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Hits 101 – 120 of 1.029

101
Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes ...
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102
Wikily Supervised Neural Translation Tailored to Cross-Lingual Tasks ...
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103
Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization ...
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104
Sorting through the noise: Testing robustness of information processing in pre-trained language models ...
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105
Building the Directed Semantic Graph for Coherent Long Text Generation ...
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106
Detect and Classify – Joint Span Detection and Classification for Health Outcomes ...
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107
Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation ...
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108
Evaluation of Summarization Systems across Gender, Age, and Race ...
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109
A Language Model-based Generative Classifier for Sentence-level Discourse Parsing ...
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110
Controllable Neural Dialogue Summarization with Personal Named Entity Planning ...
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111
Foreseeing the Benefits of Incidental Supervision ...
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112
Graphine: A Dataset for Graph-aware Terminology Definition Generation ...
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113
CSDS: A Fine-Grained Chinese Dataset for Customer Service Dialogue Summarization ...
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114
Connecting Attributions and QA Model Behavior on Realistic Counterfactuals ...
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115
Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? ...
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116
Generation and Extraction Combined Dialogue State Tracking with Hierarchical Ontology Integration ...
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117
Error-Sensitive Evaluation for Ordinal Target Variables ...
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118
CDLM: Cross-Document Language Modeling ...
Abstract: Anthology paper link: https://aclanthology.org/2021.findings-emnlp.225.pdf Abstract: We introduce a new pretraining approach geared for multi-document language modeling, incorporating two key ideas into the masked language modeling self-supervised objective. First, instead of considering documents in isolation, we pretrain over sets of multiple related documents, encouraging the model to learn cross-document relationships. Second, we improve over recent long-range transformers by introducing dynamic global attention that has access to the entire input to predict masked tokens. We release CDLM (Cross-Document Language Model), a new general language model for multi-document setting that can be easily applied to downstream tasks. Our extensive analysis shows that both ideas are essential for the success of CDLM, and work in synergy to set new state-of-the-art results for several multi-text tasks. ...
Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/pbq6-k224
https://underline.io/lecture/39791-cdlm-cross-document-language-modeling
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119
Data-to-text Generation by Splicing Together Nearest Neighbors ...
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120
Natural Language Processing Meets Quantum Physics: A Survey and Categorization ...
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