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cs.LG2026
Looped Reasoning Finishes Earlier Than You Think
Sumin Park, T. Konstantin Rusch
Looped reasoning with dynamic depth can be viewed as relaxation toward solution attractors in a learned dynamical landscape. In practice, however, latent trajectories often oscilla…
cs.AI2026
STAR: Rethinking MoE Routing as Structure-Aware Subspace Learning
Sumin Park, Noseong Park
Mixture-of-Experts (MoE) scales model capacity efficiently by selectively routing inputs to a specialized subset of experts. However, input-expert specialization, the core motivati…
cs.AI2026
Q-Delta: Beyond Key-Value Associative State Evolution
Sumin Park, Seojin Kim, Noseong Park
Linear attention reformulates sequence modeling as recurrent state evolution, enabling efficient linear-time inference. Under the key-value associative paradigm, existing approache…