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From Articles to Publishers: Aggregating Language Model Predictions for News Source Reliability Inference

arXiv · AI, language, vision and robotics · article · Sep 21, 2026 · UTC

Traditionally, the reliability of news publishers is assessed by expert organisations that evaluate editorial practices, transparency and factual standards at source. When this process is translated into a computational approach, the problem is often formulated at the level of individual articles, with models being trained on a set of pre-labelled articles and their performance being evaluated in a test phase. In this work, we investigate news source reliability inference as a source-level prediction problem. We propose a two-stage framework in which transformer-based language models first est

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