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A self-evolving memory paradigm for generative recommendation is proposed, aiming to enable effective evolution across heterogeneous behavioral patterns, and three key principles for effective self-evolving recommendation systems are identified, including isolated memorization, reinforced evolution, and scalable applic...
A novel set identifier paradigm is introduced, representing each item as a set of order-agnostic tokens, which proves SETRec’s superior efficiency and scalability on cold-start items as model sizes increase, and SETRec++’s potential in the scalability of order-agnostic identifier.
FinDeepIndicator is proposed, the first benchmark dedicated to evaluating Deep Research agents in end-to-end financial indicator construction, and covers fundamental, technical, and macroeconomic indicators organized into 21 fine-grained sub-categories.
DASH is a decision-aware user simulator that jointly generates thinking traces and predicts behavioral actions from heterogeneous cross-domain histories and tailors a rubric-based reward model that evaluates thinking traces along form, content, and logic for RL training.
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