Real developer IDE traces differ substantially from LLM simulations in behavior and structure; current proactive assistants are unreliable on real traces, and simulated data cannot substitute for real data in training.
Propersim: Developing proactive and per- sonalized ai assistants through user-assistant simulation
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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2026 2representative citing papers
ICPT converts a few reference images of a personalized concept into an adaptive-length visual prompt plus a label embedding, letting a frozen LVLM add and reason about multiple concepts on the fly.
citing papers explorer
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An Empirical Study of Proactive Coding Assistants in Real-World Software Development
Real developer IDE traces differ substantially from LLM simulations in behavior and structure; current proactive assistants are unreliable on real traces, and simulated data cannot substitute for real data in training.
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Personalize Your Large Vision-language Models With In-context Prompt Tuning
ICPT converts a few reference images of a personalized concept into an adaptive-length visual prompt plus a label embedding, letting a frozen LVLM add and reason about multiple concepts on the fly.