Publications (5)
RealBirdID: Benchmarking Bird Species Identification in the Era of MLLMs
Logan Lawrence, Mustafa Chasmai, Rangel Daroya +8
Fine-grained bird species identification in the wild is frequently unanswerable from a single image: key cues may be non-visual (e.g. vocalization), or obscured due to occlusion, c…
Direct-Scoring NLG Evaluators Can Use Pairwise Comparisons Too
Logan Lawrence, Ashton Williamson, Alexander Shelton
As large-language models have been increasingly used as automatic raters for evaluating free-form content, including document summarization, dialog, and story generation, work has…
Generate, Transduct, Adapt: Iterative Transduction with VLMs
Oindrila Saha, Logan Lawrence, Grant Van Horn +1
Transductive zero-shot learning with vision-language models leverages image-image similarities within the dataset to achieve better classification accuracy compared to the inductiv…
Efficient Transformer Knowledge Distillation: A Performance Review
Nathan Brown, Ashton Williamson, Tahj Anderson +1
As pretrained transformer language models continue to achieve state-of-the-art performance, the Natural Language Processing community has pushed for advances in model compression a…
You May Speak Freely: Improving the Fine-Grained Visual Recognition Capabilities of Multimodal Large Language Models with Answer Extraction
Logan Lawrence, Oindrila Saha, Megan Wei +3
Despite the renewed interest in zero-shot visual classification due to the rise of Multimodal Large Language Models (MLLMs), the problem of evaluating free-form responses of auto-r…