Author

Xin-Yu Wang

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#artificial intelligence Preprint Sep 2026

FinInteract: Benchmarking Clarification and Intent Integration in Ambiguous Financial Question Answering

FinInteract, a bilingual (English/Chinese) benchmark of 173 instances that pairs each question with a default and an intended interpretation across a five-category ambiguity taxonomy, and grades whether an agent elicits the right clarification and then integrates it, finds that conditioning on the ambiguity category im...

Xin-Yu Wang, Tung Sum Thomas Kwok, Zhenghan Tai et al. · 0 citations

#artificial intelligence Preprint Sep 2026

FINSKILLOPS: A Self-Evolving Multi-Agent System for SEC Filing QA

Financial QA systems are typically improved before deployment through better retrieval, prompting, or agent coordination, leaving their reliability behavior fixed thereafter. In practice, new SEC-filing questions repeatedly expose heterogeneous errors in period, entity, evidence use, and calculation. Existing self-impr...

Yanzhang Ma, Zhenghan Tai, Han-Wei Wu et al. · 0 citations

Jul 2026

FinSAgent: Corpus-Aligned Multi-Agent RAG Framework for Evidence-Grounded SEC Filing Question Answering

FinSAgent is proposed, an evidence-grounded multi-agent framework that reframes SEC filing QA as corpus-aligned retrieval planning and corrects both ends with a single principle: inject corpus-side conditioning wherever model priors would otherwise dominate.

Jijun Chi, Zhenghan Tai, Han-Wei Wu et al. · arXiv.org · 0 citations