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Tencent *Equal contribution.
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Memory optimization that prioritizes belief clarity over mere outcome success can radically enhance long-horizon reasoning in LLMs.
User corrections of AI agents are a goldmine: Echo shows how to automatically transform these noisy interactions into a 10% absolute improvement in code completion acceptance rates.
Quantizing user preferences into discrete tokens unlocks personalized multimodal content generation with improved consistency between modalities.
Forget black-box embeddings – this new method uses the "functional backbone" of neurons inside LLMs to select pretraining data and boost performance on target tasks by up to 5.3%.
