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Hits 81 – 100 of 941

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 ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.599/ Abstract: Natural language generation (NLG) spans a broad range of tasks, each of which serves for specific objectives and desires different properties of generated text. The complexity makes automatic evaluation of NLG particularly challenging. Previous work has typically focused on a single task and developed individual evaluation metrics based on specific intuitions. In this paper, we propose a unifying perspective based on the nature of information change in NLG tasks, including compression (e.g., summarization), transduction (e.g., text rewriting), and creation (e.g., dialog). Information alignment between input, context, and output text plays a common central role in characterizing the generation. With automatic alignment prediction models, we develop a family of interpretable metrics that are suitable for evaluating key aspects of different NLG tasks, often without need of gold reference data. Experiments show the uniformly designed ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural language generation; Natural Language Processing; Text Summarization
URL: https://dx.doi.org/10.48448/39mx-d326
https://underline.io/lecture/38012-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 ...
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