What Really Works for Universal Multimodal Embeddings? A Controlled Study of Contrastive Training Strategies Paper • 2610.15035 • Published 19 days ago • 17
Explaining the Roles of Experts in Mixture-of-Experts LLMs for Personalization Paper • 2610.22127 • Published 14 days ago • 5
Learning to Read Out: Unembedding Dynamics in Language Model Pretraining Paper • 2610.21025 • Published 15 days ago • 10
LEV: Thinking Fast and Deep with Looped Decision Models Paper • 2610.20951 • Published 15 days ago • 106
SpecMRL: Redesign Matryoshka Representation Learning within Parametric Spectrum Paper • 2610.26824 • Published 10 days ago • 89
Periodic Weak Spots: Phase Sensitivity from Chunked KV-Cache Compression Paper • 2609.36322 • Published Sep 28 • 120
Redesign Mixture-of-Experts Routers with Manifold Power Iteration Paper • 2606.12397 • Published Jun 10 • 91
Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings Paper • 2606.07502 • Published Jun 5 • 100
Coupling Experts and Routers in Mixture-of-Experts via an Auxiliary Loss Paper • 2512.23447 • Published Dec 29, 2025 • 100