{
  "name": "LIF3WayAP",
  "languages": "English",
  "description": "This is a neural network that applies attention mechanism and pooling to 3 sets of inputs: context, candidate question, previous questions and answers. It then classifies whether a candidate question is a follow-up question.",
  "paper": {
    "text": "<NAME>., <NAME>., and <NAME> (2020). Learning to Identify Follow-Up Questions in Conversational Question Answering. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, July 2020 (pp. 959-968).",
    "url": "https://aclanthology.org/2020.acl-main.90/"
  },
  "trainingDataset": {
    "text": "Custom dataset derived from QuAC. Can be downloaded from the author's github repository.",
    "url": "https://github.com/nusnlp/LIF"
  },
  "evaluationDataset": {
    "text": "Custom dataset derived from QuAC. Can be downloaded from the author's github repository.",
    "url": "https://github.com/nusnlp/LIF"
  },
  "evaluationScores": "0.81 F1 on development set. 0.82 F1 reported by authors in paper on development set.",
  "trainingConfig": {
    "text": "Not available."
  },
  "trainingTime": "~13 hours for 25 epochs on a single V100 GPU.",
  "modelWeights": {
    "text": "https://storage.googleapis.com/sgnlp/models/lif_3way_ap/pytorch_model.bin",
    "url": "https://storage.googleapis.com/sgnlp/models/lif_3way_ap/pytorch_model.bin"
  },
  "modelConfig": {
    "text": "https://storage.googleapis.com/sgnlp/models/lif_3way_ap/config.json",
    "url": "https://storage.googleapis.com/sgnlp/models/lif_3way_ap/config.json"
  },
  "modelInput": "Context, historical questions and answers pairs, and candidate question.",
  "modelOutput": "Probability score of whether candidate question is a valid follow-up question.",
  "modelSize": "~130MB",
  "inferenceInfo": "Not available.",
  "usageScenarios": "Chatbots",
  "originalCode": {
    "text": "https://github.com/nusnlp/LIF",
    "url": "https://github.com/nusnlp/LIF"
  },
  "license": {
    "text": "For non-commercial use: GNU GPLv3. For commercial use, please contact us.",
    "url": "https://choosealicense.com/licenses/gpl-3.0"
  },
  "contact": "<EMAIL>"
}