processing task solver?

C Qin, A Zhang, Z Zhang, J Chen, M Yasunaga… - arXiv preprint arXiv …, 2023 - arxiv.org
Spurred by advancements in scale, large language models (LLMs) have demonstrated the
ability to perform a variety of natural language processing (NLP) tasks zero-shot--ie, without …

Conversational information seeking

H Zamani, JR Trippas, J Dalton… - … and Trends® in …, 2023 - nowpublishers.com
Conversational information seeking (CIS) is concerned with a sequence of interactions
between one or more users and an information system. Interactions in CIS are primarily …

Attention, please! A survey of neural attention models in deep learning

A de Santana Correia, EL Colombini - Artificial Intelligence Review, 2022 - Springer
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Natural language processing advancements by deep learning: A survey

A Torfi, RA Shirvani, Y Keneshloo, N Tavaf… - arXiv preprint arXiv …, 2020 - arxiv.org
Natural Language Processing (NLP) helps empower intelligent machines by enhancing a
better understanding of the human language for linguistic-based human-computer …

The second conversational intelligence challenge (convai2)

E Dinan, V Logacheva, V Malykh, A Miller… - The NeurIPS'18 …, 2020 - Springer
We describe the setting and results of the ConvAI2 NeurIPS competition that aims to further
the state-of-the-art in open-domain chatbots. Some key takeaways from the competition …

Knowledge-enriched transformer for emotion detection in textual conversations

P Zhong, D Wang, C Miao - arXiv preprint arXiv:1909.10681, 2019 - arxiv.org
Messages in human conversations inherently convey emotions. The task of detecting
emotions in textual conversations leads to a wide range of applications such as opinion …

ConveRT: Efficient and accurate conversational representations from transformers

M Henderson, I Casanueva, N Mrkšić, PH Su… - arXiv preprint arXiv …, 2019 - arxiv.org
General-purpose pretrained sentence encoders such as BERT are not ideal for real-world
conversational AI applications; they are computationally heavy, slow, and expensive to train …

Proactive human-machine conversation with explicit conversation goals

W Wu, Z Guo, X Zhou, H Wu, X Zhang, R Lian… - arXiv preprint arXiv …, 2019 - arxiv.org
Though great progress has been made for human-machine conversation, current dialogue
system is still in its infancy: it usually converses passively and utters words more as a matter …