Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detection
How much verified proof exists for this claim
One strong evidence source: arxiv
How intriguing or unexplained this claim is
The claim involves emerging research on biases in LLMs, with some uncertainties about their impact on financial misinformation detection. However, it is grounded in ongoing studies and does not present a highly speculative or deeply complex mystery.
Large language models (LLMs) have been widely applied across various domains of finance. Since their training data are largely derived from human-authored corpora, LLMs may inherit a range of human biases. Behavioral biases can lead to instability and uncertainty in decision-making, particularly when processing financial information. However, existing research on LLM bias has mainly focused on direct questioning or simplified, general-purpose settings, with limited consideration of the comple...