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Found 6 papers, 3 papers with code
Behind the Magic, MERLIM: Multi-modal Evaluation Benchmark for Large Image-Language Models
This paper introduces a Multi-modal Evaluation Benchmark named MERLIM, a scalable test-bed to assess the performance of IT-LVLMs on fundamental computer vision tasks.
PIVOT: Prompting for Video Continual Learning
In this paper, we address the problem of continual learning for video data.
vCLIMB: A Novel Video Class Incremental Learning Benchmark
We perform in-depth evaluations of existing CL methods in vCLIMB, and observe two unique challenges in video data.
Augmenting BERT-style Models with Predictive Coding to Improve Discourse-level Representations
Current language models are usually trained using a self-supervised scheme, where the main focus is learning representations at the word or sentence level.
TNT: Text-Conditioned Network with Transductive Inference for Few-Shot Video Classification
Recently, few-shot learning has received increasing interest.
Interpretable Contextual Team-aware Item Recommendation: Application in Multiplayer Online Battle Arena Games
Our evaluation indicates that both the Transformer architecture and the contextual information are essential to get the best results for this item recommendation task.
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