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cs.LG2026
LLMZero: Discovering Adaptive Training Strategies for RL Post-Training via LLM Agents
Haoyang Fang, Wei Zhu, Boran Han +11
RL post-training strategies are dataset-dependent and reveal a recurring empirical pattern: capacity parameters accumulate monotonically across stages, while regularization paramet…
cs.LG2026
Attention Sinks and Outliers in Attention Residuals
Haozheng Luo, Haoran Dai, Shaoyang Zhang +10
We propose OASIS, an outlier- and sink-aware method that stabilizes dual-normalized attention-residual architectures through explicit null routing and token-to-depth null coupling.…
cs.LG2024★ 1 cited
HeteGraph-Mamba: Heterogeneous Graph Learning via Selective State Space Model
Zhenyu Pan, Yoonsung Jeong, Xiaoda Liu +1
We propose a heterogeneous graph mamba network (HGMN) as the first exploration in leveraging the selective state space models (SSSMs) for heterogeneous graph learning. Compared wit…