9 citations · 10 across the 6 of their papers we have counts for
6 papers · 1 filter
Boosting Natural Language Generation from Instructions with Meta-Learning
Budhaditya Deb, Guoqing Zheng, Ahmed Hassan Awadallah
Recent work has shown that language models (LMs) trained with multi-task \textit{instructional learning} (MTIL) can solve diverse NLP tasks in zero- and few-shot settings with impr…
A Conditional Generative Matching Model for Multi-lingual Reply Suggestion
Budhaditya Deb, Guoqing Zheng, Milad Shokouhi +1
We study the problem of multilingual automated reply suggestions (RS) model serving many languages simultaneously. Multilingual models are often challenged by model capacity and se…
An Exploratory Study on Long Dialogue Summarization: What Works and What's Next
Yusen Zhang, Ansong Ni, Tao Yu +6
Dialogue summarization helps readers capture salient information from long conversations in meetings, interviews, and TV series. However, real-world dialogues pose a great challeng…
Language Scaling for Universal Suggested Replies Model
Qianlan Ying, Payal Bajaj, Budhaditya Deb +7
We consider the problem of scaling automated suggested replies for Outlook email system to multiple languages. Faced with increased compute requirements and low resources for langu…
A Dataset and Baselines for Multilingual Reply Suggestion
Mozhi Zhang, Wei Wang, Budhaditya Deb +3
Reply suggestion models help users process emails and chats faster. Previous work only studies English reply suggestion. Instead, we present MRS, a multilingual reply suggestion da…
Diversifying Reply Suggestions using a Matching-Conditional Variational Autoencoder
Budhaditya Deb, Peter Bailey, Milad Shokouhi
We consider the problem of diversifying automated reply suggestions for a commercial instant-messaging (IM) system (Skype). Our conversation model is a standard matching based info…