stellalisy/HorizonBench
HorizonBench Long-Horizon Personalization with Evolving Preferences HorizonBench evaluates whether language models can track user preferences as they evolve across months of interaction. Each benchmark item is a 5-option multiple-choice question embedded within a conversation history averaging ~163K tokens. Pre-evolution preference values serve as hard-negative distractors, enabling diagnosis of belief-update failure: models retrieve the user's originally stated preference but… See the full description on the dataset page: https://huggingface.co/datasets/stellalisy/HorizonBench.
| Author / organization | stellalisy |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 1.8K (as reported by Hugging Face) |
| Likes | 2 |
| Created | 15 April 2026 |
| Last updated at source | 21 April 2026 |
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Recent changes
- 17 Oct 2026 Description: HorizonBench Long-Horizon Personalization with Evolving Preferences HorizonBench evaluates whether language models can track user preferences as they evolve across months of interaction. Each benchmark item is a 5-option multiple-choice que → HorizonBench Long-Horizon Personalization with Evolving Preferences HorizonBench evaluates whether language models can track user preferences as they evolve across months of interaction. Each benchmark item is a 5-option multiple-choice que
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