| --- |
| license: mit |
|
|
| widget: |
| - text: "What is or could be the cause of target? <sep> target: Thanks. Will I be able to take a retest ? <sep> context: A: Did I do well on my test ?, <utt> B: Do you want to know the honest answer ?, <utt> A: Why wouldn't I want to know ?, <utt> B: You had pretty bad scores ., <utt> A: Exactly what do you mean by bad ?, <utt> B: You failed ., <utt> A: How'd I fail it ?, <utt> B: There are a couple of reasons why you didn't pass ., <utt> A: What did I do wrong ?, <utt> B: To sum it all up , you really just don't know how to drive ., <utt> A: Thanks. Will I be able to take a retest ?, <utt> B: Sure you can , in about two and a half weeks . " |
| example_title: "Cause 1" |
| - text: "What is or could be the cause of 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 2" |
| - text: "What subsequent event happens or could happen following 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 1" |
| - text: "What subsequent event happens or could happen following the target? <sep> target: Sure you can , in about two and a half weeks . <sep> context: A: Did I do well on my test ?, <utt> B: Do you want to know the honest answer ?, <utt> A: Why wouldn't I want to know ?, <utt> B: You had pretty bad scores ., <utt> A: Exactly what do you mean by bad ?, <utt> B: You failed ., <utt> A: How'd I fail it ?, <utt> B: There are a couple of reasons why you didn't pass ., <utt> A: What did I do wrong ?, <utt> B: To sum it all up , you really just don't know how to drive ., <utt> A: Thanks. Will I be able to take a retest ?, <utt> B: Sure you can , in about two and a half weeks . " |
| example_title: "Subsequent Event 2" |
| - 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" |
| - text: "What is or could be the motivation of target? <sep> target: Sure you can , in about two and a half weeks . <sep> context: A: Did I do well on my test ?, <utt> B: Do you want to know the honest answer ?, <utt> A: Why wouldn't I want to know ?, <utt> B: You had pretty bad scores ., <utt> A: Exactly what do you mean by bad ?, <utt> B: You failed ., <utt> A: How'd I fail it ?, <utt> B: There are a couple of reasons why you didn't pass ., <utt> A: What did I do wrong ?, <utt> B: To sum it all up , you really just don't know how to drive ., <utt> A: Thanks. Will I be able to take a retest ?, <utt> B: Sure you can , in about two and a half weeks . " |
| example_title: "Motivation" |
| --- |
| |
| ## DIALogue-level Commonsense Transformer (DIALeCT) |
| The pretrained checkpoint for the paper [Multiview Contextual Commonsense Inference: A New Dataset and Task](https://arxiv.org/abs/2210.02890). |
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| The model is trained based on the [T5-large](https://huggingface.co/t5-large) checkpoint. |
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| ## Datasets |
| The dataset used to pretrain the model can be obtained from the [CICERO repo](https://github.com/declare-lab/CICERO) following instructions. The Contextualized Commonsense Inference in Dialogues v2 (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). |
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|
| **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 target? <sep> |
| target: Thanks. Will I be able to take a retest ? <sep> |
| context: A: Did I do well on my test ?, <utt> |
| B: Do you want to know the honest answer ?, <utt> |
| A: Why wouldn't I want to know ?, <utt> |
| B: You had pretty bad scores ., <utt> |
| A: Exactly what do you mean by bad ?, <utt> |
| B: You failed ., <utt> |
| A: How'd I fail it ?, <utt> |
| B: There are a couple of reasons why you didn't pass ., <utt> |
| A: What did I do wrong ?, <utt> |
| B: To sum it all up , you really just don't know how to drive ., <utt> |
| A: Thanks. Will I be able to take a retest ?, <utt> |
| B: Sure you can , in about two and a half weeks . |
| ``` |
| Predicted cause: |
| ``` |
| The speaker has failed the driving test. |
| ``` |
|
|
| **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. |
| ``` |
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|
| ## Inference: |
| The input text should be formatted as follows: |
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| ``` |
| Question <sep> target: target_utt <sep> context: A: utterance 1 <utt> B: utterance 2 <utt> A: utterance 3 <utt> B: utterance 4 |
| ``` |
| Question: The question against which we want to make the inference. |
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| A, B are speaker identifiers |
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| The ```target_utt``` should be anyone between ```utterance 1, utterance 2, utterance 3, or utterance 4```. Do not use the speaker identifier in the ```target_utt``` |
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| Some samples are provided in the Hosted inference API box examples. |
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| ## 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} |
| } |
| ``` |
