品牌即记忆：视觉语言模型为新闻来源编码因果性、可机制定位的可信度先验
Brand-as-Memory: Vision-Language Models Encode Causal, Mechanistically Localizable Credibility Priors for News Sources
AI总结：
研究视觉语言模型中基于媒体身份的来源可信度先验，通过交叉模型基准测试和机制分析，揭示其特性及影响，如模型和规模依赖性、因果形成机制等。
摘要：
视觉语言模型（VLMs）越来越多地将新闻和网络内容视为图像，其中发布者身份直观呈现。我们表明VLMs带有基于媒体身份的强大来源可信度先验，并从三个方面进行研究。（i）交叉模型基准测试……我们发布了刺激套件和CueTrust。
英文摘要：
Vision-language models (VLMs) increasingly read news and web content as images, where the publisher's identity is visually present. We show that VLMs carry a strong source-credibility prior keyed on outlet identity, and study it along three axes. (i) Cross-model benchmark. We introduce CueTrust, a cross-model diagnostic that measures which surface source cue overrides an article's content evidence via a Source-Override Index (SOI). Across seven VLMs and five cues, the vulnerability profile is model- and scale-dependent, and the override is outlet-identity-specific and encoding-invariant, firing from the masthead name, the logo image, or the bare domain, but not from a named author, in-text authority, or page layout (clean negative controls). (ii) Mechanistic account. For the brand cue, we give a full mechanistic account: swapping only the masthead moves credibility across an approximately 11 log-odds range that tracks professional ratings (rho = 0.88 with Media Bias/Fact Check). The prior is dual-coded (name and logo), strengthens with scale, is causally formed at layers 19-21, carried by interpretable seed-stable sparse-autoencoder features, and recurs at the same relative locus in a second model family. It overrides content (about 1.8x) as a signal-magnitude effect within a shared pathway, not a privileged route. Steering the localized direction selectively reduces the override (41% reduction) and generalizes to held-out outlets, confirming the prior is causally used, not merely decodable. Deployed VLMs may thus defer to source identity over the evidence in front of them, a reliability failure we can measure across models, localize, and causally probe. We release the stimulus suite and CueTrust.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
