37 citations · 129 across the 23 of their papers we have counts for
5 papers · 1 filter
A Survey on Efficient Large Language Model Training: From Data-centric Perspectives
Junyu Luo, Bohan Wu, Xiao Luo +8
Post-training of Large Language Models (LLMs) is crucial for unlocking their task generalization potential and domain-specific capabilities. However, the current LLM post-training…
Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation
Junyu Luo, Yuhao Tang, Yiwei Fu +6
Unsupervised Graph Domain Adaptation (UGDA) leverages labeled source domain graphs to achieve effective performance in unlabeled target domains despite distribution shifts. However…
MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning
Yusheng Zhao, Xiao Luo, Weizhi Zhang +4
The ability to reason is one of the most fundamental capabilities of large language models (LLMs), enabling a wide range of downstream tasks through sophisticated problem-solving.…
Cross-Domain Diffusion with Progressive Alignment for Efficient Adaptive Retrieval
Junyu Luo, Yusheng Zhao, Xiao Luo +5
Unsupervised efficient domain adaptive retrieval aims to transfer knowledge from a labeled source domain to an unlabeled target domain, while maintaining low storage cost and high…
Dynamic Bundling with Large Language Models for Zero-Shot Inference on Text-Attributed Graphs
Yusheng Zhao, Qixin Zhang, Xiao Luo +5
Large language models (LLMs) have been used in many zero-shot learning problems, with their strong generalization ability. Recently, adopting LLMs in text-attributed graphs (TAGs)…