3 papers
cs.CL2023
Resprompt: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models
Song Jiang, Zahra Shakeri, Aaron Chan +8
Chain-of-thought (CoT) prompting, which offers step-by-step problem-solving rationales, has impressively unlocked the reasoning potential of large language models (LLMs). Yet, the…
cs.LG2023
On the Equivalence of Graph Convolution and Mixup
Xiaotian Han, Hanqing Zeng, Yu Chen +9
This paper investigates the relationship between graph convolution and Mixup techniques. Graph convolution in a graph neural network involves aggregating features from neighboring…
cs.CL2023
LLM-Rec: Personalized Recommendation via Prompting Large Language Models
Hanjia Lyu, Song Jiang, Hanqing Zeng +7
Text-based recommendation holds a wide range of practical applications due to its versatility, as textual descriptions can represent nearly any type of item. However, directly empl…