Automated evaluation of large vision-language models on self-driving corner cases

[PDF] arxiv.org

INS-MMBench: A Comprehensive Benchmark for Evaluating LVLMs' Performance in Insurance

C Lin, H Lyu, X Xu, J Luo - arXiv preprint arXiv:2406.09105, 2024 - arxiv.org
Large Vision-Language Models (LVLMs) have demonstrated outstanding performance in
various general multimodal applications such as image recognition and visual reasoning …
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Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment

Z Liu, Y Gou, K Chen, L Hong, J Gao, F Mi… - arXiv preprint arXiv …, 2024 - arxiv.org
As the capabilities of large language models (LLMs) have expanded dramatically, aligning
these models with human values presents a significant challenge, posing potential risks …
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RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in LVLMs

S Woo, J Jang, D Kim, Y Choi, C Kim - arXiv preprint arXiv:2405.17821, 2024 - arxiv.org
Recent advancements in Large Vision Language Models (LVLMs) have revolutionized how
machines understand and generate textual responses based on visual inputs. Despite their …
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SciQu: Accelerating Materials Properties Prediction with Automated Literature Mining for Self-Driving Laboratories

A Babu - arXiv preprint arXiv:2407.08270, 2024 - arxiv.org
Assessing different material properties to predict specific attributes, such as band gap,
resistivity, young modulus, work function, and refractive index, is a fundamental requirement …
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