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Found 6 papers, 4 papers with code
Diversified Multiple Instance Learning for Document-Level Multi-Aspect Sentiment Classification
To this end, we propose a novel Diversified Multiple Instance Learning Network (D-MILN), which is able to achieve aspect-level sentiment classification with only document-level weak supervision.
A Comparative Study between Full-Parameter and LoRA-based Fine-Tuning on Chinese Instruction Data for Instruction Following Large Language Model
In this study, we undertook experimental comparisons between full-parameter fine-tuning and LoRA-based tuning methods, utilizing LLaMA as the base model.
Towards Better Instruction Following Language Models for Chinese: Investigating the Impact of Training Data and Evaluation
Recently, significant public efforts have been directed towards developing low-cost models with capabilities akin to ChatGPT, thereby fostering the growth of open-source conversational models.
Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases
However current research rarely studies the impact of different amounts of instruction data on model performance, especially in the real-world use cases.
Exploring ChatGPT's Ability to Rank Content: A Preliminary Study on Consistency with Human Preferences
The results on the test set show that ChatGPT's ranking preferences are consistent with human to a certain extent.
To Answer or Not to Answer? Improving Machine Reading Comprehension Model with Span-based Contrastive Learning
Machine Reading Comprehension with Unanswerable Questions is a difficult NLP task, challenged by the questions which can not be answered from passages.
