EverMind-AI/EverMemBench-Static
EverMemBench-S: Evaluating Evidence Access under Dense Semantic Interference ๐ป Code: EverMind-AI/EverMemBench-Static Overview EverMemBench-S (EMB-S) is an adversarial Needle-in-a-Haystack benchmark built on a 326M-token MemoryBank with 160,280 documents across 8 domains. It evaluates long-context models and retrieval systems under dense semantic interference โ where near-miss documents create realistic confusion that standard NIAH benchmarks cannot capture. 1โฆ See the full description on the dataset page: https://huggingface.co/datasets/EverMind-AI/EverMemBench-Static.
| Author / organization | EverMind-AI |
|---|---|
| License (as declared) | cc-by-nc-sa-4.0 |
| Downloads | 186 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 5 December 2025 |
| Last updated at source | 6 March 2026 |
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- 16 Oct 2026 Description: EverMemBench-S: Evaluating Evidence Access under Dense Semantic Interference ๐ป Code: EverMind-AI/EverMemBench-Static Overview EverMemBench-S (EMB-S) is an adversarial Needle-in-a-Haystack benchmark built on a 326M-token MemoryBank with 160 โ EverMemBench-S: Evaluating Evidence Access under Dense Semantic Interference ๐ป Code: EverMind-AI/EverMemBench-Static Overview EverMemBench-S (EMB-S) is an adversarial Needle-in-a-Haystack benchmark built on a 326M-token MemoryBank with 160
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