21 citations · 44 across the 11 of their papers we have counts for
10 papers · 1 filter
Model Compression and Efficient Inference for Large Language Models: A Survey
Wenxiao Wang, Wei Chen, Yicong Luo +6
Transformer based large language models have achieved tremendous success. However, the significant memory and computational costs incurred during the inference process make it chal…
DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning
Wei Chen, Qiushi Wang, Zefei Long +8
We propose Multiple Experts Fine-tuning Framework to build a financial large language model (LLM), DISC-FinLLM. Our methodology improves general LLMs by endowing them with multi-tu…
DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultation
Zhijie Bao, Wei Chen, Shengze Xiao +6
We propose DISC-MedLLM, a comprehensive solution that leverages Large Language Models (LLMs) to provide accurate and truthful medical response in end-to-end conversational healthca…
Inducing Causal Structure for Abstractive Text Summarization
Lu Chen, Ruqing Zhang, Wei Huang +3
The mainstream of data-driven abstractive summarization models tends to explore the correlations rather than the causal relationships. Among such correlations, there can be spuriou…
KNSE: A Knowledge-aware Natural Language Inference Framework for Dialogue Symptom Status Recognition
Wei Chen, Shiqi Wei, Zhongyu Wei +1
Symptom diagnosis in medical conversations aims to correctly extract both symptom entities and their status from the doctor-patient dialogue. In this paper, we propose a novel fram…
Learning towards Selective Data Augmentation for Dialogue Generation
Xiuying Chen, Mingzhe Li, Jiayi Zhang +6
As it is cumbersome and expensive to acquire a huge amount of data for training neural dialog models, data augmentation is proposed to effectively utilize existing training samples…