Across 2M+ in-the-wild LLM conversations, jailbreak attempts show no higher complexity than normal chats, and assistant toxicity has declined over time, suggesting bounded attack sophistication.
Discourse Coherence in the Wild: A Dataset, Evaluation and Methods
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abstract
To date there has been very little work on assessing discourse coherence methods on real-world data. To address this, we present a new corpus of real-world texts (GCDC) as well as the first large-scale evaluation of leading discourse coherence algorithms. We show that neural models, including two that we introduce here (SentAvg and ParSeq), tend to perform best. We analyze these performance differences and discuss patterns we observed in low coherence texts in four domains.
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Mass-Scale Analysis of In-the-Wild Conversations Reveals Complexity Bounds on LLM Jailbreaking
Across 2M+ in-the-wild LLM conversations, jailbreak attempts show no higher complexity than normal chats, and assistant toxicity has declined over time, suggesting bounded attack sophistication.