Enhancing LLM Capabilities Beyond Scaling Up
General-purpose large language models (LLMs) are progressively expanding both in scale
and access to unpublic training data. This has led to notable progress in a variety of AI …
and access to unpublic training data. This has led to notable progress in a variety of AI …
Evaluating and Advancing Multimodal Large Language Models in Ability Lens
As multimodal large language models (MLLMs) advance rapidly, rigorous evaluation has
become essential, providing further guidance for their development. In this work, we focus …
become essential, providing further guidance for their development. In this work, we focus …
Modular, Collaborative and Decentralized Deep Learning
The increasing complexity of modern machine learning models exposes the limitations of
the traditional, monolithic approach to their development, raising concerns about cost and …
the traditional, monolithic approach to their development, raising concerns about cost and …
LLM Merging Competition Technical Report: Efficient Model Merging with Strategic Model Selection, Merging, and Hyperparameter Optimization
The LLM Merging Competition in NeurIPS'24 aims to build LLMs efficiently through model
merging, which enables the combination of multiple specialized fine-tuned models into a …
merging, which enables the combination of multiple specialized fine-tuned models into a …