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license: mit
widget:
  - text: >-
      What is or could be the subsequent event of the target? <sep> target: Oh .
      I just can't forget it .<sep> context: A: David , why didn't you clean the
      room ?, <utt> B: I'm not in the mood ., <utt> A: Why are you feeling
      depressed ?, <utt> B: I was told my girlfriend was speaking ill of me.
      That ’ s a real let-down ., <utt> A: I don t think she will do such a
      thing ., <utt> B: But she did and made me disappointed ., <utt> A: Oh ,
      cheer up . A girlfriend is not everything ., <utt> B: But she means a lot
      to me ., <utt> A: Then forgive her mistake ., <utt> B: Oh . I just can't
      forget it 
    example_title: Subsequent Event
  - text: >-
      What is or could be the cause of the target? <sep>target: But she did and
      made me disappointed . <sep> context: A: David , why didn't you clean the
      room ?, <utt>B: I'm not in the mood ., <utt> A: Why are you feeling
      depressed ?, <utt> B: I was told my girlfriend was speaking ill of me.
      That ’ s a real let-down ., <utt>A: I don t think she will do such a thing
      ., <utt> B: But she did and made me disappointed ., <utt> A: Oh , cheer up
      . A girlfriend is not everything ., <utt>B: But she means a lot to me .,
      <utt> A: Then forgive her mistake ., <utt> B: Oh . I just can't forget it 
    example_title: Cause
  - text: >-
      What is the possible emotional reaction of the listener in response to
      target? <sep> target: Oh . I just can't forget it .<sep> context: A: David
      , why didn't you clean the room ?, <utt> B: I'm not in the mood ., <utt>
      A: Why are you feeling depressed ?, <utt>B: I was told my girlfriend was
      speaking ill of me. That ’ s a real let-down ., <utt> A: I don t think she
      will do such a thing ., <utt> B: But she did and made me disappointed .,
      <utt> A: Oh , cheer up . A girlfriend is not everything ., <utt> B: But
      she means a lot to me ., <utt> A: Then forgive her mistake ., <utt> B: Oh
      . I just can't forget it 
    example_title: Emotional Reaction

Contextualized Commonsense Inference in Dialogues v2

The pretrained checkpoint for the paper Multiview Contextual Commonsense Inference: A New Dataset and Task.

The model is trained based on the T5-large checkpoint.

model image

Datasets

The dataset used to pretrain the model can be obtained from the CICERO repo following instructions. The CICEROv2 consists of annotated commonsense inferences including cause and emotional reaction, etc. The dialogues are from multiple datasets.

Dataset #Dialogues #Instances
DailyDialog 1118 3973
MuTual 1011 3384
Dream 250 994

Examples

Some examples of generated results from the pretrained model (the zero-shot setting).

Subsequent Event

What is or could be the subsequent event of the target? <sep> 
target: Oh . I just can't forget it .<sep> 
context: A: David , why didn't you clean the room ?, <utt> 
B: I'm not in the mood ., <utt> 
A: Why are you feeling depressed ?, <utt> 
B: I was told my girlfriend was speaking ill of me. That \u2019 s a real let-down ., <utt> 
A: I don t think she will do such a thing ., <utt> 
B: But she did and made me disappointed ., <utt> 
A: Oh , cheer up . A girlfriend is not everything ., <utt> 
B: But she means a lot to me ., <utt> 
A: Then forgive her mistake ., <utt> 
B: Oh . I just can't forget it 

Predicted subsequent event:

David's girlfriend apologized to david for her mistake.

Cause

What is or could be the cause of the target? <sep>
target: But she did and made me disappointed . <sep> 
context: A: David , why didn't you clean the room ?, <utt>
B: I'm not in the mood ., <utt> 
A: Why are you feeling depressed ?, <utt> 
B: I was told my girlfriend was speaking ill of me. That \u2019 s a real let-down ., <utt>
A: I don t think she will do such a thing ., <utt> 
B: But she did and made me disappointed ., <utt> 
A: Oh , cheer up . A girlfriend is not everything ., <utt>
B: But she means a lot to me ., <utt> 
A: Then forgive her mistake ., <utt> 
B: Oh . I just can't forget it 

Predicted cause:

David's girlfriend was not nice to him.

Emotional Reaction

What is the possible emotional reaction of the listener in response to target? <sep> 
target: Oh . I just can't forget it .<sep> 
context: A: David , why didn't you clean the room ?, <utt> 
B: I'm not in the mood ., <utt> 
A: Why are you feeling depressed ?, <utt>
B: I was told my girlfriend was speaking ill of me. That \u2019 s a real let-down ., <utt> 
A: I don t think she will do such a thing ., <utt> 
B: But she did and made me disappointed ., <utt> 
A: Oh , cheer up . A girlfriend is not everything ., <utt> 
B: But she means a lot to me ., <utt> 
A: Then forgive her mistake ., <utt> 
B: Oh . I just can't forget it 

Predicted emotional reaction:

The listener is hopeful that david will forgive his girlfriend for her mistake.

BibTeX entry and citation info

If you use the model, you can cite:

@article{Shen2022MultiviewCC,
  title={Multiview Contextual Commonsense Inference: A New Dataset and Task},
  author={Siqi Shen and Deepanway Ghosal and Navonil Majumder and Henry Lim and Rada Mihalcea and Soujanya Poria},
  journal={ArXiv},
  year={2022},
  volume={abs/2210.02890}
}