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cs.CL2026
Mechanism-Aligned Observability for Training Instability of Large Language Models
Ruixuan Huang, Yipei Wang, Hantao Huang +7
Frontier large language model training consumes massive accelerator fleets over long wall-clock times, making stability failures extremely costly. However, global symptoms such as…
cs.CL2026
Continual LLM Upcycling: A Predictor-Gated Bank-Wise Sparsity Training Recipe for Dense-to-Sparse LLMs
Ruixuan Huang, Jinyuan Shi, Hantao Huang +5
We study dense-to-sparse continual training as a way to construct channel-sparse large language models from dense checkpoints. Starting from a Qwen2.5-8B dense backbone, we continu…
cs.CL2025★ 1 cited
Seed-Coder: Let the Code Model Curate Data for Itself
ByteDance Seed, Yuyu Zhang, Jing Su +24
Code data in large language model (LLM) pretraining is recognized crucial not only for code-related tasks but also for enhancing general intelligence of LLMs. Current open-source L…