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cs.CL2024
A Comparative Study of Learning Paradigms in Large Language Models via Intrinsic Dimension
Saahith Janapati, Yangfeng Ji
The performance of Large Language Models (LLMs) on natural language tasks can be improved through both supervised fine-tuning (SFT) and in-context learning (ICL), which operate via…
cs.IR2024
Improve Temporal Awareness of LLMs for Sequential Recommendation
Zhendong Chu, Zichao Wang, Ruiyi Zhang +3
Large language models (LLMs) have demonstrated impressive zero-shot abilities in solving a wide range of general-purpose tasks. However, it is empirically found that LLMs fall shor…