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cs.LG2026
X-MoD: Practical Scaling Laws for Sparse-Depth Routing Beyond Mixture-of-Depths
Bowen Dong, Yilong Fan, Tengyu Pan +6
Mixture-of-Depths (MoD) enables conditional computation across Transformer depth by routing only a subset of tokens through selected layers, but its original one-sparse--one-dense…
cs.CL2026
CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution
Teng Pan, Yuchen Yan, Zixuan Wang +6
Label-free reinforcement learning enables large language models to improve reasoning capabilities without ground-truth supervision, typically by treating majority-voted answers as…