Songlin Jiang
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| title | conference | date |
|---|---|---|
| Optimizing Reinforcement Learning at Trillion-Parameter Scale | PyTorch Conference Europe 2026 | 2026-04-07 |
Trillion-parameter MoE reasoning model with 384 experts and ~32.6B active parameters per token trains using LoRA adapters (rank 32 across all linear layers) so… | ||
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