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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gheini, Mozhdeh; May, Jonathan. - : Underline Science Inc., 2021 BASE Show details 2 RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ho, Daniel; Khanna, Rahul. - : Underline Science Inc., 2021 BASE Show details 3 Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jin, Xisen; Lin, Yuchen. - : Underline Science Inc., 2021 BASE Show details 4 RockNER: A Simple Method to Create Adversarial Examples for Evaluating the Robustness of Named Entity Recognition Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gao, Wenyang; Lin, Yuchen. - : Underline Science Inc., 2021 BASE Show details 5 ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Han, Rujun; Peng, Nanyun. - : Underline Science Inc., 2021 BASE Show details 6 Discretized Integrated Gradients for Explaining Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ren, Xiang; Sanyal, Soumya. - : Underline Science Inc., 2021 BASE Show details 7 Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Galstyan, Aram; Mehrabi, Ninareh; Morstatter, Fred; Pujara, Jay; Ren, Xiang; Zhou, Pei. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.410/ Abstract: Warning: this work contains content that may be offensive or upsetting. Commonsense knowledge bases (CSKB) are increasingly used for various natural language processing tasks. Since CSKBs are mostly human-generated and may reflect societal biases, it is important to ensure that such biases are not conflated with the notion of common sense. Here we focus on two widely used CSKBs, ConceptNet and GenericsKB, and establish the presence of bias in the form of two types of representational harms, overgeneralization of polarized perceptions and representation disparity across different demographic groups in both CSKBs. Next, we find similar representational harms for downstream models that use ConceptNet. Finally, we propose a filtering-based approach for mitigating such harms, and observe that our filtered-based approach can reduce the issues in both resources and models but leads to a performance drop, leaving room for future work to ... Keyword: Computational Linguistics; Ethics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing URL: https://underline.io/lecture/37537-lawyers-are-dishonestquestion-quantifying-representational-harms-in-commonsense-knowledge-resources https://dx.doi.org/10.48448/0xzm-k745 BASE Hide details 8 Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Han, Jiawei; Mao, Yuning. - : Underline Science Inc., 2021 BASE Show details

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