3 papers
cs.CL2024
R4: Reinforced Retriever-Reorder-Responder for Retrieval-Augmented Large Language Models
Taolin Zhang, Dongyang Li, Qizhou Chen +5
Retrieval-augmented large language models (LLMs) leverage relevant content retrieved by information retrieval systems to generate correct responses, aiming to alleviate the halluci…
cs.IR2024
On the Role of Long-tail Knowledge in Retrieval Augmented Large Language Models
Dongyang Li, Junbing Yan, Taolin Zhang +5
Retrieval augmented generation (RAG) exhibits outstanding performance in promoting the knowledge capabilities of large language models (LLMs) with retrieved documents related to us…
cs.CL2024
DAFNet: Dynamic Auxiliary Fusion for Sequential Model Editing in Large Language Models
Taolin Zhang, Qizhou Chen, Dongyang Li +5
Recently, while large language models (LLMs) have demonstrated impressive results, they still suffer from hallucination, i.e., the generation of false information. Model editing is…