14 citations · 28 across the 10 of their papers we have counts for
4 papers · 1 filter
A Survey of Small Language Models
Chien Van Nguyen, Xuan Shen, Ryan Aponte +25
Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, maki…
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation
Junda Wu, Cheng-Chun Chang, Tong Yu +4
The long-tail recommendation is a challenging task for traditional recommender systems, due to data sparsity and data imbalance issues. The recent development of large language mod…
Large Language Models and Causal Inference in Collaboration: A Survey
Xiaoyu Liu, Paiheng Xu, Junda Wu +10
Causal inference has shown potential in enhancing the predictive accuracy, fairness, robustness, and explainability of Natural Language Processing (NLP) models by capturing causal…
InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment
Jianing Wang, Junda Wu, Yupeng Hou +3
Do current large language models (LLMs) better solve graph reasoning and generation tasks with parameter updates? In this paper, we propose InstructGraph, a framework that empowers…