activity
20192022
most citedSpeaker attribution with voice profiles by graph-based semi-supervised learning

12 citations · 31 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IT2022

How to Minimize the Weighted Sum AoI in Multi-Source Status Update Systems: OMA or NOMA?

Jixuan Wang, Deli Qiao

In this paper, the minimization of the weighted sum average age of information (AoI) in a multi-source status update communication system is studied. Multiple independent sources s…

cs.CL2022

On the data requirements of probing

Zining Zhu, Jixuan Wang, Bai Li +1

As large and powerful neural language models are developed, researchers have been increasingly interested in developing diagnostic tools to probe them. There are many papers with c…

eess.AS202112 cited

Speaker attribution with voice profiles by graph-based semi-supervised learning

Jixuan Wang, Xiong Xiao, Jian Wu +3

Speaker attribution is required in many real-world applications, such as meeting transcription, where speaker identity is assigned to each utterance according to speaker voice prof…

cs.AI20204 cited

Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling

Jixuan Wang, Kai Wei, Martin Radfar +2

We propose a novel Transformer encoder-based architecture with syntactical knowledge encoded for intent detection and slot filling. Specifically, we encode syntactic knowledge into…

eess.AS2020

Speaker diarization with session-level speaker embedding refinement using graph neural networks

Jixuan Wang, Xiong Xiao, Jian Wu +3

Deep speaker embedding models have been commonly used as a building block for speaker diarization systems; however, the speaker embedding model is usually trained according to a gl…

cs.LG20195 cited

Training without training data: Improving the generalizability of automated medical abbreviation disambiguation

Marta Skreta, Aryan Arbabi, Jixuan Wang +1

Abbreviation disambiguation is important for automated clinical note processing due to the frequent use of abbreviations in clinical settings. Current models for automated abbrevia…