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Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality ...
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ANLIzing the Adversarial Natural Language Inference Dataset
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In: Proceedings of the Society for Computation in Linguistics (2022)
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Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection ...
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FLAVA: A Foundational Language And Vision Alignment Model ...
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I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling ...
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Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.696/ Abstract: Despite recent progress, state-of-the-art question answering models remain vulnerable to a variety of adversarial attacks. While dynamic adversarial data collection, in which a human annotator tries to write examples that fool a model-in-the-loop, can improve model robustness, this process is expensive which limits the scale of the collected data. In this work, we are the first to use synthetic adversarial data generation to make question answering models more robust to human adversaries. We develop a data generation pipeline that selects source passages, identifies candidate answers, generates questions, then finally filters or re-labels them to improve quality. Using this approach, we amplify a smaller human-written adversarial dataset to a much larger set of synthetic question-answer pairs. By incorporating our synthetic data, we improve the state-of-the-art on the AdversarialQA dataset by 3.7F1 and improve model generalisation ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Question-Answering Systems
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URL: https://dx.doi.org/10.48448/f04n-c312 https://underline.io/lecture/37811-improving-question-answering-model-robustness-with-synthetic-adversarial-data-generation
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Gradient-based Adversarial Attacks against Text Transformers ...
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On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study ...
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Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little ...
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Deep Artificial Neural Networks Reveal a Distributed Cortical Network Encoding Propositional Sentence-Level Meaning
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In: J Neurosci (2021)
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Emergent Linguistic Phenomena in Multi-Agent Communication Games ...
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Inferring concept hierarchies from text corpora via hyperbolic embeddings ...
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Inferring concept hierarchies from text corpora via hyperbolic embeddings
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In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) (2019)
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Visually Grounded and Textual Semantic Models Differentially Decode Brain Activity Associated with Concrete and Abstract Nouns ...
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Virtual Embodiment: A Scalable Long-Term Strategy for Artificial Intelligence Research ...
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HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment ...
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