MemEIC/CCKEB
CCKEB (Compositional/Continual Knowledge Editing Benchmark) π Overview CCKEB is a benchmark designed for Continual and Compositional Knowledge Editing in Large Vision-Language Models (LVLMs), accepted at NeurIPS 2025. The benchmark targets realistic knowledge update scenarios in which visual identities and textual facts are edited sequentially.Models are required to retain previously edited knowledge while answering compositional multimodal queries thatβ¦ See the full description on the dataset page: https://huggingface.co/datasets/MemEIC/CCKEB.
| Author / organization | MemEIC |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 266 (as reported by Hugging Face) |
| Likes | 2 |
| Created | 17 December 2025 |
| Last updated at source | 6 March 2026 |
Recent changes
- 16 Oct 2026 Description: CCKEB (Compositional/Continual Knowledge Editing Benchmark) π Overview CCKEB is a benchmark designed for Continual and Compositional Knowledge Editing in Large Vision-Language Models (LVLMs), accepted at NeurIPS 2025. The benchmark targets β CCKEB (Compositional/Continual Knowledge Editing Benchmark) π Overview CCKEB is a benchmark designed for Continual and Compositional Knowledge Editing in Large Vision-Language Models (LVLMs), accepted at NeurIPS 2025. The benchmark targets
Changes detected by Silytics between refreshes of the source.
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.