48 citations · 50 across the 3 of their papers we have counts for
3 papers
cs.CL2024
CoBa: Convergence Balancer for Multitask Finetuning of Large Language Models
Zi Gong, Hang Yu, Cong Liao +3
Multi-task learning (MTL) benefits the fine-tuning of large language models (LLMs) by providing a single model with improved performance and generalization ability across tasks, pr…
cs.CL2024★ 2 cited
SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy
Tingkai Zhang, Chaoyu Chen, Cong Liao +6
Text-to-SQL conversion is a critical innovation, simplifying the transition from complex SQL to intuitive natural language queries, especially significant given SQL's prevalence in…
cs.LG2022★ 48 cited
A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud
Siqiao Xue, Chao Qu, Xiaoming Shi +11
Predictive autoscaling (autoscaling with workload forecasting) is an important mechanism that supports autonomous adjustment of computing resources in accordance with fluctuating w…