Optimizations for Large Language Models: Developing core technologies for enhancing the capabilities of large language models
Large language models (LLMs) are designed to handle and produce extensive natural language content. They develop an understanding of the structure, meaning, and knowledge embedded in human language datasets. Our focus includes three specific areas: (1) Fundamental technologies in Transformer-based LLMs, (2) Tailoring LLMs to specialized tasks, and (3) Refining methods for LLM agents.
Related Publications
[1] Haochen Zhang, Yuyang Dong, Chuan Xiao, Masafumi Oyamada. Jellyfish: Instruction-Tuning Local Large Language Models for Data Preprocessing. EMNLP 2024.
[2] Haochen Zhang, Yuyang Dong, Chuan Xiao, Masafumi Oyamada. Large Language Models as Data Preprocessors. TaDA 2024.
[2] Haochen Zhang, Yuyang Dong, Chuan Xiao, Masafumi Oyamada. Large Language Models as Data Preprocessors. TaDA 2024.
Funding
Consultation on the utilization of Large Language Models for data management challenges (NEC Corporation)
Consultation on the high performance and acceleration of Large Language Models (NEC Corporation)