SCAI-JHU/ThoughtTrace
ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions 🌐 Project Page · 📄 Paper · 💻 Code Conversational AI has reached billions of users, yet existing datasets capture only what people say, not what they think. ThoughtTrace is the first large-scale dataset that pairs real-world multi-turn human–AI conversations with users' self-reported thoughts: their reasons for sending prompts and reactions to assistant responses. ThoughtTrace comprises 1,058 users, 2… See the full description on the dataset page: https://huggingface.co/datasets/SCAI-JHU/ThoughtTrace.
| Author / organization | SCAI-JHU |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 5.4K (as reported by Hugging Face) |
| Likes | 27 |
| Created | 13 May 2026 |
| Last updated at source | 23 May 2026 |
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- 16 Oct 2026 Description: ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions 🌐 Project Page · 📄 Paper · 💻 Code Conversational AI has reached billions of users, yet existing datasets capture only what people say, not what they think. ThoughtT → ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions 🌐 Project Page · 📄 Paper · 💻 Code Conversational AI has reached billions of users, yet existing datasets capture only what people say, not what they think. ThoughtT
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