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Found 4 papers, 1 papers with code
RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents
Owing to recent advancements, Large Language Models (LLMs) can now be deployed as agents for increasingly complex decision-making applications in areas including robotics, gaming, and API integration.
One Student Knows All Experts Know: From Sparse to Dense
Mixture-of-experts (MoE) is a powerful sparse architecture including multiple experts.
Cross-token Modeling with Conditional Computation
Mixture-of-Experts (MoE), a conditional computation architecture, achieved promising performance by scaling local module (i. e. feed-forward network) of transformer.
Go Wider Instead of Deeper
To achieve better performance with fewer trainable parameters, recent methods are proposed to go shallower by parameter sharing or model compressing along with the depth.
Ranked #663 on
Image Classification
on ImageNet
