28 citations · 28 across the 6 of their papers we have counts for
6 papers
Self-Supervised Audio-and-Text Pre-training with Extremely Low-Resource Parallel Data
Yu Kang, Tianqiao Liu, Hang Li +2
Multimodal pre-training for audio-and-text has recently been proved to be effective and has significantly improved the performance of many downstream speech understanding tasks. Ho…
Formula graph self-attention network for representation-domain independent materials discovery
Achintha Ihalage, Yang Hao
The success of machine learning (ML) in materials property prediction depends heavily on how the materials are represented for learning. Two dominant families of material descripto…
Temporal-aware Language Representation Learning From Crowdsourced Labels
Yang Hao, Xiao Zhai, Wenbiao Ding +1
Learning effective language representations from crowdsourced labels is crucial for many real-world machine learning tasks. A challenging aspect of this problem is that the quality…
A Multimodal Machine Learning Framework for Teacher Vocal Delivery Evaluation
Hang Li, Yu Kang, Yang Hao +3
The quality of vocal delivery is one of the key indicators for evaluating teacher enthusiasm, which has been widely accepted to be connected to the overall course qualities. Howeve…
Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models
Yang Hao, Hang Li, Wenbiao Ding +4
In this work, we study computational approaches to detect online dialogic instructions, which are widely used to help students understand learning materials, and build effective st…
NeuCrowd: Neural Sampling Network for Representation Learning with Crowdsourced Labels
Yang Hao, Wenbiao Ding, Zitao Liu
Representation learning approaches require a massive amount of discriminative training data, which is unavailable in many scenarios, such as healthcare, smart city, education, etc.…