gistbench

GISTBench — Groundedness & Interest Specificity Test Bench GISTBench evaluates how well LLMs understand users from their engagement history. Given a user's interactions with content (videos, articles, books, etc.), the benchmark measures whether an LLM can extract meaningful interests, ground them in evidence, and cite specific relevant items. Dataset Details **Rows:** 4,214,059 engagements **Users:** ~1,000 anonymized users **Format:** Parquet Schema | Column | Type | Description | |---|---|---| | `user_id` | `int64` | Anonymized user identifier | | `object_id` | `int64` | Anonymized content item identifier | | `object_text` | `string` | Text description of the content item | | `interaction_type` | `string` | One of: `explicit_positive`, `implicit_positive`, `implicit_negative`, `explicit_negative` | | `interaction_time` | `string` | Anonymized interaction timestamp | Interaction Types | Type | Meaning | Examples | |---|---|---| | `explicit_positive` | User actively expressed positive interest | Liked, favorited, rated highly | | `implicit_positive` | Passive positive signal | Watched fully, clicked through | | `implicit_negative` | Passive negative signal | Scrolled past, skipped | | `explicit_negative` | User actively expressed dislike | Downvoted, reported, rated low | Usage Citation If you use GISTBench in your research, please cite: License This dataset is released under CC BY-NC 4.0.