@inproceedings{jiang-etal-2026-glisters,
    title = "All That Glisters Is Not Gold: A Benchmark for Reference-Free Counterfactual Financial Misinformation Detection",
    author = "Jiang, Yuechen  and
      Liu, Zhiwei  and
      Cao, Yupeng  and
      He, Yueru  and
      Xu, Ziyang  and
      Xu, Chen  and
      Deng, Zhiyang  and
      Tiwari, Prayag  and
      Chen, Xi  and
      Lopez-Lira, Alejandro  and
      Huang, Jimin  and
      Tsujii, Junichi  and
      Ananiadou, Sophia",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.acl-long.492/",
    pages = "10737--10776",
    ISBN = "979-8-89176-390-6",
    abstract = "We introduce RFC-Bench, a benchmark for evaluating large language models on financial misinformation under realistic news. RFC-Bench operates at the paragraph level and captures the contextual complexity of financial news where meaning emerges from dispersed cues. The benchmark defines two complementary tasks: reference-free misinformation detection and comparison-based diagnosis using paired original{--}perturbed inputs. Experiments reveal a consistent pattern: performance is substantially stronger when comparative context is available, while reference-free settings expose significant weaknesses, including unstable predictions and elevated invalid outputs. These results indicate that current models struggle to maintain coherent belief states without external grounding. By highlighting this gap, RFC-Bench provides a structured testbed for studying reference-free reasoning and advancing more reliable financial misinformation detection in real-world settings."
}