7 citations · 11 across the 10 of their papers we have counts for
10 papers
Transfer Learning Enhanced Single-choice Decision for Multi-choice Question Answering
Chenhao Cui, Yufan Jiang, Shuangzhi Wu +1
Multi-choice Machine Reading Comprehension (MMRC) aims to select the correct answer from a set of options based on a given passage and question. The existing methods employ the pre…
Code Comparison Tuning for Code Large Language Models
Yufan Jiang, Qiaozhi He, Xiaomin Zhuang +1
We present Code Comparison Tuning (CCT), a simple and effective tuning method for code large language models (Code LLMs) to better handle subtle code errors. Specifically, we integ…
RecycleGPT: An Autoregressive Language Model with Recyclable Module
Yufan Jiang, Qiaozhi He, Xiaomin Zhuang +4
Existing large language models have to run K times to generate a sequence of K tokens. In this paper, we present RecycleGPT, a generative language model with fast decoding speed by…
Soft Language Clustering for Multilingual Model Pre-training
Jiali Zeng, Yufan Jiang, Yongjing Yin +5
Multilingual pre-trained language models have demonstrated impressive (zero-shot) cross-lingual transfer abilities, however, their performance is hindered when the target language…
DialogQAE: N-to-N Question Answer Pair Extraction from Customer Service Chatlog
Xin Zheng, Tianyu Liu, Haoran Meng +6
Harvesting question-answer (QA) pairs from customer service chatlog in the wild is an efficient way to enrich the knowledge base for customer service chatbots in the cold start or…
Contrastive Learning with Prompt-derived Virtual Semantic Prototypes for Unsupervised Sentence Embedding
Jiali Zeng, Yongjing Yin, Yufan Jiang +2
Contrastive learning has become a new paradigm for unsupervised sentence embeddings. Previous studies focus on instance-wise contrastive learning, attempting to construct positive…
DualNER: A Dual-Teaching framework for Zero-shot Cross-lingual Named Entity Recognition
Jiali Zeng, Yufan Jiang, Yongjing Yin +3
We present DualNER, a simple and effective framework to make full use of both annotated source language corpus and unlabeled target language text for zero-shot cross-lingual named…
An Efficient Coarse-to-Fine Facet-Aware Unsupervised Summarization Framework based on Semantic Blocks
Xinnian Liang, Jing Li, Shuangzhi Wu +4
Unsupervised summarization methods have achieved remarkable results by incorporating representations from pre-trained language models. However, existing methods fail to consider ef…
Task-guided Disentangled Tuning for Pretrained Language Models
Jiali Zeng, Yufan Jiang, Shuangzhi Wu +2
Pretrained language models (PLMs) trained on large-scale unlabeled corpus are typically fine-tuned on task-specific downstream datasets, which have produced state-of-the-art result…
Improving Machine Reading Comprehension with Single-choice Decision and Transfer Learning
Yufan Jiang, Shuangzhi Wu, Jing Gong +5
Multi-choice Machine Reading Comprehension (MMRC) aims to select the correct answer from a set of options based on a given passage and question. Due to task specific of MMRC, it is…