3rd Conversational AI:
“Today's Practice and Tomorrow's Potential”

NeurIPS 2019 - Workshop

 
 

Description

In less than a decade, conversational systems have become commonplace. Every day, millions of people use natural-language interfaces such as Siri, the Google Assistant, Cortana, Alexa and others via in-home devices, phones, or messaging channels such as Messenger, Slack, Skype, among others.  At the same time, interest among the research community in conversational systems has blossomed: for supervised and reinforcement learning, conversational systems often serve as both a benchmark task and an inspiration for new ML methods at conferences which don't focus on speech and language per se, such as NeurIPS, ICML, IJCAI, and others. Such movement has not been unnoticed by major publications. This year in collaboration with AAAI community, the AI magazine will have a special issue on conversational AI. Moreover, research community challenge tasks are proliferating, including the seventh Dialog Systems Technology Challenge (DSTC7), the Amazon Alexa prize, and the Conversational Intelligence Challenge live competitions at NeurIPS (2017, 2018).


Following two successful NeurIPS workshops:
        2017: 9 invited talks, 26 submissions, 3 oral papers, 13 accepted papers, 37 reviewers

        2018: 4 invited talks, 42 submission, 6 oral papers, 23 accepted papers, 58 reviewers,

we are excited to continue promoting cross-pollination of ideas between academic research centers and industry. The goal of this workshop is to bring together researchers and practitioners in this area, to clarify impactful research problems, understand well-founded methods, share findings from large-scale real-world deployments, and generate new ideas for future lines of research.


This workshop will include invited talks from academia and industry, contributed work, and open discussion. In these talks, senior technical leaders from many of the most popular conversational services will give insights into real usage and challenges at scale. We will end the day with an open discussion, including a panel consisting of academic and industrial researchers.



Invited Speakers


  1. Y-Lan Boureau (Facebook)

  2. Ryuchiro Higashinaka (NTT)

  3. Alan Ritter (Ohio State University)

  4. Gabriel Skantze (KTH, Furhat Robotics)

  5. David Traum (USC)

  6. Zhou Yu (UC Davis): *Unable to deliver her talk due to visa issues


Chairs:







Organizers:










Call for Papers

We invite you to submit your novel contributions (submission page) in the area of conversational AI in NeurIPS style with maximum of 8 pages excluding the references. You can add supplementary material in addition to 8 pages, but reviewers are not required to review the extra material (e.g. your paper should stand on its own without the supplementary material). Selected papers will be presented through invited talks or posters. Maximum allowed size of posters is 36 x 48 inch (91 x 122 cm). Posters should be on light weight paper and not laminated. Submitting papers that are under review by other venues are ok. However, please avoid submitting already peer-reviewed and published work. Notice that our workshop is not archival. However, accepted submission will be hosted on this website similar to last year’s workshop. Given authors concern around posting their submissions to arXiv the organizing committed decided to lift the anonymity requirement for our workshop. This means the anonymity will be optional and decided by the authors. Hence, you can post your submissions to arXiv. For further questions, feel free to reach out to co-chairs through email (alborz dot geramifard at gmail dot com; jdw at alumni dot princeton dot edu).


Two phase submission process

This year, we will have two submission phases due to limitation for allocating tickets to authors. We advise all workshop attendees to enter their names for the NeurIPS lottery here.


Phase 1 (Early Submission): Please follow the early submission, only if you did not win a ticket in the NeurIPS lottery. We will notify accepted authors by October 1st and provide tickets to the author presenting the paper.


Submission:    21st September 2019 11:59 PM EST (link)

Notification:    1st October 2019


Phase 2 (Regular Submission): If you already acquired the NeurIPS ticket, please follow the regular submission process below.

Submission:    1st October 2019 11:59 PM EST (link)

Notification:    1st November 2019


Shared dates for both phases:

Camera Ready:        14th November 2019

Registration Start:  6th September 2019

Workshop:                14th December 2019 (Saturday - Second day of workshops)


Location
Vancouver Convention Center, CANADA 


Schedule


8:45-8:55         Opening

8:55-9:25         Invited Talk - Alan Ritter

9:25-9:40         Contributed talk 1: Attention over Parameters for Dialogue Systems

9:40-9:55         Poster - Lightning round

9:55-10:40      Coffee Break / Poster Session

10:40-11:10    Invited Talk - Ryuchiro Higashinaka

11:10-11:25    Contributed talk 2: Persona-aware Dialogue Generation with Enriched Profile
11:25-11:40    Contributed talk 3: HSCJN: A Holistic Semantic Constraint Joint Network for Diverse Response Generation
11:40-11:55    Contributed talk 4: Hierarchical Reinforcement Learning for Open-Domain Dialog

11:55-1:45      Lunch Break

1:45-2:15        Invited Talk - David Traum

2:15-2:45        Invited Talk - Y-Lan Boureau

2:45-3:00        Contributed talk 5: Domain Transfer in Dialogue Systems without Turn-Level Supervision

3:00-3:15        Contributed talk 6: Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings

3:15-3:30        Contributed talk 7: Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues

3:30-4:15        Coffee Break / Poster Session

4:15-4:45        Invited Talk - Gabriel Skantze
4:45-5:00        Contributed talk 8: Recurrent Chunking Mechanisms for Conversational Machine Reading Comprehension

5:00-5:50        Panel / Open Discussion - All Organizers (submit questions here)

5:50-6:00        Closing Remarks


Questions for Panel























Accepted Papers - Talk


  1. Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues [PDF]
    Jang, Youngsoo; Lee, Jongmin; Kim, Kee-Eung

  2. Domain Transfer in Dialogue Systems without Turn-Level Supervision [PDF]
    Bingel, Joachim; Petrén Bach Hansen, Victor; Gonzalez, Ana V; Budzianowski, Paweł; Augenstein, Isabelle; Søgaard, Anders

  3. Persona-aware Dialogue Generation with Enriched Profile [PDF]
    Zheng, Yinhe; Chen, Guanyi; Huang, Minlie; Liu, Song; Zhu, Xuan

  4. Attention over Parameters for Dialogue Systems [PDF]
    Madotto, Andrea; Lin, Zhaojiang; Wu, Chien-Sheng; Shin, Jamin; Fung, Pascale

  5. Hierarchical Reinforcement Learning for Open-Domain Dialog [PDF]
    Saleh, Abdelrhman; Jaques, Natasha; Ghandeharioun, Asma; Shen, Judy Hanwen; Picard, Rosalind

  6. Recurrent Chunking Mechanisms for Conversational Machine Reading Comprehension [PDF]
    Gong, Hongyu; Shen, Yelong; Yu, Dian; Chen, Jianshu; Yu, Dong

  7. HSCJN: A Holistic Semantic Constraint Joint Network for Diverse Response Generation [PDF]
    Wang, Yiru; Si, Pengda; Lei, Zeyang; Xun, Guangxu; Yang, Yujiu

  8. Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings [PDF]
    Mendez, Jorge A; Geramifard, Alborz; Ghavamzadeh, Mohammad; Liu, Bing


Accepted Papers - Poster


  1. 1.Multi-Turn Beam Search for Neural Dialogue Modeling [PDF]
    Kulikov, Ilia*; Lee, Jason; Cho, Kyunghyun

  2. 2.Just Ask:An Interactive Learning Framework for Vision and Language Navigation [PDF]
    Chi, Ta-Chung*; Shen, Minmin; Eric, Mihail; Kim, Seokhwan; Hakkani-tur, Dilek

  3. 3.Improving Robustness of Task Oriented Dialog Systems [PDF]
    Einolghozati, Arash*; Gupta, Sonal; Mohit, Mrinal; Shah, Rushin

  4. 4.Hierarchical Tensor Fusion Network for Deception Handling Negotiation Dialog Model [PDF]
    Nguyen, The  Tung*; Yoshino, Koichiro; Sakti, Sakriani; Nakaura, Satoshi

  5. 5.Conversational QA for FAQs [PDF]
    Campos, Jon Ander*; Agirre, Eneko; Soroa, Aitor; Otegi, Arantxa; Deriu, Jan; Cieliebak, Mark

  6. 6.Dialogue Model and Response Generation for Emotion Improvement Elicitation [PDF]
    Lubis, Nurul*; Sakti, Sakriani; Yoshino, Koichiro; Nakaura, Satoshi

  7. 7.ACUTE-EVAL: Improved dialogue evaluation with optimized questions and multi-turn comparisons [PDF]
    Li, Margaret*; Roller, Stephen; Weston, Jason

  8. 8.MA-DST: Multi-Attention-Based Scalable Dialog State Tracking [PDF]
    Kumar, Adarsh*; Ku, Peter; Goyal, Anuj Kumar; Metallinou, Angeliki; Hakkani-tur, Dilek

  9. 9.Aging Memories Generate More Fluent Dialogue Responses with Memory Augmented Neural Networks [PDF]
    Florez, Omar U*; Muller, Erik

  10. 10.Learning to Control Latent Representations \or Few-Shot Learning of Named Entities [PDF]
    Florez, Omar U*; Muller, Erik

  11. 11.Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning [PDF]
    Neelakantan, Arvind*; Narang, Sharan; Yavuz, Semih

  12. 12.Retrieval-based Goal-Oriented Dialogue Generation [PDF]
    Gonzalez, Ana V*; Augenstein, Isabelle; Søgaard, Anders

  13. 13.Investigation of Error Simulation Techniques for Learning Dialog Policies for Conversational Error Recovery [PDF]
    Fazel-Zarandi, Maryam*; Wang, Longshaokan; Tiwari, Aditya; Matsoukas, Spyros

  14. 14.Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog [PDF]
    Jaques, Natasha*; Ghandeharioun, Asma; Shen, Judy Hanwen; Ferguson, Craig; Lapedriza Garcia, Agata; Jones, Noah; Gu, Shixiang; Picard, Rosalind

  15. 15.Incorporating rules into end-to-end dialog systems [PDF]
    Razumovskaia, Evgeniia*; Eskenazi, Maxine

  16. 16.Learning Conversational Web Interfaces [PDF]
    Gur, Izzeddin*; Yan, Xifeng

  17. 17.Towards Personalized Dialog Policies for Conversational Skill Discovery [PDF]
    Fazel-Zarandi, Maryam*; Biswas, Sampat; Summers, Ryan; Elmalt, Ahmed; McCraw, Andy; McPhilips, Michael; Peach, John

  18. 18.The Eighth Dialog System Technology Challenge [PDF]
    Kim, Seokhwan*; Galley, Michel; Gunasekara, Chulaka; Lee, Sungjin; Atkinson, Adam; Peng, Baolin; Schulz, Hannes;  Gao, Jianfeng; Li, Jinchao; Adada, Mahmoud; Huang, Minlie; Lastras, Luis A.; Kummerfeld, Jonathan K; Lasecki, Walter; Hori, Chiori; Cherian, Anoop; Marks, Tim K; Rastogi, Abhinav; Zang, Xiaoxue; Sunkara, Srinivas; Gupta, Raghav

  19. 19.Multi-domain Conversation Quality Evaluaiton via User Satisfaction Estimation [PDF]
    Bodigutla, Praveen Kumar*; Matsoukas, Spyros; Polymenakos, Lazaros

  20. 20.Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering [PDF]
    Zhou, Li*; Small, Kevin

  21. 21.TAM: Using trainable-action-mask to improve sample-efficiency in reinforcement learning for dialogue systems [PDF]
    Wu, Yen-Chen*

  22. 22.Domain-Specific Question Answering at Scale for Conversational Systems [PDF]
    Semnani, Sina; Pandey, Madhulima ; Pandey, Manish*


Program Committee


  1. Masahiro Araki (Kyoto Institute of Technology)

  2. Ron Artstein (USC Institute for Creative Technologies)

  3. Rafael Banchs (Intapp, Inc)

  4. Parminder Bhatia (Amazon)

  5. Nate Blaylock (Nuance Communications)

  6. Praveen Kumar Bodigutla (Amazon)

  7. Yun-Nung Chen (National Taiwan University)

  8. Paul Crook (Facebook)

  9. Heriberto Cuayahuitl (University of Lincoln)

  10. Ludovic Denoyer (Facebook)

  11. Nina Dethlefs (University of Hull)

  12. Maryam Fazel-Zarandi (Amazon)

  13. Michel Galley (Microsoft)

  14. Kallirroi Georgila (University of Southern California)

  15. Helen Hastie (Heriot-Watt University)

  16. Larry Heck (Samsung Research America)

  17. Matthew Henderson (Google)

  18. Ryuichiro Higashinaka (NTT)

  19. Ravi Jain (Amazon)

  20. Anders Johannsen (Apple)

  21. Filip Jurcicek (Apple)

  22. Chandra Khatri (Uber AI)

  23. Douwe Kiela (Facebook AI Research)

  24. Kazunori Komatani (Osaka University)

  25. Anjishnu Kumar (Amazon)

  26. Sungjin Lee (Microsoft Research)

  27. Oliver Lemon (Heriot-Watt University)

  28. Lihong Li (Google)

  29. Lin Li (Apple)

  30. Lambert Mathias (Amazon)

  31. Angeliki Metallinou (Amazon)

  32. Diarmuid Ó Séaghdha (Apple)

  33. Alexandros Papangelis (Toshiba Research Europe Limited)

  34. Stephen Pulman (Apple)

  35. Giuseppe Riccardi (University of Trento)

  36. Sanjeev Satheesh (Tesla)

  37. Ethan Selfridge (Interactions Corporation)

  38. Amina Shabbeer (Amazon)

  39. Kevin Small (Amazon)

  40. Eddy Su (PolyAI)

  41. Sandeep Subramanian (MILA)

  42. Gyuri Szarvas (Amazon)

  43. Blaise Thomson (Apple)

  44. Gokhan Tur (Google)

  45. Stefan Ultes (Daimler)

  46. Anu Venkatesh (Amazon)

  47. Shawn Wen (PolyAI)

  48. Jason Weston (Facebook AI Research)

  49. Hong Yu (Apple)

  50. Kai Yu (SJTU)

  51. Imed Zitouni (Microsoft)

  52. Baiyang Liu (Facebook AI)

  53. Seokhwan Kim (Amazon Alexa AI)

  54. Mihail Eric (Amazon Alexa AI)

  55. Semih Yavuz (UCSB)

  56. Pawel Budzianowski (Cambridge U.)

  57. Maxine Eskenazi (CMU)

  58. Tiancheng (Tony) Zhao (CMU)

  59. Marilyn Walker (UCSC)

  60. Ashutosh Modi (Disney Research)

  61. Luis Fernando D'Haro (Technical University of Madrid)

  62. Nurul Lubis (Heinrich Heine University Düsseldorf)

  63. Marcus Heck (Heinrich Heine University Düsseldorf)

  64. Dhivya Piraviperumal (Apple)

  65. Chiori Hori (MERL)

  66. Jinho Choi (Emory University)

  67. Scott Sanner (UToronto)

  68. Tyler Lu (Google)

  69. Deepak Ramachandran (Google)