Papers by Honghong Zhao

2 papers
BERT-EMD: Many-to-Many Layer Mapping for BERT Compression with Earth Mover’s Distance (2020.emnlp-main)

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Challenge: Pre-trained language models have been proposed and applied to many NLP tasks, yielding state-of-the-art performance, but high storage and computational costs obstruct them to be effectively deployed on resource-constrained devices and real-time applications.
Approach: They propose a BERT distillation method which allows each intermediate student layer to learn from any intermediate teacher layers.
Outcome: The proposed method can learn from different teacher layers adaptively for different NLP tasks.
SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model (2024.emnlp-demo)

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Challenge: Large language models (LLMs) have shown remarkable achievements across various language tasks.
Approach: They propose a scientific literature LLM and a knowledge service system based on it . they collect scientific literature and then pre-train it using autoregressive training .
Outcome: The proposed system provides literature investigation, paper reading, and academic writing functions.

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