Papers by Filippo Menczer
PluRule: A Benchmark for Moderating Pluralistic Communities on Social Media (2026.acl-long)
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| Challenge: | Social media are shifting towards community-governed platforms where groups define their own norms. |
| Approach: | They propose a multimodal, multilingual benchmark for detecting 13,371 rule violations across 1,989 Reddit communities . they show that bigger models and increased context provide marginal gains, and universal rules like civility and self-promotion are easier to detect. |
| Outcome: | The proposed model can detect 13,371 rule violations across 1,989 Reddit communities across 2,885 rules in 9 languages. |
REMATCH: Robust and Efficient Matching of Local Knowledge Graphs to Improve Structural and Semantic Similarity (2024.findings-naacl)
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| Challenge: | Existing AMR metrics are inefficient and struggle to capture semantic similarity . Existing metrics are not efficient and lack a systematic evaluation benchmark . |
| Approach: | They propose a new AMR similarity metric, rematch, which matches graphs structurally and semantically to each other. |
| Outcome: | The proposed metric is five times faster than the next most efficient metric. |
Large Language Models Require Curated Context for Reliable Political Fact-Checking—Even with Reasoning and Web Search (2026.findings-acl)
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| Challenge: | Large language models (LLMs) have raised hopes for automated end-to-end fact-checking, but prior studies report mixed results. |
| Approach: | They evaluate 15 large language models on 6,000 claims fact-checked by PolitiFact . standard models perform poorly, reasoning offers minimal benefits, and web search provides only moderate gains . |
| Outcome: | The models predict claim veracity and a curated RAG system improved macro F1 by 233% on average across model variants. |