Benchmarking Robustness to Text-Guided Corruptions

This study investigates the robustness of image classifiers to text-guided corruptions. We utilize diffusion models to edit images to different domains. Unlike other works that use synthetic or hand-picked data for benchmarking, we use diffusion models as they are generative models capable of learning to edit images while preserving their semantic content. Thus, the corruptions will be more realistic and the comparison will be more informative. Also, there is no need for manual labeling and we can create large-scale benchmarks with less effort. We define a prompt hierarchy based on the original ImageNet hierarchy to apply edits in different domains. As well as introducing a new benchmark we try to investigate the robustness of different vision models. The results of this study demonstrate that the performance of image classifiers decreases significantly in different language-based corruptions and edit domains. We also observe that convolutional models are more robust than transformer architectures. Additionally, we see that common data augmentation techniques can improve the performance on both the original data and the edited images. The findings of this research can help improve the design of image classifiers and contribute to the development of more robust machine learning systems. The code for generating the benchmark is available at https://github.com/ckoorosh/RobuText.Comment: Accepted to CVPRW 202

Investigation of the role of endosomal Toll-like receptors in murine collagen-induced arthritis reveals a potential role for TLR7 in disease maintenance

INTRODUCTION Endosomal toll-like receptors (TLRs) have recently emerged as potential contributors to the inflammation observed in human and rodent models of rheumatoid arthritis (RA). This study aims to evaluate the role of endosomal TLRs and in particular TLR7 in the murine collagen induced arthritis (CIA) model. METHODS CIA was induced by injection of collagen in complete Freund's adjuvant. To investigate the effect of endosomal TLRs in the CIA model, mianserin was administered daily from the day of disease onset. The specific role of TLR7 was examined by inducing CIA in TLR7-deficient mice. Disease progression was assessed by measuring clinical score, paw swelling, serum anti-collagen antibodies histological parameters, cytokine production and the percentage of T regulatory (Treg) cells. RESULTS Therapeutic administration of mianserin to arthritic animals demonstrated a highly protective effect on paw swelling and joint destruction. TLR7-/- mice developed a mild arthritis, where the clinical score and paw swelling were significantly compromised in comparison to the control group. The amelioration of arthritis by mianserin and TLR7 deficiency both corresponded with a reduction in IL-17 responses, histological and clinical scores, and paw swelling. CONCLUSIONS These data highlight the potential role for endosomal TLRs in the maintenance of inflammation in RA and support the concept of a role for TLR7 in experimental arthritis models. This study also illustrates the potential benefit that may be afforded by therapeutically inhibiting the endosomal TLRs in RA