2 citations · 3 across the 5 of their papers we have counts for
7 papers
Reasoning with Context Management and External Memory
Man-Ling Sung, William Hartmann, Jiangying Zhou
Reasoning models maintain information about the status of their reasoning process through in-context memory. Complex problems require larger context windows and memory requirements…
Multi-author style detection with stylistic embeddings
Man-Ling Sung, Chak Fai Li, Damianos Karakos +2
We investigate the use of Large Language Models (LLMs) in multi-author style change detection. Using off-the-shelf LLMs or supervised fine-tuning solely within the target domain fa…
Neural Network Conversion of Machine Learning Pipelines
Man-Ling Sung, Jan Silovsky, Man-Hung Siu +2
Transfer learning and knowledge distillation has recently gained a lot of attention in the deep learning community. One transfer approach, the student-teacher learning, has been sh…
Unsupervised Spoken Term Discovery on Untranscribed Speech
Man-Ling Sung
(Part of the abstract) In this thesis, we investigate the use of unsupervised spoken term discovery in tackling this problem. Unsupervised spoken term discovery aims to discover to…
Unsupervised Pattern Discovery from Thematic Speech Archives Based on Multilingual Bottleneck Features
Man-Ling Sung, Siyuan Feng, Tan Lee
The present study tackles the problem of automatically discovering spoken keywords from untranscribed audio archives without requiring word-by-word speech transcription by automati…
Unsupervised Spoken Term Discovery Based on Re-clustering of Hypothesized Speech Segments with Siamese and Triplet Networks
Man-Ling Sung, Tan Lee
Spoken term discovery from untranscribed speech audio could be achieved via a two-stage process. In the first stage, the unlabelled speech is decoded into a sequence of subword uni…
Towards a New Understanding of the Training of Neural Networks with Mislabeled Training Data
Herbert Gish, Jan Silovsky, Man-Ling Sung +3
We investigate the problem of machine learning with mislabeled training data. We try to make the effects of mislabeled training better understood through analysis of the basic mode…