Abstract is missing.
- Video Highlights Detection and Summarization with Lag-Calibration based on Concept-Emotion Mapping of Crowdsourced Time-Sync CommentsQing-ping, Chaomei Chen. 1-11 [doi]
- Multimedia Summary Generation from Online Conversations: Current Approaches and Future DirectionsEnamul Hoque, Giuseppe Carenini. 12-19 [doi]
- Low-Resource Neural Headline GenerationOttokar Tilk, Tanel Alumäe. 20-26 [doi]
- Towards Improving Abstractive Summarization via Entailment GenerationRamakanth Pasunuru, Han Guo, Mohit Bansal. 27-32 [doi]
- Coarse-to-Fine Attention Models for Document SummarizationJeffrey Ling, Alexander M. Rush. 33-42 [doi]
- Automatic Community Creation for Abstractive Spoken Conversations SummarizationKaran Singla, Evgeny A. Stepanov, Ali Orkan Bayer, Giuseppe Carenini, Giuseppe Riccardi. 43-47 [doi]
- Combining Graph Degeneracy and Submodularity for Unsupervised Extractive SummarizationAntoine J.-P. Tixier, Polykarpos Meladianos, Michalis Vazirgiannis. 48-58 [doi]
- TL;DR: Mining Reddit to Learn Automatic SummarizationMichael Völske, Martin Potthast, Shahbaz Syed, Benno Stein. 59-63 [doi]
- Topic Model Stability for Hierarchical SummarizationJohn Miller, Kathleen F. McCoy. 64-73 [doi]
- Learning to Score System Summaries for Better Content Selection EvaluationMaxime Peyrard, Teresa Botschen, Iryna Gurevych. 74-84 [doi]
- Revisiting the Centroid-based Method: A Strong Baseline for Multi-Document SummarizationDemian Gholipour Ghalandari. 85-90 [doi]
- Reader-Aware Multi-Document Summarization: An Enhanced Model and The First DatasetPiji Li, Lidong Bing, Wai Lam. 91-99 [doi]
- A Pilot Study of Domain Adaptation Effect for Neural Abstractive SummarizationXinyu Hua, Lu Wang. 100-106 [doi]