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Dual use, the intentional, harmful reuse of technology and scientific artefacts, is an ill-defined problem within the context of Natural Language Processing (NLP).As large language models (LLMs) have advanced in their capabilities and become more accessible, the risk of their intentional misuse becomes more prevalent.To prevent such intentional malicious use, it is necessary for NLP researchers and practitioners to understand and mitigate the risks of their research.Hence, we present an NLPspecific definition of dual use informed by researchers and practitioners in the field.Further, we propose a checklist focusing on dual-use in NLP, that can be integrated into existing conference ethics-frameworks.The definition and checklist are created based on a survey of NLP researchers and practitioners. 1
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Stored only when both papers are in the corpus — 12 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.