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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 \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 "
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 \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 "
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 \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 "
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](https://arxiv.org/abs/2210.02890).
The model is trained based on the [T5-large](https://huggingface.co/t5-large) checkpoint.
## Datasets
The dataset used to pretrain the model can be obtained from the [CICERO repo](https://github.com/declare-lab/CICERO) 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}
}
```
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