Papers With Code
metadata only
M^3Eval: Multi-Modal Memory Evaluation through Cognitively-Grounded Video Tasks
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- The Brain, Body, and Behavior Dataset (BBBD): Multimodal Recordings during Educational Videos.#305339
- SimpleMemVLA: A Simple but Effective Native-Video Memory for Vision-Language-Action Models#972594
- Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models#1049692
- CAM: Question Answering on Entity-Centric Videos with Continuous Extraction and Adaptive Querying#974075
- Towards Automatic Video Annotation with ASH: Zero-Shot Open-Vocabulary Multi-Object Tracking and Segmentation#1155957
Record · ID 258662
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive