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Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai Jiao Tong University
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LLMs' final layers might be holding your recommendation system back: representations from middle layers actually perform *better*, and a modular compression approach can unlock significant gains.
LMM-based GUI agents stick out like a sore thumb in human-centric mobile environments, but simple techniques can make them blend in without sacrificing utility.
Function calling gets a serious upgrade: a new reward model and inference scaling technique boosts performance by focusing on the *process* of tool use, not just the outcome.
Current LLM evaluation benchmarks often conflate chatbots and true AI agents, leading to misaligned research efforts, but this survey provides a framework for targeted evaluation based on environmental complexity and agent capabilities.