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20212023
most citedONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models

9 citations · 15 across the 8 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.SE2023★ 2 cited

TransCoder: Towards Unified Transferable Code Representation Learning Inspired by Human Skills

Qiushi Sun, Nuo Chen, Jianing Wang +2

Code pre-trained models (CodePTMs) have recently demonstrated a solid capacity to process various software intelligence tasks, e.g., code clone detection, code translation, and cod…

cs.CL2023

When Gradient Descent Meets Derivative-Free Optimization: A Match Made in Black-Box Scenario

Chengcheng Han, Liqing Cui, Renyu Zhu +5

Large pre-trained language models (PLMs) have garnered significant attention for their versatility and potential for solving a wide spectrum of natural language processing (NLP) ta…

cs.CL2023★ 3 cited

Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives

Qiushi Sun, Chengcheng Han, Nuo Chen +4

Large language models (LLMs) have shown increasing power on various natural language processing (NLP) tasks. However, tuning these models for downstream tasks usually needs exorbit…

cs.IR2023★ 9 cited

ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models

Qijiong Liu, Nuo Chen, Tetsuya Sakai +1

Personalized content-based recommender systems have become indispensable tools for users to navigate through the vast amount of content available on platforms like daily news websi…

cs.CL2023

HugNLP: A Unified and Comprehensive Library for Natural Language Processing

Jianing Wang, Nuo Chen, Qiushi Sun +3

In this paper, we introduce HugNLP, a unified and comprehensive library for natural language processing (NLP) with the prevalent backend of HuggingFace Transformers, which is desig…