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cs.LG2026
Why Are Linear RNNs More Parallelizable?
William Merrill, Hongjian Jiang, Yanhong Li +2
The community is increasingly exploring linear RNNs (LRNNs) as language models, motivated by their expressive power and parallelizability. While prior work establishes the expressi…
cs.LG2025
How Instruction and Reasoning Data shape Post-Training: Data Quality through the Lens of Layer-wise Gradients
Ming Li, Yanhong Li, Ziyue Li +1
As the post-training of large language models (LLMs) advances from instruction-following to complex reasoning tasks, understanding how different data affect finetuning dynamics rem…