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ORCIDDavid Schlangen
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- affiliation: University of Potsdam, Potsdam, Germany
- affiliation (former): Bielefeld University, Bielefeld, Germany
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2020 – today
- 2024
[c125]Brielen Madureira, Patrick Kahardipraja, David Schlangen:
When Only Time Will Tell: Interpreting How Transformers Process Local Ambiguities Through the Lens of Restart-Incrementality. ACL (1) 2024: 4722-4749- [c124]Julian Hough, Sina Zarrieß, Casey Kennington, David Schlangen, Massimo Poesio:
Conceptual Pacts for Reference Resolution Using Small, Dynamically Constructed Language Models: A Study in Puzzle Building Dialogues. LREC/COLING 2024: 3689-3699 - [c123]Philipp Sadler, Sherzod Hakimov, David Schlangen:
Sharing the Cost of Success: A Game for Evaluating and Learning Collaborative Multi-Agent Instruction Giving and Following Policies. LREC/COLING 2024: 14770-14783 - [c122]Kranti Chalamalasetti, Sherzod Hakimov, David Schlangen:
Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft. EMNLP (Findings) 2024: 11159-11170 - [c121]Luka Borec, Philipp Sadler, David Schlangen:
The Unreasonable Ineffectiveness of Nucleus Sampling on Mitigating Text Memorization. INLG 2024: 358-370 - [c120]Brielen Madureira, David Schlangen:
It Couldn't Help but Overhear: On the Limits of Modelling Meta-Communicative Grounding Acts with Supervised Learning. SIGDIAL 2024: 149-158 - [c119]Isidora Jeknic, David Schlangen, Alexander Koller:
A Dialogue Game for Eliciting Balanced Collaboration. SIGDIAL 2024: 477-489 - [i43]Brielen Madureira, David Schlangen:
Taking Action Towards Graceful Interaction: The Effects of Performing Actions on Modelling Policies for Instruction Clarification Requests. CoRR abs/2401.17039 (2024) - [i42]Philipp Sadler, Sherzod Hakimov, David Schlangen:
Learning Communication Policies for Different Follower Behaviors in a Collaborative Reference Game. CoRR abs/2402.04824 (2024) - [i41]Brielen Madureira
, Patrick Kahardipraja, David Schlangen:
When Only Time Will Tell: Interpreting How Transformers Process Local Ambiguities Through the Lens of Restart-Incrementality. CoRR abs/2402.13113 (2024) - [i40]Philipp Sadler, Sherzod Hakimov, David Schlangen:
Sharing the Cost of Success: A Game for Evaluating and Learning Collaborative Multi-Agent Instruction Giving and Following Policies. CoRR abs/2403.17497 (2024) - [i39]Brielen Madureira, David Schlangen:
It Couldn't Help But Overhear: On the Limits of Modelling Meta-Communicative Grounding Acts with Supervised Learning. CoRR abs/2405.01139 (2024) - [i38]Anne Beyer, Kranti Chalamalasetti, Sherzod Hakimov, Brielen Madureira, Philipp Sadler, David Schlangen:
clembench-2024: A Challenging, Dynamic, Complementary, Multilingual Benchmark and Underlying Flexible Framework for LLMs as Multi-Action Agents. CoRR abs/2405.20859 (2024) - [i37]Isidora Jeknic, David Schlangen, Alexander Koller:
A Dialogue Game for Eliciting Balanced Collaboration. CoRR abs/2406.08202 (2024) - [i36]Sherzod Hakimov, Yerkezhan Abdullayeva, Kushal Koshti, Antonia Schmidt, Yan Weiser, Anne Beyer, David Schlangen:
Two Giraffes in a Dirt Field: Using Game Play to Investigate Situation Modelling in Large Multimodal Models. CoRR abs/2406.14035 (2024) - [i35]Nidhir Bhavsar, Jonathan Jordan, Sherzod Hakimov, David Schlangen:
How Many Parameters Does it Take to Change a Light Bulb? Evaluating Performance in Self-Play of Conversational Games as a Function of Model Characteristics. CoRR abs/2406.14051 (2024) - [i34]Chalamalasetti Kranti, Sherzod Hakimov, David Schlangen:
Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft. CoRR abs/2406.17553 (2024) - [i33]Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, Desmond Elliott, Raquel Fernández, Albert Gatt, Esam Ghaleb, Mario Giulianelli, Michael Hanna, Alexander Koller, André F. T. Martins, Philipp Mondorf, Vera Neplenbroek, Sandro Pezzelle, Barbara Plank, David Schlangen, Alessandro Suglia, Aditya K. Surikuchi, Ece Takmaz, Alberto Testoni:
LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks. CoRR abs/2406.18403 (2024) - [i32]David Schlangen:
LLMs as Function Approximators: Terminology, Taxonomy, and Questions for Evaluation. CoRR abs/2407.13744 (2024) - [i31]Luka Borec, Philipp Sadler, David Schlangen:
The Unreasonable Ineffectiveness of Nucleus Sampling on Mitigating Text Memorization. CoRR abs/2408.16345 (2024) - [i30]Chalamalasetti Kranti, Sherzod Hakimov, David Schlangen:
Towards No-Code Programming of Cobots: Experiments with Code Synthesis by Large Code Models for Conversational Programming. CoRR abs/2409.11041 (2024) - 2023
- [j10]Mark Dingemanse, Andreas Liesenfeld, Marlou Rasenberg, Saul Albert, Felix K. Ameka, Abeba Birhane, Dimitris Bolis, Justine Cassell, Rebecca Clift, Elena Cuffari, Hanne De Jaegher, Catarina Dutilh Novaes, Nicholas J. Enfield, Riccardo Fusaroli, Eleni Gregoromichelaki, Edwin Hutchins, Ivana Konvalinka, Damian Milton, Joanna Raczaszek-Leonardi, Vasudevi Reddy, Federico Rossano, David Schlangen, Johanna Seibt, Elizabeth Stokoe, Lucy A. Suchman, Cordula Vesper, Thalia Wheatley, Martina Wiltschko:
Beyond Single-Mindedness: A Figure-Ground Reversal for the Cognitive Sciences. Cogn. Sci. 47(1) (2023) - [c118]Patrick Kahardipraja, Brielen Madureira, David Schlangen:
TAPIR: Learning Adaptive Revision for Incremental Natural Language Understanding with a Two-Pass Model. ACL (Findings) 2023: 4173-4197 - [c117]Philipp Sadler, Sherzod Hakimov, David Schlangen:
Yes, this Way! Learning to Ground Referring Expressions into Actions with Intra-episodic Feedback from Supportive Teachers. ACL (Findings) 2023: 9228-9239 - [c116]Sherzod Hakimov, David Schlangen:
Images in Language Space: Exploring the Suitability of Large Language Models for Vision & Language Tasks. ACL (Findings) 2023: 14196-14210 - [c115]Brielen Madureira, Pelin Çelikkol, David Schlangen:
Revising with a Backward Glance: Regressions and Skips during Reading as Cognitive Signals for Revision Policies in Incremental Processing. CoNLL 2023: 335-351 - [c114]Philipp Sadler, David Schlangen:
Pento-DIARef: A Diagnostic Dataset for Learning the Incremental Algorithm for Referring Expression Generation from Examples. EACL 2023: 2098-2114 - [c113]Brielen Madureira, David Schlangen:
Instruction Clarification Requests in Multimodal Collaborative Dialogue Games: Tasks, and an Analysis of the CoDraw Dataset. EACL 2023: 2295-2311 - [c112]David Schlangen:
On General Language Understanding. EMNLP (Findings) 2023: 8818-8825 - [c111]Kranti Chalamalasetti, Jana Götze, Sherzod Hakimov, Brielen Madureira, Philipp Sadler, David Schlangen:
clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents. EMNLP 2023: 11174-11219 - [c110]Pelin Çelikkol, Jochen Laubrock, David Schlangen:
TF-IDF based Scene-Object Relations Correlate With Visual Attention. ETRA 2023: 21:1-21:6 - [c109]Brielen Madureira, Patrick Kahardipraja, David Schlangen:
The Road to Quality is Paved with Good Revisions: A Detailed Evaluation Methodology for Revision Policies in Incremental Sequence Labelling. SIGDIAL 2023: 156-167 - [e3]David Schlangen, Svetlana Stoyanchev, Shafiq Joty, Ondrej Dusek, Casey Kennington, Malihe Alikhani:
Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2023, Prague, Czechia, September 11 - 15, 2023. Association for Computational Linguistics 2023, ISBN 979-8-89176-028-8 [contents] - [i29]David Schlangen:
What A Situated Language-Using Agent Must be Able to Do: A Top-Down Analysis. CoRR abs/2302.08590 (2023) - [i28]Brielen Madureira, David Schlangen:
Instruction Clarification Requests in Multimodal Collaborative Dialogue Games: Tasks, and an Analysis of the CoDraw Dataset. CoRR abs/2302.14406 (2023) - [i27]David Schlangen:
Dialogue Games for Benchmarking Language Understanding: Motivation, Taxonomy, Strategy. CoRR abs/2304.07007 (2023) - [i26]Patrick Kahardipraja, Brielen Madureira, David Schlangen:
TAPIR: Learning Adaptive Revision for Incremental Natural Language Understanding with a Two-Pass Model. CoRR abs/2305.10845 (2023) - [i25]Philipp Sadler, Sherzod Hakimov, David Schlangen:
Yes, this Way! Learning to Ground Referring Expressions into Actions with Intra-episodic Feedback from Supportive Teachers. CoRR abs/2305.12880 (2023) - [i24]Kranti Chalamalasetti, Jana Götze, Sherzod Hakimov, Brielen Madureira, Philipp Sadler, David Schlangen:
clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents. CoRR abs/2305.13455 (2023) - [i23]Sherzod Hakimov, David Schlangen:
Images in Language Space: Exploring the Suitability of Large Language Models for Vision & Language Tasks. CoRR abs/2305.13782 (2023) - [i22]Philipp Sadler, David Schlangen:
Pento-DIARef: A Diagnostic Dataset for Learning the Incremental Algorithm for Referring Expression Generation from Examples. CoRR abs/2305.15087 (2023) - [i21]Brielen Madureira, David Schlangen:
"Are you telling me to put glasses on the dog?" Content-Grounded Annotation of Instruction Clarification Requests in the CoDraw Dataset. CoRR abs/2306.02377 (2023) - [i20]Brielen Madureira, Patrick Kahardipraja, David Schlangen:
The Road to Quality is Paved with Good Revisions: A Detailed Evaluation Methodology for Revision Policies in Incremental Sequence Labelling. CoRR abs/2307.15508 (2023) - [i19]Fabian Galetzka, Anne Beyer, David Schlangen:
Neural Conversation Models and How to Rein Them in: A Survey of Failures and Fixes. CoRR abs/2308.06095 (2023) - [i18]David Schlangen:
On General Language Understanding. CoRR abs/2310.18038 (2023) - [i17]Brielen Madureira, Pelin Çelikkol, David Schlangen:
Revising with a Backward Glance: Regressions and Skips during Reading as Cognitive Signals for Revision Policies in Incremental Processing. CoRR abs/2310.18229 (2023) - 2022
- [c108]Brielen Madureira, David Schlangen:
Can Visual Dialogue Models Do Scorekeeping? Exploring How Dialogue Representations Incrementally Encode Shared Knowledge. ACL (2) 2022: 651-664 - [c107]Sharid Loáiciga, Anne Beyer, David Schlangen:
New or Old? Exploring How Pre-Trained Language Models Represent Discourse Entities. COLING 2022: 875-886 - [c106]Jana Götze, Maike Paetzel-Prüsmann, Wencke Liermann, Tim Diekmann, David Schlangen:
The slurk Interaction Server Framework: Better Data for Better Dialog Models. LREC 2022: 4069-4078 - [i16]Jana Götze, Maike Paetzel-Prüsmann, Wencke Liermann, Tim Diekmann, David Schlangen:
The slurk Interaction Server Framework: Better Data for Better Dialog Models. CoRR abs/2202.01155 (2022) - [i15]Brielen Madureira, David Schlangen:
Can Visual Dialogue Models Do Scorekeeping? Exploring How Dialogue Representations Incrementally Encode Shared Knowledge. CoRR abs/2204.06970 (2022) - [i14]David Schlangen:
Norm Participation Grounds Language. CoRR abs/2206.02885 (2022) - 2021
- [c105]David Schlangen:
Targeting the Benchmark: On Methodology in Current Natural Language Processing Research. ACL/IJCNLP (2) 2021: 670-674 - [c104]Fabian Galetzka, Jewgeni Rose, David Schlangen, Jens Lehmann:
Space Efficient Context Encoding for Non-Task-Oriented Dialogue Generation with Graph Attention Transformer. ACL/IJCNLP (1) 2021: 7028-7041 - [c103]Patrick Kahardipraja, Brielen Madureira, David Schlangen:
Towards Incremental Transformers: An Empirical Analysis of Transformer Models for Incremental NLU. EMNLP (1) 2021: 1178-1189 - [c102]Anne Beyer, Sharid Loáiciga, David Schlangen:
Is Incoherence Surprising? Targeted Evaluation of Coherence Prediction from Language Models. NAACL-HLT 2021: 4164-4173 - [i13]Anne Beyer, Sharid Loáiciga, David Schlangen:
Is Incoherence Surprising? Targeted Evaluation of Coherence Prediction from Language Models. CoRR abs/2105.03495 (2021) - [i12]Patrick Kahardipraja, Brielen Madureira, David Schlangen:
Towards Incremental Transformers: An Empirical Analysis of Transformer Models for Incremental NLU. CoRR abs/2109.07364 (2021) - 2020
- [c101]Brielen Madureira, David Schlangen:
Incremental Processing in the Age of Non-Incremental Encoders: An Empirical Assessment of Bidirectional Models for Incremental NLU. EMNLP (1) 2020: 357-374 - [c100]Robin Rojowiec, Jana Götze, Philipp Sadler, Henrik Voigt, Sina Zarrieß, David Schlangen:
From "Before" to "After": Generating Natural Language Instructions from Image Pairs in a Simple Visual Domain. INLG 2020: 316-326 - [c99]Fabian Galetzka, Chukwuemeka Uchenna Eneh, David Schlangen:
A Corpus of Controlled Opinionated and Knowledgeable Movie Discussions for Training Neural Conversation Models. LREC 2020: 565-573 - [e2]Qun Liu, David Schlangen:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, EMNLP 2020 - Demos, Online, November 16-20, 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-62-0 [contents] - [i11]Fabian Galetzka, Chukwuemeka Uchenna Eneh, David Schlangen:
A Corpus of Controlled Opinionated and Knowledgeable Movie Discussions for Training Neural Conversation Models. CoRR abs/2003.13342 (2020) - [i10]David Schlangen:
Targeting the Benchmark: On Methodology in Current Natural Language Processing Research. CoRR abs/2007.04792 (2020) - [i9]Brielen Madureira, David Schlangen:
An Overview of Natural Language State Representation for Reinforcement Learning. CoRR abs/2007.09774 (2020) - [i8]Brielen Madureira, David Schlangen:
Incremental Processing in the Age of Non-Incremental Encoders: An Empirical Assessment of Bidirectional Models for Incremental NLU. CoRR abs/2010.05330 (2020)
2010 – 2019
- 2019
- [c98]Sina Zarrieß, David Schlangen:
Know What You Don't Know: Modeling a Pragmatic Speaker that Refers to Objects of Unknown Categories. ACL (1) 2019: 654-659 - [c97]Nikolai Ilinykh, Sina Zarrieß, David Schlangen:
Tell Me More: A Dataset of Visual Scene Description Sequences. INLG 2019: 152-157 - [c96]Philipp Sadler, Tatjana Scheffler, David Schlangen:
Can Neural Image Captioning be Controlled via Forced Attention? INLG 2019: 427-431 - [c95]David Schlangen:
Natural Language Semantics With Pictures: Some Language & Vision Datasets and Potential Uses for Computational Semantics. IWCS (1) 2019: 283-294 - [c94]Nazia Attari, Martin Heckmann, David Schlangen:
From Explainability to Explanation: Using a Dialogue Setting to Elicit Annotations with Justifications. SIGdial 2019: 331-335 - [i7]David Schlangen:
Natural Language Semantics With Pictures: Some Language & Vision Datasets and Potential Uses for Computational Semantics. CoRR abs/1904.07318 (2019) - [i6]Sina Zarrieß, David Schlangen:
Know What You Don't Know: Modeling a Pragmatic Speaker that Refers to Objects of Unknown Categories. CoRR abs/1906.05518 (2019) - [i5]Nikolai Ilinykh, Sina Zarrieß, David Schlangen:
MeetUp! A Corpus of Joint Activity Dialogues in a Visual Environment. CoRR abs/1907.05084 (2019) - [i4]David Schlangen:
Language Tasks and Language Games: On Methodology in Current Natural Language Processing Research. CoRR abs/1908.10747 (2019) - [i3]David Schlangen:
Grounded Agreement Games: Emphasizing Conversational Grounding in Visual Dialogue Settings. CoRR abs/1908.11279 (2019) - [i2]Philipp Sadler, Tatjana Scheffler, David Schlangen:
Can Neural Image Captioning be Controlled via Forced Attention? CoRR abs/1911.03936 (2019) - 2018
- [c93]Ting Han, Casey Kennington, David Schlangen:
Placing Objects in Gesture Space: Toward Incremental Interpretation of Multimodal Spatial Descriptions. AAAI 2018: 5157-5164 - [c92]Birte Carlmeyer, Simon Betz, Petra Wagner, Britta Wrede, David Schlangen:
The Hesitating Robot - Implementation and First Impressions. HRI (Companion) 2018: 77-78 - [c91]Nikolai Ilinykh, Sina Zarrieß, David Schlangen:
The Task Matters: Comparing Image Captioning and Task-Based Dialogical Image Description. INLG 2018: 397-402 - [c90]Sina Zarrieß, David Schlangen:
Decoding Strategies for Neural Referring Expression Generation. INLG 2018: 503-512 - [c89]Soledad López Gambino, Sina Zarrieß, David Schlangen:
Testing Strategies For Bridging Time-To-Content In Spoken Dialogue Systems. IWSDS 2018: 103-109 - [c88]Ting Han, David Schlangen:
A Corpus of Natural Multimodal Spatial Scene Descriptions. LREC 2018 - 2017
- [j9]Casey Kennington, David Schlangen:
A simple generative model of incremental reference resolution for situated dialogue. Comput. Speech Lang. 41: 43-67 (2017) - [c87]Sina Zarrieß, David Schlangen:
Obtaining referential word meanings from visual and distributional information: Experiments on object naming. ACL (1) 2017: 243-254 - [c86]Sina Zarrieß, David Schlangen:
Is this a Child, a Girl or a Car? Exploring the Contribution of Distributional Similarity to Learning Referential Word Meanings. EACL (2) 2017: 86-91 - [c85]Julian Hough, David Schlangen:
Joint, Incremental Disfluency Detection and Utterance Segmentation from Speech. EACL (1) 2017: 326-336 - [c84]Ting Han, David Schlangen:
Grounding Language by Continuous Observation of Instruction Following. EACL (2) 2017: 491-496 - [c83]Sina Zarrieß, David Schlangen:
Deriving continous grounded meaning representations from referentially structured multimodal contexts. EMNLP 2017: 959-965 - [c82]Julian Hough, David Schlangen:
It's Not What You Do, It's How You Do It: Grounding Uncertainty for a Simple Robot. HRI 2017: 274-282 - [c81]Casey Kennington, Ting Han, David Schlangen:
Temporal alignment using the incremental unit framework. ICMI 2017: 297-301 - [c80]Ting Han, Julian Hough, David Schlangen:
Natural Language Informs the Interpretation of Iconic Gestures: A Computational Approach. IJCNLP(2) 2017: 134-139 - [c79]Ting Han, David Schlangen:
Draw and Tell: Multimodal Descriptions Outperform Verbal- or Sketch-Only Descriptions in an Image Retrieval Task. IJCNLP(2) 2017: 361-365 - [c78]Sina Zarrieß, Soledad López Gambino, David Schlangen:
Refer-iTTS: A System for Referring in Spoken Installments to Objects in Real-World Images. INLG 2017: 72-73 - [c77]Angelika Maier, Julian Hough, David Schlangen:
Towards Deep End-of-Turn Prediction for Situated Spoken Dialogue Systems. INTERSPEECH 2017: 1676-1680 - [c76]Soledad López Gambino, Casey Kennington, David Schlangen:
Silence, Please! Interrupting In-Car Phone Conversations. WCIHAI@IVA 2017: 9-18 - [c75]Iwan de Kok, Felix Hülsmann, Thomas Waltemate, Cornelia Frank, Julian Hough, Thies Pfeiffer, David Schlangen, Thomas Schack, Mario Botsch, Stefan Kopp:
The Intelligent Coaching Space: A Demonstration. IVA 2017: 105-108 - [c74]Soledad López Gambino, Sina Zarrieß, David Schlangen:
Beyond On-hold Messages: Conversational Time-buying in Task-oriented Dialogue. SIGDIAL Conference 2017: 241-246 - 2016
- [j8]Sean Andrist, Dan Bohus, Bilge Mutlu, David Schlangen:
Turn-Taking and Coordination in Human-Machine Interaction. AI Mag. 37(4): 5-6 (2016) - [c73]David Schlangen, Sina Zarrieß, Casey Kennington:
Resolving References to Objects in Photographs using the Words-As-Classifiers Model. ACL (1) 2016 - [c72]Sina Zarrieß, David Schlangen:
Easy Things First: Installments Improve Referring Expression Generation for Objects in Photographs. ACL (1) 2016 - [c71]Viktor Richter, Birte Carlmeyer, Florian Lier, Sebastian Meyer zu Borgsen, David Schlangen, Franz Kummert, Sven Wachsmuth, Britta Wrede:
Are you talking to me?: Improving the Robustness of Dialogue Systems in a Multi Party HRI Scenario by Incorporating Gaze Direction and Lip Movement of Attendees. HAI 2016: 43-50 - [c70]Birte Carlmeyer, David Schlangen, Britta Wrede:
"Look at Me!": Self-Interruptions as Attention Booster? HAI 2016: 221-224 - [c69]Birte Carlmeyer, David Schlangen, Britta Wrede:
Exploring self-interruptions as a strategy for regaining the attention of distracted users. EISE@ICMI 2016: 4:1-4:6 - [c68]Iwan de Kok, Julian Hough, David Schlangen, Stefan Kopp:
Deictic gestures in coaching interactions. MA3HMI@ICMI 2016: 10-14 - [c67]Sina Zarrieß, David Schlangen:
Towards Generating Colour Terms for Referents in Photographs: Prefer the Expected or the Unexpected? INLG 2016: 246-255 - [c66]Timo Baumann, Casey Kennington, Julian Hough, David Schlangen:
Recognising Conversational Speech: What an Incremental ASR Should Do for a Dialogue System and How to Get There. IWSDS 2016: 421-432 - [c65]Patrick Holthaus, Christian Leichsenring, Jasmin Bernotat, Viktor Richter, Marian Pohling, Birte Carlmeyer, Norman Köster, Sebastian Meyer zu Borgsen, René Zorn, Birte Schiffhauer, Kai Frederic Engelmann, Florian Lier, Simon Schulz, Philipp Cimiano, Friederike Eyssel, Thomas Hermann, Franz Kummert, David Schlangen, Sven Wachsmuth, Petra Wagner, Britta Wrede, Sebastian Wrede:
How to Address Smart Homes with a Social Robot? A Multi-modal Corpus of User Interactions with an Intelligent Environment. LREC 2016 - [c64]Julian Hough, Ye Tian, Laura E. de Ruiter, Simon Betz, Spyros Kousidis, David Schlangen, Jonathan Ginzburg:
DUEL: A Multi-lingual Multimodal Dialogue Corpus for Disfluency, Exclamations and Laughter. LREC 2016 - [c63]Sina Zarrieß, Julian Hough, Casey Kennington, Ramesh R. Manuvinakurike, David DeVault, Raquel Fernández, David Schlangen:
PentoRef: A Corpus of Spoken References in Task-oriented Dialogues. LREC 2016 - [c62]Ramesh R. Manuvinakurike, Casey Kennington, David DeVault, David Schlangen:
Real-Time Understanding of Complex Discriminative Scene Descriptions. SIGDIAL Conference 2016: 232-241 - [c61]Casey Kennington, David Schlangen:
Supporting Spoken Assistant Systems with a Graphical User Interface that Signals Incremental Understanding and Prediction State. SIGDIAL Conference 2016: 242-251 - [c60]Ramesh R. Manuvinakurike, Maike Paetzel, Cheng Qu, David Schlangen, David DeVault:
Toward incremental dialogue act segmentation in fast-paced interactive dialogue systems. SIGDIAL Conference 2016: 252-262 - [c59]Julian Hough, David Schlangen:
Investigating Fluidity for Human-Robot Interaction with Real-time, Real-world Grounding Strategies. SIGDIAL Conference 2016: 288-298 - [c58]