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Cross-attentive MLLMs already solve the attribute-binding failures that cripple embedding models鈥攁nd distilling their soft multi-level ranking distributions via Rank-KL unlocks that reasoning for bi-encoders without degrading standard recall.
SkillComposer enables language models to self-evolve skills in real-time, achieving up to +4.5 improvements on agent tasks compared to larger models.
Forget multi-agent complexity: a single RL agent can outperform product-level baselines in persona-centric memory management for conversational AI.
