SOURCE-LINKED INTELLIGENCE
FinInteract: Benchmarking Clarification and Intent Integration in Ambiguous Financial Question Answering
Large language model agents increasingly answer financial questions by searching regulatory filings. Such questions are often deceptively under-specified: Meta Platforms' "operating income" is $46.75B consolidated but $62.87B for the Family of Apps segment, and each reading is exactly verifiable against the filing. A capable agent should recognize the ambiguity and ask, rather than commit to a plausible but unintended reading. Existing financial benchmarks cannot measure this, because one gold answer per question cannot separate agents that resolve the ambiguity from those that guess the commo
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-21T02:06:45.000Z
First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.