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cs.LG2026
Ranking and Partitioning of Attention Heads for Sparse and Continual Reinforcement Learning Fine-tuning
Ruizhe Shi, Zaiwen Yang, Qiubo Wang +2
We study sparse and continual reinforcement learning fine-tuning of language models through attention-head ranking and partitioning. For sparse learning, we rank attention heads by…
cs.LG2026
On the Nonlinearity of Learning Rate Scaling for LLM Training
Zaiwen Yang, Huaqing Zhang, Jing Xu +1
Learning-rate transfer can reduce the cost of training large language models: instead of sweeping learning rates at target scale, practitioners extrapolate from smaller runs. Exist…
cs.LG2026
Position: The Inevitable End of One-Architecture-Fits-All-Domains in Time Series Forecasting
Qinwei Ma, Jingzhe Shi, Jiahao Qiu +1
Recent work has questioned the effectiveness and robustness of neural network architectures for time series forecasting tasks. We summarize these concerns and analyze groundly thei…