Improving LLM-based Machine Translation with Systematic Self-Correction

1 code implementation • 26 Feb 2024 • Zhaopeng Feng, Yan Zhang, Hao Li, Wenqiang Liu, Jun Lang, Yang Feng, Jian Wu, Zuozhu Liu

Large Language Models (LLMs) have achieved impressive results in Machine Translation (MT).

Machine Translation Translation

DCR: Divide-and-Conquer Reasoning for Multi-choice Question Answering with LLMs

2 code implementations • 10 Jan 2024 • Zijie Meng, Yan Zhang, Zhaopeng Feng, Zuozhu Liu

Subsequently, we propose Filter Choices based Reasoning (FCR) to improve model performance on MCQs with low ($\mathcal{CS}$).

Question Answering

How Well Do Text Embedding Models Understand Syntax?

1 code implementation • 14 Nov 2023 • Yan Zhang, Zhaopeng Feng, Zhiyang Teng, Zuozhu Liu, Haizhou Li

Text embedding models have significantly contributed to advancements in natural language processing by adeptly capturing semantic properties of textual data.

Learning from Mixed Datasets: A Monotonic Image Quality Assessment Model

1 code implementation • 21 Sep 2022 • Zhaopeng Feng, Keyang Zhang, Shuyue Jia, Baoliang Chen, Shiqi Wang

Deep learning based image quality assessment (IQA) models usually learn to predict image quality from a single dataset, leading the model to overfit specific scenes.

Image Quality Assessment