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ORCIDVera Demberg
Vera Demberg-Winterfors
Person information
- affiliation: Saarland University, Cluster of Excellence Multimodal Computing and Interaction, Saarbrücken, Germany
- affiliation (former): Edinburgh University, School of Informatics, UK
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2020 – today
- 2024
[i26]Frances Yung, Mansoor Ahmad, Merel C. J. Scholman, Vera Demberg:
Prompting Implicit Discourse Relation Annotation. CoRR abs/2402.04918 (2024)- [i25]Dongqi Pu, Yifan Wang, Jia E. Loy, Vera Demberg:
SciNews: From Scholarly Complexities to Public Narratives - A Dataset for Scientific News Report Generation. CoRR abs/2403.17768 (2024) - 2023
- [j8]Jia E. Loy, Vera Demberg:
Perspective Taking Reflects Beliefs About Partner Sophistication: Modern Computer Partners Versus Basic Computer and Human Partners. Cogn. Sci. 47(12) (2023) - [c91]Dongqi Pu, Vera Demberg:
ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfer. ACL (student) 2023: 1-18 - [c90]Dongqi Pu, Yifan Wang, Vera Demberg:
Incorporating Distributions of Discourse Structure for Long Document Abstractive Summarization. ACL (1) 2023: 5574-5590 - [c89]Ernie Chang, Muhammad Hassan Rashid, Pin-Jie Lin, Changsheng Zhao, Vera Demberg, Yangyang Shi, Vikas Chandra:
Revisiting Sample Size Determination in Natural Language Understanding. ACL (Findings) 2023: 6716-6724 - [c88]Xudong Hong, Vera Demberg, Asad B. Sayeed, Qiankun Zheng, Bernt Schiele
:
Visual Coherence Loss for Coherent and Visually Grounded Story Generation. ACL (Findings) 2023: 9456-9470 - [c87]Margarita Ryzhova, Iza Skrjanec, Nina Quach, Alice Virginia Chase, Emilia Ellsiepen, Vera Demberg:
Word Familiarity Classification From a Single Trial Based on Eye-Movements. A Study in German and English. ETRA 2023: 60:1-60:2 - [c86]Xudong Hong, Khushboo Mehra, Asad B. Sayeed, Vera Demberg:
Visually Grounded Story Generation Challenge. INLG (Generation Challenges) 2023: 17-22 - [c85]Saad Obaid ul Islam, Iza Skrjanec, Ondrej Dusek, Vera Demberg:
Tackling Hallucinations in Neural Chart Summarization. INLG 2023: 414-423 - [c84]Iza Skrjanec, Frederik Yannick Broy, Vera Demberg:
Expert-adapted language models improve the fit to reading times. KES 2023: 3488-3497 - [c83]Xudong Hong, Vera Demberg, Asad B. Sayeed, Qiankun Zheng, Bernt Schiele:
Visual Coherence Loss for Coherent and Visually Grounded Story Generation. RepL4NLP@ACL 2023: 334-346 - [c82]Frances Yung, Merel C. J. Scholman, Ekaterina Lapshinova-Koltunski, Christina Pollkläsener, Vera Demberg:
Investigating Explicitation of Discourse Connectives in Translation using Automatic Annotations. SIGDIAL 2023: 21-30 - [i24]Xudong Hong, Asad B. Sayeed, Khushboo Mehra, Vera Demberg, Bernt Schiele:
Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences. CoRR abs/2301.08571 (2023) - [i23]Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, Reut Tsarfaty, Ido Dagan, Vera Demberg:
Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design. CoRR abs/2304.00815 (2023) - [i22]Dongqi Pu, Yifan Wang, Vera Demberg:
Incorporating Distributions of Discourse Structure for Long Document Abstractive Summarization. CoRR abs/2305.16784 (2023) - [i21]Dongqi Pu, Vera Demberg:
ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfer. CoRR abs/2306.07799 (2023) - [i20]Ernie Chang, Muhammad Hassan Rashid, Pin-Jie Lin, Changsheng Zhao, Vera Demberg, Yangyang Shi, Vikas Chandra:
Revisiting Sample Size Determination in Natural Language Understanding. CoRR abs/2307.00374 (2023) - [i19]Saad Obaid ul Islam, Iza Skrjanec, Ondrej Dusek, Vera Demberg:
Tackling Hallucinations in Neural Chart Summarization. CoRR abs/2308.00399 (2023) - [i18]Xudong Hong, Margarita Ryzhova, Daniel Adrian Biondi, Vera Demberg:
Do large language models and humans have similar behaviors in causal inference with script knowledge? CoRR abs/2311.07311 (2023) - [i17]Tong Liu, Iza Skrjanec, Vera Demberg:
Improving fit to human reading times via temperature-scaled surprisal. CoRR abs/2311.09325 (2023) - 2022
- [j7]Marian Marchal, Merel C. J. Scholman, Vera Demberg:
The effect of domain knowledge and implicitation on discourse relation inferences. Dialogue Discourse 13(2): 49-78 (2022) - [c81]Ernie Chang, Alex Marin, Vera Demberg:
Programmable Annotation with Diversed Heuristics and Data Denoising. COLING 2022: 2681-2691 - [c80]Marian Marchal, Merel C. J. Scholman, Frances Yung, Vera Demberg:
Establishing Annotation Quality in Multi-label Annotations. COLING 2022: 3659-3668 - [c79]Fangzhou Zhai, Vera Demberg, Alexander Koller:
Zero-shot Script Parsing. COLING 2022: 4049-4060 - [c78]Ernie Chang, Jesujoba O. Alabi, David Ifeoluwa Adelani, Vera Demberg:
Few-Shot Pidgin Text Adaptation via Contrastive Fine-Tuning. COLING 2022: 4286-4291 - [c77]Ernie Chang, Alex Marin, Vera Demberg:
Improving Zero-Shot Multilingual Text Generation via Iterative Distillation. COLING 2022: 5876-5881 - [c76]Merel C. J. Scholman, Valentina Pyatkin, Frances Yung, Ido Dagan, Reut Tsarfaty, Vera Demberg:
Design Choices in Crowdsourcing Discourse Relation Annotations: The Effect of Worker Selection and Training. LREC 2022: 2148-2156 - [c75]Merel C. J. Scholman, Tianai Dong, Frances Yung, Vera Demberg:
DiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations. LREC 2022: 3281-3290 - [c74]Iza Skrjanec, Muhammad Salman Edhi, Vera Demberg:
Barch: an English Dataset of Bar Chart Summaries. LREC 2022: 3552-3560 - [c73]Ernie Chang, Alisa Kovtunova, Stefan Borgwardt, Vera Demberg, Kathryn Chapman, Hui-Syuan Yeh:
Logic-Guided Message Generation from Raw Real-Time Sensor Data. LREC 2022: 6899-6908 - [c72]Anupama Chingacham, Vera Demberg, Dietrich Klakow:
A Data-Driven Investigation of Noise-Adaptive Utterance Generation with Linguistic Modification. SLT 2022: 353-360 - [i16]Anupama Chingacham, Vera Demberg, Dietrich Klakow:
A Data-Driven Investigation of Noise-Adaptive Utterance Generation with Linguistic Modification. CoRR abs/2210.10252 (2022) - 2021
- [c71]Ernie Chang, Xiaoyu Shen, Hui-Syuan Yeh, Vera Demberg:
On Training Instance Selection for Few-Shot Neural Text Generation. ACL/IJCNLP (2) 2021: 8-13 - [c70]Wei Shi, Vera Demberg:
Entity Enhancement for Implicit Discourse Relation Classification in the Biomedical Domain. ACL/IJCNLP (2) 2021: 925-931 - [c69]Ernie Chang, Yow-Ting Shiue, Hui-Syuan Yeh, Vera Demberg:
Time-Aware Ancient Chinese Text Translation and Inference. LChange@ACL-IJCNLP 2021: 1-6 - [c68]Stefan Borgwardt, Ernie Chang, Kathryn Chapman, Vera Demberg, Alisa Kovtunova, Hui-Syuan Yeh:
Logic-Guided Neural Utterance Generation from Drone Sensory Data (Extended Abstract). Description Logics 2021 - [c67]Ernie Chang, Hui-Syuan Yeh, Vera Demberg:
Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learning. EACL 2021: 727-733 - [c66]Ernie Chang, Xiaoyu Shen, Dawei Zhu, Vera Demberg, Hui Su:
Neural Data-to-Text Generation with LM-based Text Augmentation. EACL 2021: 758-768 - [c65]Ernie Chang, Vera Demberg, Alex Marin:
Jointly Improving Language Understanding and Generation with Quality-Weighted Weak Supervision of Automatic Labeling. EACL 2021: 818-829 - [c64]Frederik Wiehr, Anke Hirsch, Lukas Schmitz, Nina Knieriemen, Antonio Krüger, Alisa Kovtunova, Stefan Borgwardt, Ernie Chang, Vera Demberg, Marcel Steinmetz, Jörg Hoffmann:
Why Do I Have to Take Over Control? Evaluating Safe Handovers with Advance Notice and Explanations in HAD. ICMI 2021: 308-317 - [c63]Ernie Chang, Xiaoyu Shen, Alex Marin, Vera Demberg:
The SelectGen Challenge: Finding the Best Training Samples for Few-Shot Neural Text Generation. INLG 2021: 325-330 - [c62]Anupama Chingacham, Vera Demberg, Dietrich Klakow:
Exploring the Potential of Lexical Paraphrases for Mitigating Noise-Induced Comprehension Errors. Interspeech 2021: 1713-1717 - [i15]Ernie Chang, Vera Demberg, Alex Marin:
Jointly Improving Language Understanding and Generation with Quality-Weighted Weak Supervision of Automatic Labeling. CoRR abs/2102.03551 (2021) - [i14]Ernie Chang, Hui-Syuan Yeh, Vera Demberg:
Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learning. CoRR abs/2102.03554 (2021) - [i13]Ernie Chang, Xiaoyu Shen, Dawei Zhu, Vera Demberg, Hui Su:
Neural Data-to-Text Generation with LM-based Text Augmentation. CoRR abs/2102.03556 (2021) - [i12]Ernie Chang, Xiaoyu Shen, Hui-Syuan Yeh, Vera Demberg:
On Training Instance Selection for Few-Shot Neural Text Generation. CoRR abs/2107.03176 (2021) - [i11]Ernie Chang, Yow-Ting Shiue, Hui-Syuan Yeh, Vera Demberg:
Time-Aware Ancient Chinese Text Translation and Inference. CoRR abs/2107.03179 (2021) - [i10]Anupama Chingacham, Vera Demberg, Dietrich Klakow:
Exploring the Potential of Lexical Paraphrases for Mitigating Noise-Induced Comprehension Errors. CoRR abs/2107.08337 (2021) - [i9]Ernie Chang, Xiaoyu Shen, Alex Marin, Vera Demberg:
The SelectGen Challenge: Finding the Best Training Samples for Few-Shot Neural Text Generation. CoRR abs/2108.06614 (2021) - 2020
- [c61]Margarita Ryzhova, Vera Demberg:
Processing particularized pragmatic inferences under load. CogSci 2020 - [c60]Ernie Chang, Jeriah Caplinger, Alex Marin, Xiaoyu Shen, Vera Demberg:
DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool. COLING (Demonstrations) 2020: 12-17 - [c59]Fangzhou Zhai, Vera Demberg, Alexander Koller:
Story Generation with Rich Details. COLING 2020: 2346-2351 - [c58]Xudong Hong, Rakshith Shetty, Asad B. Sayeed, Khushboo Mehra, Vera Demberg, Bernt Schiele:
Diverse and Relevant Visual Storytelling with Scene Graph Embeddings. CoNLL 2020: 420-430 - [c57]Ernie Chang, David Ifeoluwa Adelani, Xiaoyu Shen, Vera Demberg:
Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training. AfricaNLP 2020 - [i8]Ernie Chang, Jeriah Caplinger, Alex Marin, Xiaoyu Shen, Vera Demberg:
DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool. CoRR abs/2010.04141 (2020) - [i7]Frederik Wiehr, Anke Hirsch, Florian Daiber, Antonio Krüger, Alisa Kovtunova, Stefan Borgwardt, Ernie Chang, Vera Demberg, Marcel Steinmetz, Jörg Hoffmann:
Safe Handover in Mixed-Initiative Control for Cyber-Physical Systems. CoRR abs/2010.10967 (2020)
2010 – 2019
- 2019
- [c56]Frances Yung, Vera Demberg, Merel C. J. Scholman:
Crowdsourcing Discourse Relation Annotations by a Two-Step Connective Insertion Task. LAW@ACL 2019: 16-25 - [c55]Xudong Hong, Ernie Chang, Vera Demberg:
Improving Language Generation from Feature-Rich Tree-Structured Data with Relational Graph Convolutional Encoders. MSR@EMNLP-IJCNLP 2019: 75-80 - [c54]Wei Shi, Vera Demberg:
Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains. EMNLP/IJCNLP (1) 2019: 5789-5795 - [c53]Wei Shi, Vera Demberg:
Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification. IWCS (1) 2019: 188-199 - [e4]Simon Dobnik, Stergios Chatzikyriakidis, Vera Demberg:
Proceedings of the 13th International Conference on Computational Semantics, IWCS 2019, Long Papers, Gothenburg, Sweden, May 23-27 May, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-19-2 [contents] - [e3]Simon Dobnik, Stergios Chatzikyriakidis, Vera Demberg:
Proceedings of the 13th International Conference on Computational Semantics, IWCS 2019, Short Papers, Gothenburg, Sweden, May 23-27, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-20-8 [contents] - 2018
- [c52]Xiaoyu Shen, Hui Su, Shuzi Niu, Vera Demberg:
Improving Variational Encoder-Decoders in Dialogue Generation. AAAI 2018: 5456-5463 - [c51]Aleksandrs Berdicevskis, Çagri Çöltekin, Katharina Ehret, Kilu von Prince, Daniel Ross, Bill Thompson, Chunxiao Yan, Vera Demberg, Gary Lupyan, Taraka Rama, Christian Bentz:
Using Universal Dependencies in cross-linguistic complexity research. UDW@EMNLP 2018: 8-17 - [c50]David M. Howcroft, Dietrich Klakow, Vera Demberg:
Toward Bayesian Synchronous Tree Substitution Grammars for Sentence Planning. INLG 2018: 391-396 - [c49]Nelson Mukuze, Anna Rohrbach, Vera Demberg, Bernt Schiele:
A vision-grounded dataset for predicting typical locations for verbs. LREC 2018 - [c48]Asad B. Sayeed, Pavel Shkadzko, Vera Demberg:
Rollenwechsel-English: a large-scale semantic role corpus. LREC 2018 - [c47]Xudong Hong, Asad B. Sayeed, Vera Demberg:
Learning distributed event representations with a multi-task approach. *SEM@NAACL-HLT 2018: 11-21 - [i6]Xiaoyu Shen, Hui Su, Shuzi Niu, Vera Demberg:
Improving Variational Encoder-Decoders in Dialogue Generation. CoRR abs/1802.02032 (2018) - [i5]Wei Shi, Frances Yung, Vera Demberg:
Acquiring Annotated Data with Cross-lingual Explicitation for Implicit Discourse Relation Classification. CoRR abs/1808.10290 (2018) - [i4]Wei Shi, Vera Demberg:
Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification. CoRR abs/1811.01697 (2018) - 2017
- [j6]Merel C. J. Scholman, Vera Demberg:
Examples and Specifications that Prove a Point: Identifying Elaborative and Argumentative Discourse Relations. Dialogue Discourse 8(2): 56-83 (2017) - [j5]Ashutosh Modi, Ivan Titov, Vera Demberg, Asad B. Sayeed, Manfred Pinkal:
Modelling Semantic Expectation: Using Script Knowledge for Referent Prediction. Trans. Assoc. Comput. Linguistics 5: 31-44 (2017) - [c46]Merel C. J. Scholman, Vera Demberg:
Crowdsourcing discourse interpretations: On the influence of context and the reliability of a connective insertion task. LAW@ACL 2017: 24-33 - [c45]Katja Häuser, Vera Demberg, Jutta Kray:
Age differences in language comprehension during driving: Recovery from prediction errors is more effortful for older adults. CogSci 2017 - [c44]Wei Shi, Vera Demberg:
Do We Need Cross Validation for Discourse Relation Classification? EACL (2) 2017: 150-156 - [c43]Attapol Rutherford, Vera Demberg, Nianwen Xue:
A Systematic Study of Neural Discourse Models for Implicit Discourse Relation. EACL (1) 2017: 281-291 - [c42]David M. Howcroft, Vera Demberg:
Psycholinguistic Models of Sentence Processing Improve Sentence Readability Ranking. EACL (1) 2017: 958-968 - [c41]Wei Shi, Frances Yung, Raphael Rubino, Vera Demberg:
Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification. IJCNLP(1) 2017: 484-495 - [c40]David M. Howcroft, Jorrig Vogels, Vera Demberg:
G-TUNA: a corpus of referring expressions in German, including duration information. INLG 2017: 149-153 - [c39]David M. Howcroft, Dietrich Klakow, Vera Demberg:
The Extended SPaRKy Restaurant Corpus: Designing a Corpus with Variable Information Density. INTERSPEECH 2017: 3757-3761 - [i3]Ashutosh Modi, Ivan Titov, Vera Demberg, Asad B. Sayeed, Manfred Pinkal:
Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction. CoRR abs/1702.03121 (2017) - [i2]Vera Demberg, Fatemeh Torabi Asr, Merel C. J. Scholman:
How consistent are our discourse annotations? Insights from mapping RST-DT and PDTB annotations. CoRR abs/1704.08893 (2017) - 2016
- [j4]Vera Demberg, Jörg Hoffmann, David M. Howcroft, Dietrich Klakow, Álvaro Torralba:
Search Challenges in Natural Language Generation with Complex Optimization Objectives. Künstliche Intell. 30(1): 63-69 (2016) - [j3]Matthew W. Crocker, Vera Demberg, Elke Teich:
Information Density and Linguistic Encoding (IDeaL). Künstliche Intell. 30(1): 77-81 (2016) - [c38]Asad B. Sayeed, Xudong Hong, Vera Demberg:
Roleo: Visualising Thematic Fit Spaces on the Web. ACL (System Demonstrations) 2016: 139-144 - [c37]Fatemeh Torabi Asr, Vera Demberg:
But vs. Although under the microscope. CogSci 2016 - [c36]Maximilian Schwenger, Álvaro Torralba, Jörg Hoffmann, David M. Howcroft, Vera Demberg:
From OpenCCG to AI Planning: Detecting Infeasible Edges in Sentence Generation. COLING 2016: 1524-1534 - [c35]Ottokar Tilk, Vera Demberg, Asad B. Sayeed, Dietrich Klakow, Stefan Thater:
Event participant modelling with neural networks. EMNLP 2016: 171-182 - [c34]Vera Demberg:
How can we adapt generation to the user's cognitive load? INLG 2016: 132 - [c33]Ines Rehbein, Merel C. J. Scholman, Vera Demberg:
Annotating Discourse Relations in Spoken Language: A Comparison of the PDTB and CCR Frameworks. LREC 2016 - [c32]Florian Pusse, Asad B. Sayeed, Vera Demberg:
LingoTurk: managing crowdsourced tasks for psycholinguistics. HLT-NAACL Demos 2016: 57-61 - [c31]Simon Ahrendt, Vera Demberg:
Improving event prediction by representing script participants. HLT-NAACL 2016: 546-551 - [c30]Asad Basheer Sayeed, Clayton Greenberg, Vera Demberg:
Thematic fit evaluation: an aspect of selectional preferences. RepEval@ACL 2016: 99-105 - [i1]Attapol T. Rutherford, Vera Demberg, Nianwen Xue:
Neural Network Models for Implicit Discourse Relation Classification in English and Chinese without Surface Features. CoRR abs/1606.01990 (2016) - 2015
- [c29]Asad B. Sayeed, Stefan Fischer, Vera Demberg:
Vector-space calculation of semantic surprisal for predicting word pronunciation duration. ACL (1) 2015: 763-773 - [c28]Clayton Greenberg, Vera Demberg, Asad B. Sayeed:
Verb polysemy and frequency effects in thematic fit modeling. CMCL@NAACL-HLT 2015: 48-57 - [c27]Ekaterina Kravtchenko, Vera Demberg:
Semantically underinformative utterances trigger pragmatic inferences. CogSci 2015 - [c26]Andrea K. Fischer, Vera Demberg, Dietrich Klakow:
Towards Flexible, Small-Domain Surface Generation: Combining Data-Driven and Grammatical Approaches. ENLG 2015: 105-108 - [c25]Fatemeh Torabi Asr, Vera Demberg:
Uniform Surprisal at the Level of Discourse Relations: Negation Markers and Discourse Connective Omission. IWCS 2015: 118-128 - [c24]Clayton Greenberg, Asad B. Sayeed, Vera Demberg:
Improving unsupervised vector-space thematic fit evaluation via role-filler prototype clustering. HLT-NAACL 2015: 21-31 - [c23]Rachel Rudinger, Vera Demberg, Ashutosh Modi, Benjamin Van Durme, Manfred Pinkal:
Learning to predict script events from domain-specific text. *SEM@NAACL-HLT 2015: 205-210 - 2014
- [c22]Heiner Drenhaus, Vera Demberg, Judith Köhne, Francesca Delogu:
Incremental and predictive discourse processing based on causal and concessive discourse markers: ERP studies on German and English. CogSci 2014 - [c21]Ioannis Konstas, Frank Keller, Vera Demberg, Mirella Lapata:
Incremental Semantic Role Labeling with Tree Adjoining Grammar. EMNLP 2014: 301-312 - [e2]Vera Demberg, Timothy O'Donnell:
Proceedings of the Fifth Workshop on Cognitive Modeling and Computational Linguistics, CMCL@ACL 2014, Baltimore, Maryland, USA, June 26, 2014. Association for Computational Linguistics 2014, ISBN 978-1-941643-05-1 [contents] - 2013
- [j2]Vera Demberg, Frank Keller, Alexander Koller:
Incremental, Predictive Parsing with Psycholinguistically Motivated Tree-Adjoining Grammar. Comput. Linguistics 39(4): 1025-1066 (2013) - [c20]Asad B. Sayeed, Vera Demberg:
The semantic augmentation of a psycholinguistically-motivated syntactic formalism. CMCL 2013: 57-65 - [c19]Fatemeh Torabi Asr, Vera Demberg:
On the Information Conveyed by Discourse Markers. CMCL 2013: 84-93 - [c18]Vera Demberg, Asad B. Sayeed, Angela Mahr, Christian A. Müller:
Measuring linguistically-induced cognitive load during driving using the ConTRe task. AutomotiveUI 2013: 176-183 - [c17]Vera Demberg:
Pupillometry: the Index of Cognitive Activity in a dual-task study. CogSci 2013 - [c16]Vera Demberg:
Integration Costs on Auxiliaries? - a self-paced reading study using WebExp. CogSci 2013 - [c15]Vera Demberg, Evangelia Kiagia, Asad B. Sayeed:
The Index of Cognitive Activity as a Measure of Linguistic Processing. CogSci 2013 - [c14]Nikolaos Engonopoulos, Asad B. Sayeed, Vera Demberg:
Language and cognitive load in a dual task environment. CogSci 2013 - [c13]Judith Köhne, Vera Demberg:
The time-course of processing discourse connectives. CogSci 2013 - [c12]Silas Weinbach, Vera Demberg:
Identifying Predictive Collocations. CogSci 2013 - [e1]Vera Demberg, Roger Levy:
Proceedings of the Fourth Annual Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2013, Sofia, Bulgaria, August 8, 2013. Association for Computational Linguistics 2013, ISBN 978-1-937284-61-9 [contents] - 2012
- [c11]Fatemeh Torabi Asr, Vera Demberg:
Implicitness of Discourse Relations. COLING 2012: 2669-2684 - [c10]Vera Demberg, Asad B. Sayeed, Philip Gorinski, Nikolaos Engonopoulos:
Syntactic Surprisal Affects Spoken Word Duration in Conversational Contexts. EMNLP-CoNLL 2012: 356-367 - [c9]Miriam Kaeshammer, Vera Demberg:
German and English Treebanks and Lexica for Tree-Adjoining Grammars. LREC 2012: 1880-1887 - [c8]Asad B. Sayeed, Vera Demberg:
Incremental Neo-Davidsonian semantic construction for TAG. TAG 2012: 64-72 - [c7]Vera Demberg:
Incremental Derivations in CCG. TAG 2012: 198-206 - 2011
- [j1]Vera Demberg, Andi Winterboer, Johanna D. Moore:
A Strategy for Information Presentation in Spoken Dialog Systems. Comput. Linguistics 37(3): 489-539 (2011) - 2010
- [c6]Jeff Mitchell, Mirella Lapata, Vera Demberg, Frank Keller:
Syntactic and Semantic Factors in Processing Difficulty: An Integrated Measure. ACL 2010: 196-206
2000 – 2009
- 2008
- [c5]Martin I. Tietze, Vera Demberg, Johanna D. Moore:
Syntactic complexity induces explicit grounding in the Maptask corpus. INTERSPEECH 2008: 542 - [c4]Vera Demberg, Frank Keller:
A Psycholinguistically Motivated Version of TAG. TAG 2008: 25-32 - 2007
- [c3]Vera Demberg:
A Language-Independent Unsupervised Model for Morphological Segmentation. ACL 2007 - [c2]Vera Demberg, Helmut Schmid, Gregor Möhler:
Phonological Constraints and Morphological Preprocessing for Grapheme-to-Phoneme Conversion. ACL 2007 - 2006
- [c1]Vera Demberg, Johanna D. Moore:
Information Presentation in Spoken Dialogue Systems. EACL 2006
Coauthor Index
Asad B. Sayeed
aka: Asad Basheer Sayeed
aka: Asad Basheer Sayeed
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