% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").

@inproceedings{kumar2024semeval,

    title = "SemEval 2024 -- Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)",

    author = "Kumar, Shivani  and

      Akhtar, Md Shad  and

      Cambria, Erik and

      Chakraborty, Tanmoy",

    booktitle = "Proceedings of the 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics",

    year = "2024",

    publisher = "Association for Computational Linguistics",

    url = "https://arxiv.org/abs/2402.18944",

}

@article{Ekman_1992, title={An argument for basic emotions}, volume={6}, ISSN={1464-0600}, url={http://dx.doi.org/10.1080/02699939208411068}, DOI={10.1080/02699939208411068}, number={3–4}, journal={Cognition and Emotion}, publisher={Informa UK Limited}, author={Ekman, Paul}, year={1992}, month=may, pages={169–200} }

@inproceedings{demszky2020goemotions, author = {Demszky, Dorottya and Movshovitz-Attias, Dana and Ko, Jeongwoo and Cowen, Alan and Nemade, Gaurav and Ravi, Sujith}, booktitle = {58th Annual Meeting of the Association for Computational Linguistics (ACL)}, title = {{GoEmotions: A Dataset of Fine-Grained Emotions}}, year = {2020} }

@article{Devlin,
Author = {Jacob Devlin and Ming-Wei Chang and Kenton Lee and Kristina Toutanova},
Title = {BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding},
Year = {2018},
Eprint = {arXiv:1810.04805},
}

@misc{Brown,
Author = {Tom B. Brown and Benjamin Mann and Nick Ryder and Melanie Subbiah and Jared Kaplan and Prafulla Dhariwal and Arvind Neelakantan and Pranav Shyam and Girish Sastry and Amanda Askell and Sandhini Agarwal and Ariel Herbert-Voss and Gretchen Krueger and Tom Henighan and Rewon Child and Aditya Ramesh and Daniel M. Ziegler and Jeffrey Wu and Clemens Winter and Christopher Hesse and Mark Chen and Eric Sigler and Mateusz Litwin and Scott Gray and Benjamin Chess and Jack Clark and Christopher Berner and Sam McCandlish and Alec Radford and Ilya Sutskever and Dario Amodei},
Title = {Language Models are Few-Shot Learners},
Year = {2020},
Eprint = {arXiv:2005.14165},
}

@misc{Kumar,
Author = {Shivani Kumar and Anubhav Shrimal and Md Shad Akhtar and Tanmoy Chakraborty},
Title = {Discovering Emotion and Reasoning its Flip in Multi-Party Conversations using Masked Memory Network and Transformer},
Year = {2021},
Eprint = {arXiv:2103.12360},
}

@article{sun2020,
      title={How to Fine-Tune BERT for Text Classification?}, 
      author={Chi Sun and Xipeng Qiu and Yige Xu and Xuanjing Huang},
      year={2020},
      eprint={1905.05583},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@article{jiang2023mistral,
  title={Mistral 7{B}},
  author={Jiang, Albert Q and Sablayrolles, Alexandre and Mensch, Arthur and Bamford, Chris and Chaplot, Devendra Singh and Casas, Diego de las and Bressand, Florian and Lengyel, Gianna and Lample, Guillaume and Saulnier, Lucile and others},
  journal={arXiv preprint arXiv:2310.06825},
  Eprint = {arXiv:2310.06825},
  year={2023}
}

@article{DBLP:journals/corr/abs-1911-02116,
  author    = {Alexis Conneau and
               Kartikay Khandelwal and
               Naman Goyal and
               Vishrav Chaudhary and
               Guillaume Wenzek and
               Francisco Guzm{\'{a}}n and
               Edouard Grave and
               Myle Ott and
               Luke Zettlemoyer and
               Veselin Stoyanov},
  title     = {Unsupervised Cross-lingual Representation Learning at Scale},
  journal   = {CoRR},
  volume    = {abs/1911.02116},
  year      = {2019},
  url       = {http://arxiv.org/abs/1911.02116},
  eprinttype = {arXiv},
  eprint    = {1911.02116},
  timestamp = {Mon, 11 Nov 2019 18:38:09 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-02116.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@misc{kim2023solar,
      title="{SOLAR} 10.7{B}: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling", 
      author={Dahyun Kim and Chanjun Park and Sanghoon Kim and Wonsung Lee and Wonho Song and Yunsu Kim and Hyeonwoo Kim and Yungi Kim and Hyeonju Lee and Jihoo Kim and Changbae Ahn and Seonghoon Yang and Sukyung Lee and Hyunbyung Park and Gyoungjin Gim and Mikyoung Cha and Hwalsuk Lee and Sunghun Kim},
      year={2023},
      eprint={2312.15166},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{mixtral2024,
Author = {Albert Q. Jiang and Alexandre Sablayrolles and Antoine Roux and Arthur Mensch and Blanche Savary and Chris Bamford and Devendra Singh Chaplot and Diego de las Casas and Emma Bou Hanna and Florian Bressand and Gianna Lengyel and Guillaume Bour and Guillaume Lample and Lélio Renard Lavaud and Lucile Saulnier and Marie-Anne Lachaux and Pierre Stock and Sandeep Subramanian and Sophia Yang and Szymon Antoniak and Teven Le Scao and Théophile Gervet and Thibaut Lavril and Thomas Wang and Timothée Lacroix and William El Sayed},
Title = {Mixtral of Experts},
Year = {2024},
Eprint = {arXiv:2401.04088},
}

@article{KUMAR2022108112,
title = {Discovering emotion and reasoning its flip in multi-party conversations using masked memory network and transformer},
journal = {Knowledge-Based Systems},
volume = {240},
pages = {108112},
year = {2022},
issn = {0950-7051},
doi = {https://doi.org/10.1016/j.knosys.2021.108112},
url = {https://www.sciencedirect.com/science/article/pii/S0950705121011709},
author = {Shivani Kumar and Anubhav Shrimal and Md Shad Akhtar and Tanmoy Chakraborty},
keywords = {Emotion recognition, Emotion-Flip Reasoning, Multi-party conversations},
abstract = {Efficient discovery of a speaker’s emotional states in a multi-party conversation is significant to design human-like conversational agents. During a conversation, the cognitive state of a speaker often alters due to certain past utterances, which may lead to a flip in their emotional state. Therefore, discovering the reasons (triggers) behind the speaker’s emotion-flip during a conversation is essential to explain the emotion labels of individual utterances. In this paper, along with addressing the task of emotion recognition in conversations (ERC), we introduce a novel task – Emotion-Flip Reasoning (EFR), that aims to identify past utterances which have triggered one’s emotional state to flip at a certain time. We propose a masked memory network to address the former and a Transformer-based network for the latter task. To this end, we consider MELD, a benchmark emotion recognition dataset in multi-party conversations for the task of ERC, and augment it with new ground-truth labels for EFR. An extensive comparison with five state-of-the-art models suggests improved performances of our models for both the tasks. We further present anecdotal evidence and both qualitative and quantitative error analyses to support the superiority of our models compared to the baselines.}
}