1 citations · 2 across the 12 of their papers we have counts for
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cs.LG2024★ 1 cited
Aligning Large Language Models and Geometric Deep Models for Protein Representation
Dong Shu, Bingbing Duan, Kai Guo +3
Latent representation alignment has become a foundational technique for constructing multimodal large language models (MLLM) by mapping embeddings from different modalities into a…
cs.CL2024
Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context Learning
Dong Shu, Mengnan Du
In-context learning can help Large Language Models (LLMs) to adapt new tasks without additional training. However, this performance heavily depends on the quality of the demonstrat…
cs.CL2024★ 1 cited
DemoShapley: Valuation of Demonstrations for In-Context Learning
Shan Xie, Man Luo, Chadly Daniel Stern +2
Large language models (LLMs) using in-context learning (ICL) excel in many tasks without task-specific fine-tuning. However, demonstration selection and ordering greatly impact ICL…