3 citations · 3 across the 12 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
Claw-R1: A Step-Level Data Middleware System for Agentic Reinforcement Learning
Daoyu Wang, Mingyue Cheng, Qingchuan Li +3
Agentic reinforcement learning (RL) has become an important post-training paradigm for turning LLMs from static chatbots into interactive agents, giving rise to representative appl…
cs.LG2026
CastFlow: Learning Role-Specialized Agentic Workflows for Time Series Forecasting
Bokai Pan, Mingyue Cheng, Zhiding Liu +6
Recently, large language models (LLMs) have shown great promise in time series forecasting. However, most existing LLM-based forecasting methods still follow a static generative pa…
cs.LG2026
MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning
Xiaoyu Tao, Mingyue Cheng, Ze Guo +4
Time series forecasting (TSF) plays a critical role in decision-making for many real-world applications. Recently, large language model (LLM)- based forecasters have made promising…