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Mind2Dialogue introduces a psychology‑guided simulator that generates user mental states and uses privileged distillation to train LLM assistants on Oracle responses that know those states. The resulting models improve personalization and theory‑of‑mind metrics by up to 41 percentage points versus standard instruction‑tuned baselines.
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The paper studies long‑horizon memorization where a language model must learn 100 tasks via continual fine‑tuning without retaining data or task IDs. By composing data, function, and weight anchors with merged LoRA, they boost final retention from 1.2% to 34.9%, a 28× improvement.
Hugging Face Daily Papersarxiv.org1 minpaperHN2MLLMs Hallucinate when Information Distribution Drifts in Synergy Heads
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Hugging Face Daily Papersarxiv.org1 minpaperThere's no point at which turning your brain off will work
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