Papers by Norbert Fuhr
Can Rumour Stance Alone Predict Veracity? (C18-1)
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| Challenge: | Existing studies of automatic veracity classification of social media rumours have not explored the effectiveness of crowd stance to determine veracity. |
| Approach: | They propose to use stance as an additional feature to those commonly used in earlier studies to model the veracity of a rumour using Hidden Markov Models and collective stance information to model a social media rumor. |
| Outcome: | The proposed models outperform those using crowd stance and tweets’ times as the only features for modelling true and false rumours. |
TracSum: A New Benchmark for Aspect-Based Summarization with Sentence-Level Traceability in Medical Domain (2025.emnlp-main)
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| Challenge: | Existing evidence-based summarization tasks require tracing source evidence to assess their accuracy. |
| Approach: | They propose a benchmark for traceable, aspect-based summarization that pairs summaries with sentence-level citations to enable users to trace back to the original context. |
| Outcome: | The proposed benchmark can be used to evaluate document summarization with LLMs and human evaluations. |