Noetic End-to-End Response Selection Challenge

Update - A tensorflow based baseline for subtask 1 of the track is available here.

This challenge is part of dialog state tracking challenge (DSTC 7) series. It provides a partial conversation, and requires participants to select the correct next utterances from a set of candidates. Unlike previous similar challenges, this task tries to push towards real world problems by introducing:

  • A large number of candidates

  • Cases where no candidate is correct

  • External data

This challenge is offered with two goal oriented dialog datasets, used in 5 subtasks. A participant may participate in one, several, or all the subtasks. A full description of the track is available here.

If you use this data or code in your work, please cite the task description paper:

  title     = {DSTC7 Task 1: Noetic End-to-End Response Selection},
  author    = {Chulaka Gunasekara, Jonathan K. Kummerfeld, Lazaros Polymenakos, and Walter S. Lasecki},
  year      = {2019},
  booktitle = {7th Edition of the Dialog System Technology Challenges at AAAI 2019},
  url       = {},
  month     = {January},

If you use the Ubuntu data, please also cite the paper in which we describe its creation:

  author    = {Jonathan K. Kummerfeld, Sai R. Gouravajhala, Joseph Peper, Vignesh Athreya, Chulaka Gunasekara, Jatin Ganhotra, Siva Sankalp Patel, Lazaros Polymenakos, and Walter S. Lasecki},
  title     = {Analyzing Assumptions in Conversation Disentanglement Research Through the Lens of a New Dataset and Model},
  journal   = {ArXiv e-prints},
  archivePrefix = {arXiv},
  eprint    = {1810.11118},
  primaryClass = {cs.CL},
  year      = {2018},
  month     = {October},
  url       = {},



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