9 citations · 9 across the 9 of their papers we have counts for
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cs.LG2024★ 9 cited
GraphTool-Instruction: Revolutionizing Graph Reasoning in LLMs through Decomposed Subtask Instruction
Rongzheng Wang, Shuang Liang, Qizhi Chen +2
Large language models (LLMs) have been demonstrated to possess the capabilities to understand fundamental graph properties and address various graph reasoning tasks. Existing metho…
cs.AI2024
MuAP: Multi-step Adaptive Prompt Learning for Vision-Language Model with Missing Modality
Ruiting Dai, Yuqiao Tan, Lisi Mo +3
Recently, prompt learning has garnered considerable attention for its success in various Vision-Language (VL) tasks. However, existing prompt-based models are primarily focused on…