3 papers
cs.LG2026
InfoMamba: An Attention-Free Hybrid Mamba-Transformer Model
Youjin Wang, Jiaqiao Zhao, Rong Fu +5
Balancing fine-grained local modeling with long-range dependency capture under computational constraints remains a central challenge in sequence modeling. While Transformers provid…
cs.LG2025
RLAX: Large-Scale, Distributed Reinforcement Learning for Large Language Models on TPUs
Runlong Zhou, Lefan Zhang, Shang-Chen Wu +29
Reinforcement learning (RL) has emerged as the de-facto paradigm for improving the reasoning capabilities of large language models (LLMs). We have developed RLAX, a scalable RL fra…
cs.LG2025
CASCADE Your Datasets for Cross-Mode Knowledge Retrieval of Language Models
Runlong Zhou, Yi Zhang
Language models often struggle with cross-mode knowledge retrieval -- the ability to access knowledge learned in one format (mode) when queried in another. We demonstrate that mode…