4 papers
Rethinking Fairness in LLM-Based Recommender Systems: A Survey
Song-Duo Ma, Chu-Yun Chen, Bang-An Li +3
Large Language Models (LLMs) are reshaping recommender systems by enabling more semantic, generative, and interactive recommendation pipelines. However, this shift also introduces…
RADAR: Retrieval-Augmented Detector with Adversarial Refinement for Robust Fake News Detection
Song-Duo Ma, Yi-Hung Liu, Hsin-Yu Lin +4
To efficiently combat the spread of LLM-generated misinformation, we present RADAR, a Retrieval-Augmented Detector with Adversarial Refinement for robust fake news detection. Our a…
The Role of Exploration Modules in Small Language Models for Knowledge Graph Question Answering
Yi-Jie Cheng, Oscar Chew, Yun-Nung Chen
Integrating knowledge graphs (KGs) into the reasoning processes of large language models (LLMs) has emerged as a promising approach to mitigate hallucination. However, existing wor…
LLM Inference Enhanced by External Knowledge: A Survey
Yu-Hsuan Lin, Qian-Hui Chen, Yi-Jie Cheng +4
Recent advancements in large language models (LLMs) have enhanced natural-language reasoning. However, their limited parametric memory and susceptibility to hallucination present p…