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Found 5 papers, 1 papers with code
Infi-Med: Low-Resource Medical MLLMs with Robust Reasoning Evaluation
Multimodal large language models (MLLMs) have demonstrated promising prospects in healthcare, particularly for addressing complex medical tasks, supporting multidisciplinary treatment (MDT), and enabling personalized precision medicine.
InfiR : Crafting Effective Small Language Models and Multimodal Small Language Models in Reasoning
Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have made significant advancements in reasoning capabilities.
InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion
Large Language Models (LLMs) have demonstrated strong performance across various reasoning tasks, yet building a single model that consistently excels across all domains remains challenging.
Unconstrained Model Merging for Enhanced LLM Reasoning
In this work, we propose an unconstrained model merging framework that accommodates both homogeneous and heterogeneous model architectures with a focus on reasoning tasks.
NeuronBlocks: Building Your NLP DNN Models Like Playing Lego
Deep Neural Networks (DNN) have been widely employed in industry to address various Natural Language Processing (NLP) tasks.
