metadata
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
datasets:
- declare-lab/cicero
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.
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}
}