[1] Park, Sangha, et al. On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection (NeurIPS 2023)

[2] Radford, Alec, et al. Learning transferable visual models from natural language supervision (ICML 2021)

[3] Brown, Tom, et al. Language models are few-shot learners (NeurIPS 2020)

[4] Li, Junnan, et al. Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models (Preprint 2023)

[5] Zheng, Haotian, et al. Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources (NeurIPS 2023)

[6] Tang, Zhenheng, et al. Virtual homogeneity learning: Defending against data heterogeneity in federated learning (ICML 2022)