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Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants., , , , , and . NAACL-HLT, page 3754-3767. Association for Computational Linguistics, (2022)Grounding, Meaning and Foundation Models: Adventures in Multimodal Machine Learning.. ACM Multimedia, page 5. ACM, (2022)Countering Language Drift via Visual Grounding., , and . EMNLP/IJCNLP (1), page 4384-4394. Association for Computational Linguistics, (2019)Specializing Word Embeddings for Similarity or Relatedness., , and . EMNLP, page 2044-2048. The Association for Computational Linguistics, (2015)Multi- and Cross-Modal Semantics Beyond Vision: Grounding in Auditory Perception., and . EMNLP, page 2461-2470. The Association for Computational Linguistics, (2015)Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation., , , , , and . EMNLP (1), page 8830-8848. Association for Computational Linguistics, (2021)Emergent Linguistic Phenomena in Multi-Agent Communication Games., , and . EMNLP/IJCNLP (1), page 3698-3708. Association for Computational Linguistics, (2019)To what extent do human explanations of model behavior align with actual model behavior?, , , , , and . CoRR, (2020)Leveraging Diffusion Perturbations for Measuring Fairness in Computer Vision., , , , and . CoRR, (2023)I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling., , , , and . CoRR, (2020)