 The proposed model was able to generate decent results and cleared showed potential to perform state of the art if trained on a larger dataset  .
<meaning-changed>  The proposed model was able to generate decent results and cleared showed potential to perform state of the art if trained on a larger dataset  .
 The proposed model was able to generate decent results and cleared showed potential to perform state of the art if trained on a larger dataset phrases responsible for invoking sarcasm. Bi-ISCA generates state-of-the-art results on two widely used benchmark datasets for the sarcasm detection task (Reddit and Twitter). To the best of our knowledge, none of the existing state-of-the-art models use an inter-sentence contextual attention mechanism to detect sarcasm in the user-generated short text using only conversational context .