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Researchers release multi-view media profiling suite for bias and factuality detection

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced MBFC-2025, a large dataset of approximately 2,600 media outlets, to address the lack of unified resources for detecting political bias and factuality in news. The study also constructs multi-view representations for existing datasets like ACL-2020 and MBFC-2025, incorporating various data sources such as hyperlink graphs and LLM-derived information. A systematic evaluation of embedding views and fusion strategies was performed, achieving state-of-the-art results on ACL-2020 and setting new benchmarks for MBFC-2025. AI

IMPACT Provides new resources and benchmarks for developing AI systems capable of identifying political bias and factuality in news media.

RANK_REASON The cluster contains a new academic paper detailing a dataset and evaluation methodology for media bias detection. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Researchers release multi-view media profiling suite for bias and factuality detection

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The cluster contains a new academic paper detailing a dataset and evaluation methodology for media bias detection. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Muhammad Arslan Manzoor, Dilshod Azizov, Daniil Orel, Umer Siddique, Zain Muhammad Mujahid, Yufang Hou, Preslav Nakov ·

    A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis

    arXiv:2605.01336v1 Announce Type: new Abstract: News outlets shape public opinion at a scale that makes automated detection of political bias and factuality essential. However, the field still lacks unified resources, comprehensive evaluations across diverse approaches, and syste…

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