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Found 4 papers, 0 papers with code
MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning
We present MM1. 5, a new family of multimodal large language models (MLLMs) designed to enhance capabilities in text-rich image understanding, visual referring and grounding, and multi-image reasoning.
Ranked #55 on
Visual Question Answering
on MM-Vet
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Through careful and comprehensive ablations of the image encoder, the vision language connector, and various pre-training data choices, we identified several crucial design lessons.
Ranked #73 on
Visual Question Answering
on MM-Vet
FiGLearn: Filter and Graph Learning using Optimal Transport
We cast a new optimisation problem that minimises the Wasserstein distance between the distribution of the signal observations and the filtered signal distribution model.
Sequential Mode Estimation with Oracle Queries
We consider the problem of adaptively PAC-learning a probability distribution $\mathcal{P}$'s mode by querying an oracle for information about a sequence of i. i. d.
