Scientific ideation is the capacity to formulate novel and testable hypotheses from scientific evidence, and autonomous AI scientists depend on it. Existing evaluations largely assess it by asking models to generate ideas from a static, curated set of reference papers. That passive setup departs from the retrieval-and-...
Yunxiang Mo, Tianshi ZHENG, Yi-Sen Gao et al.· 0 citations
Visual retrieval-augmented generation (RAG) commonly expands the retrieved evidence set to improve answer-page coverage, implicitly assuming that all available evidence should be passed to the generator. We show that this assumption does not hold for diffusion language models (DLMs): retrieving more pages increases ans...
Jiankun Wang, Yi-Sen Gao, Ziwei Zhang et al.· 0 citations
This work proposes MAFIA, a query-only Memory Attack framework via probing and Factual Injection against Audit, tailored to this extended threat model, and introduces a placement strategy that ensures retrieval-competitive injection via memory probing, budget allocation, and scheduling.
Jiamin Chen, Yi-Sen Gao, Yan-Ping Li et al.· 0 citations
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