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cs.LG2026
STEM: Scaling Transformers with Embedding Modules
Ranajoy Sadhukhan, Sheng Cao, Harry Dong +5
Fine-grained sparsity promises higher parametric capacity without proportional per-token compute, but often suffers from training instability, load balancing, and communication ove…
cs.LG2025
Kinetics: Rethinking Test-Time Scaling Laws
Ranajoy Sadhukhan, Zhuoming Chen, Haizhong Zheng +3
We rethink test-time scaling laws from a practical efficiency perspective, revealing that the effectiveness of smaller models is significantly overestimated. Prior work, grounded i…