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Found 7 papers, 4 papers with code
Catwalk: A Unified Language Model Evaluation Framework for Many Datasets
The success of large language models has shifted the evaluation paradigms in natural language processing (NLP).
VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use
These descriptions enable 1) collecting human-verified reference outputs for each instance; and 2) automatic evaluation of candidate multimodal generations using a text-only LLM, aligning with human judgment.
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models
We introduce OpenFlamingo, a family of autoregressive vision-language models ranging from 3B to 9B parameters.
Ranked #14 on
Visual Question Answering (VQA)
on InfiMM-Eval
Are aligned neural networks adversarially aligned?
We show that existing NLP-based optimization attacks are insufficiently powerful to reliably attack aligned text models: even when current NLP-based attacks fail, we can find adversarial inputs with brute force.
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text
We release Multimodal C4, an augmentation of the popular text-only C4 corpus with images interleaved.
Exploring The Landscape of Distributional Robustness for Question Answering Models
We conduct a large empirical evaluation to investigate the landscape of distributional robustness in question answering.
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection
We then translate the out-of-distribution score into a human interpretable CONFIDENCE SCORE to investigate its effect on the users' interaction with health ML applications.
