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Giuseppe Carenini
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Publications
- 2023
- [c125]Chuyuan Li, Patrick Huber, Wen Xiao, Maxime Amblard, Chloé Braud, Giuseppe Carenini:
Discourse Structure Extraction from Pre-Trained and Fine-Tuned Language Models in Dialogues. EACL (Findings) 2023: 2517-2534 - [i41]Chuyuan Li, Patrick Huber, Wen Xiao, Maxime Amblard, Chloé Braud, Giuseppe Carenini:
Discourse Structure Extraction from Pre-Trained and Fine-Tuned Language Models in Dialogues. CoRR abs/2302.05895 (2023) - 2022
- [c123]Patrick Huber, Linzi Xing, Giuseppe Carenini:
Predicting Above-Sentence Discourse Structure Using Distant Supervision from Topic Segmentation. AAAI 2022: 10794-10802 - [c120]Patrick Huber, Giuseppe Carenini:
Towards Understanding Large-Scale Discourse Structures in Pre-Trained and Fine-Tuned Language Models. NAACL-HLT 2022: 2376-2394 - [i33]Patrick Huber, Giuseppe Carenini:
Towards Understanding Large-Scale Discourse Structures in Pre-Trained and Fine-Tuned Language Models. CoRR abs/2204.04289 (2022) - [i30]Linzi Xing, Patrick Huber, Giuseppe Carenini:
Improving Topic Segmentation by Injecting Discourse Dependencies. CoRR abs/2209.08626 (2022) - [i28]Patrick Huber, Giuseppe Carenini:
Unsupervised Inference of Data-Driven Discourse Structures using a Tree Auto-Encoder. CoRR abs/2210.09559 (2022) - [i27]Patrick Huber, Giuseppe Carenini:
Towards Domain-Independent Supervised Discourse Parsing Through Gradient Boosting. CoRR abs/2210.09565 (2022) - [i26]Patrick Huber, Giuseppe Carenini:
Large Discourse Treebanks from Scalable Distant Supervision. CoRR abs/2212.06038 (2022) - 2021
- [c117]Patrick Huber, Giuseppe Carenini:
Unsupervised Learning of Discourse Structures using a Tree Autoencoder. AAAI 2021: 13107-13115 - [c115]Patrick Huber, Wen Xiao, Giuseppe Carenini:
W-RST: Towards a Weighted RST-style Discourse Framework. ACL/IJCNLP (1) 2021: 3908-3918 - [c111]Wen Xiao, Patrick Huber, Giuseppe Carenini:
Predicting Discourse Trees from Transformer-based Neural Summarizers. NAACL-HLT 2021: 4139-4152 - [i24]Wen Xiao, Patrick Huber, Giuseppe Carenini:
Predicting Discourse Trees from Transformer-based Neural Summarizers. CoRR abs/2104.07058 (2021) - [i22]Patrick Huber, Wen Xiao, Giuseppe Carenini:
W-RST: Towards a Weighted RST-style Discourse Framework. CoRR abs/2106.02658 (2021) - [i16]Patrick Huber, Linzi Xing, Giuseppe Carenini:
Predicting Above-Sentence Discourse Structure using Distant Supervision from Topic Segmentation. CoRR abs/2112.06196 (2021) - 2020
- [c105]Patrick Huber, Giuseppe Carenini:
From Sentiment Annotations to Sentiment Prediction through Discourse Augmentation. COLING 2020: 185-197 - [c104]Grigorii Guz, Patrick Huber, Giuseppe Carenini:
Unleashing the Power of Neural Discourse Parsers - A Context and Structure Aware Approach Using Large Scale Pretraining. COLING 2020: 3794-3805 - [c102]Patrick Huber, Giuseppe Carenini:
MEGA RST Discourse Treebanks with Structure and Nuclearity from Scalable Distant Sentiment Supervision. EMNLP (1) 2020: 7442-7457 - [i11]Patrick Huber, Giuseppe Carenini:
MEGA RST Discourse Treebanks with Structure and Nuclearity from Scalable Distant Sentiment Supervision. CoRR abs/2011.03017 (2020) - [i10]Patrick Huber, Giuseppe Carenini:
From Sentiment Annotations to Sentiment Prediction through Discourse Augmentation. CoRR abs/2011.03021 (2020) - [i9]Grigorii Guz, Patrick Huber, Giuseppe Carenini:
Unleashing the Power of Neural Discourse Parsers - A Context and Structure Aware Approach Using Large Scale Pretraining. CoRR abs/2011.03203 (2020) - [i7]Wen Xiao, Patrick Huber, Giuseppe Carenini:
Do We Really Need That Many Parameters In Transformer For Extractive Summarization? Discourse Can Help ! CoRR abs/2012.02144 (2020) - [i6]Patrick Huber, Giuseppe Carenini:
Unsupervised Learning of Discourse Structures using a Tree Autoencoder. CoRR abs/2012.09446 (2020) - 2019
- [c92]Patrick Huber, Giuseppe Carenini:
Predicting Discourse Structure using Distant Supervision from Sentiment. EMNLP/IJCNLP (1) 2019: 2306-2316 - [i3]Patrick Huber, Giuseppe Carenini:
Predicting Discourse Structure using Distant Supervision from Sentiment. CoRR abs/1910.14176 (2019)
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