Papers by Yukun Ma

2 papers
MulCode: A Multiplicative Multi-way Model for Compressing Neural Language Model (D19-1)

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Challenge: a large number of parameters dominate the memory usage of deep neural nets . compression of embedding layers is the key to reducing memory usage .
Approach: They propose a multi-way multiplicative neural compressor to compress embedding layers . they use an adaptively created matrix and multiplicativative compositions to learn them .
Outcome: a new multi-way multiplicative neural compressor can achieve 41.38 times compression rate with little loss in performance.
Ditto: A Simple and Efficient Approach to Improve Sentence Embeddings (2023.emnlp-main)

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Challenge: Prior studies diagnose the anisotropy problem in sentence embeddings from pre-trained language models without fine-tuning.
Approach: They propose an unsupervised method that weights words with model-based importance estimations and computes the weighted average of word representations from pre-trained models as sentence embeddings.
Outcome: Empirical evaluations show that the proposed method can alleviate the anisotropy problem and improve various pre-trained models on the STS benchmarks.

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