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Found 8 papers, 5 papers with code
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.
BEIKE NLP at SemEval-2022 Task 4: Prompt-Based Paragraph Classification for Patronizing and Condescending Language Detection
PCL detection task is aimed at identifying and categorizing language that is patronizing or condescending towards vulnerable communities in the general media. Compared to other NLP tasks of paragraph classification, the negative language presented in the PCL detection task is usually more implicit and subtle to be recognized, making the performance of common text-classification approaches disappointed.
Ranked #1 on
Multi-label Condescension Detection
on DPM
Binary Condescension Detection
Multi-Label Classification
+2
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.
Selective Attention Encoders by Syntactic Graph Convolutional Networks for Document Summarization
Abstractive text summarization is a challenging task, and one need to design a mechanism to effectively extract salient information from the source text and then generate a summary.
DELTA: A DEep learning based Language Technology plAtform
In this paper we present DELTA, a deep learning based language technology platform.
Ranked #3 on
Named Entity Recognition
on CoNLL 2003 (English)
