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BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models ...
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Including Signed Languages in Natural Language Processing ...
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Including Signed Languages in Natural Language Processing ...
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Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? ...
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Measuring and Improving Consistency in Pretrained Language Models ...
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Aligning Faithful Interpretations with their Social Attribution ...
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Amnesic Probing: Behavioral Explanation With Amnesic Counterfactuals ...
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Abstract:
Read paper: https://doi.org/10.1162/tacla00359 Abstract: A growing body of work makes use of probing in order to investigate the working of neural models, often considered black boxes. Recently, an ongoing debate emerged surrounding the limitations of the probing paradigm. In this work, we point out the inability to infer behavioral conclusions from probing results, and offer an alternative method that focuses on how the information is being used, rather than on what information is encoded. Our method, Amnesic Probing, follows the intuition that the utility of a property for a given task can be assessed by measuring the influence of a causal intervention that removes it from the representation. Equipped with this new analysis tool, we can ask questions that were not possible before, for example, is part-of-speech information important for word prediction? We perform a series of analyses on BERT to answer these types of questions. Our findings demonstrate that conventional probing performance is not ...
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Keyword:
Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
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URL: https://dx.doi.org/10.48448/ac82-sa45 https://underline.io/lecture/25845-amnesic-probing-behavioral-explanation-with-amnesic-counterfactuals
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Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent ...
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Asking It All: Generating Contextualized Questions for any Semantic Role ...
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Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora
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In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03161637 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States. pp.538-555, ⟨10.18653/v1/2020.acl-main.51⟩ (2020)
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