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The results provide significant, multi-perspective evidence that social effects of data could be a causal driver of LLM capability decay in continual pre-training, thereby motivating routine"cognitive health checks" for deployed and evolving LLMs.
Across financial filings and earnings-call transcripts, it is found that LLM-based compression can produce fluent and factually plausible compressed contexts that nevertheless alter downstream decisions, suggesting that financial compression should be evaluated not only by efficiency or factuality, but also by its abil...
This paper presents the first systematic empirical study in the financial domain to characterize how an adversarial signal enters a multi-agent trading system and how far it survives toward the decision, and evaluates four communication topologies under data- and agent-level attacks.
Fund2Persona, a framework that builds financial-advisor personas from real-world fund disclosures and refines them through an actor-scorer-patcher loop, is proposed, suggesting that real fund data can bring manager-specific investment expertise to LLM advisors rather than merely changing an LLM's surface style.
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