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Hits 81 – 100 of 927

81
Journalistic Guidelines Aware News Image Captioning ...
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82
MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News Summarization ...
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83
Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline ...
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84
Fine-grained Factual Consistency Assessment for Abstractive Summarization Models ...
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85
Modeling Endorsement for Multi-Document Abstractive Summarization ...
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86
COVR: A Test-Bed for Visually Grounded Compositional Generalization with Real Images ...
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87
Are We Summarizing the Right Way? A Survey of Dialogue Summarization Data Sets ...
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88
A Large-Scale Dataset for Empathetic Response Generation ...
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89
Convex Aggregation for Opinion Summarization ...
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90
Knowledge and Keywords Augmented Abstractive Sentence Summarization ...
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91
Continual Learning for Grounded Instruction Generation by Observing Human Following Behavior ...
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92
Coupling Context Modeling with Zero Pronoun Recovering for Document-Level Natural Language Generation ...
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93
Sentence-level Planning for Especially Abstractive Summarization ...
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94
Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences ...
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95
Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation ...
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96
Aspect-Controllable Opinion Summarization ...
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97
Measuring Similarity of Opinion-bearing Sentences ...
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98
Learning Compact Metrics for MT ...
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99
Models and Datasets for Cross-Lingual Summarisation ...
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100
Smelting Gold and Silver for Improved Multilingual AMR-to-Text Generation ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.57/ Abstract: Recent work on multilingual AMR-to-text generation has exclusively focused on data augmentation strategies that utilize silver AMR. However, this assumes a high quality of generated AMRs, potentially limiting the transferability to the target task. In this paper, we investigate different techniques for automatically generating AMR annotations, where we aim to study which source of information yields better multilingual results. Our models trained on gold AMR with silver (machine translated) sentences outperform approaches which leverage generated silver AMR. We find that combining both complementary sources of information further improves multilingual AMR-to-text generation. Our models surpass the previous state of the art for German, Italian, Spanish, and Chinese by a large margin. ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Text Generation
URL: https://dx.doi.org/10.48448/zryq-gp24
https://underline.io/lecture/37489-smelting-gold-and-silver-for-improved-multilingual-amr-to-text-generation
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