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:

bibtex

@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}
}

shensq0814/DIALECT

Contextualized Commonsense Inference in Dialogues v2

Datasets

Examples

BibTeX entry and citation info

shensq0814/
DIALECT