% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").
@InProceedings{chizhikova2022multilingual,
    author="Chizhikova, Anastasia
    and Konovalov, Vasily
    and Burtsev, Mikhail",
    editor="Kryzhanovsky, Boris
    and Dunin-Barkowski, Witali
    and Redko, Vladimir
    and Tiumentsev, Yury",
    title="Multilingual Case-Insensitive Named Entity Recognition",
    booktitle="Advances in Neural Computation, Machine Learning, and Cognitive Research VI",
    year="2023",
    publisher="Springer International Publishing",
    address="Cham",
    pages="448--454",
    isbn="978-3-031-19032-2",
    doi="10.1007/978-3-031-19032-2_46"
}

@inproceedings{karpov2023knowledge,
  title={Knowledge Transfer Between Tasks and Languages in the Multi-task Encoder-agnostic Transformer-based Models},
  author={Karpov, Dmitry and Konovalov, Vasily},
  booktitle={Computational Linguistics and Intellectual Technologies},
  volume={2023},
  year={2023},  
  doi={10.28995/2075-7182-2023-22-200-214},
  url={https://www.dialog-21.ru/media/5902/karpovdpluskonovalovv002.pdf},
  isbn={978-5-7281-2947-9}
}

@InProceedings{tirskikh2023zero,
    author="Tirskikh, Danil
    and Konovalov, Vasily",
    editor="Kryzhanovsky, Boris
    and Dunin-Barkowski, Witali
    and Redko, Vladimir
    and Tiumentsev, Yury
    and Klimov, Valentin",
    title="Zero-Shot NER via Extractive Question Answering",
    booktitle="Advances in Neural Computation, Machine Learning, and Cognitive Research VII",
    year="2023",
    publisher="Springer Nature Switzerland",
    address="Cham",
    pages="22--31",
    abstract="Although the task of named entity recognition (NER) is usually solved as a sequence tagging problem via traditional supervised learning approaches which require the presence of a substantially sized annotated dataset, recent works aiming to utilize pretrained extractive question-answering (QA) models have shown significant few and zero-shot capabilities. This work aims to further investigate their applicability in zero-shot setting i.e. without explicit fine-tuning. We construct a test dataset and conduct a series of experiments to determine the shortcomings inherent in using QA models for the NER task. Our findings demonstrate such problems as weak prompt robustness, high false positive rate, trouble distinguishing between semantically close entity types and more. We suggest that addressing these problems is a crucial first step in improving the extractive QA NER approach. We conduct most of our experiments using DeepPavlov's models within their framework.",
    isbn="978-3-031-44865-2",
    doi="10.1007/978-3-031-44865-2_3"
}


@inproceedings{konovalov2016collecting,
	address = {Los Angeles},
    url = {http://workshop.colips.org/wochat/documents/RP-270.pdf},
	title = {Collecting {Better} {Training} {Data} using {Biased} {Agent} {Policies} in {Negotiation} {Dialogues}},
	abstract = {When naturally occurring data is characterized by a highly skewed class distribution, supervised learning often benefits from reducing this skew. Human-agent dialogue data is commonly highly skewed when using standard agent policies. Hence, we suggest that agent policies need to be reconsidered in the context of training data collection. Specifically, in this work we implemented biased agent policies that are optimized for data collection in the negotiation domain. Empirical evaluations show that our method is successful in collecting a reasonably balanced corpus in the highly skewed Job-Candidate domain. Furthermore, using this balanced corpus to train a negotiation intent classifier yields notable performance improvements relative to naturally distributed data.},
	booktitle = {Proceedings of {WOCHAT}, the {Second} {Workshop} on {Chatbots} and {Conversational} {Agent} {Technologies}},
	publisher = {Zerotype},
	author = {Konovalov, Vasily and Melamud, Oren and Artstein, Ron and Dagan, Ido},
	month = sep,
	year = {2016},
	keywords = {Virtual Humans}
}

@misc{lian2023explainable,
      title={Explainable Multimodal Emotion Reasoning}, 
      author={Zheng Lian and Licai Sun and Mingyu Xu and Haiyang Sun and Ke Xu and Zhuofan Wen and Shun Chen and Bin Liu and Jianhua Tao},
      year={2023},
      eprint={2306.15401},
      archivePrefix={arXiv},
      primaryClass={cs.MM}
}

@misc{zhang2023videollama,
      title={Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding}, 
      author={Hang Zhang and Xin Li and Lidong Bing},
      year={2023},
      eprint={2306.02858},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{touvron2023llama,
      title={Llama 2: Open Foundation and Fine-Tuned Chat Models}, 
      author={Hugo Touvron and Louis Martin and Kevin Stone and Peter Albert and Amjad Almahairi and Yasmine Babaei and Nikolay Bashlykov and Soumya Batra and Prajjwal Bhargava and Shruti Bhosale and Dan Bikel and Lukas Blecher and Cristian Canton Ferrer and Moya Chen and Guillem Cucurull and David Esiobu and Jude Fernandes and Jeremy Fu and Wenyin Fu and Brian Fuller and Cynthia Gao and Vedanuj Goswami and Naman Goyal and Anthony Hartshorn and Saghar Hosseini and Rui Hou and Hakan Inan and Marcin Kardas and Viktor Kerkez and Madian Khabsa and Isabel Kloumann and Artem Korenev and Punit Singh Koura and Marie-Anne Lachaux and Thibaut Lavril and Jenya Lee and Diana Liskovich and Yinghai Lu and Yuning Mao and Xavier Martinet and Todor Mihaylov and Pushkar Mishra and Igor Molybog and Yixin Nie and Andrew Poulton and Jeremy Reizenstein and Rashi Rungta and Kalyan Saladi and Alan Schelten and Ruan Silva and Eric Michael Smith and Ranjan Subramanian and Xiaoqing Ellen Tan and Binh Tang and Ross Taylor and Adina Williams and Jian Xiang Kuan and Puxin Xu and Zheng Yan and Iliyan Zarov and Yuchen Zhang and Angela Fan and Melanie Kambadur and Sharan Narang and Aurelien Rodriguez and Robert Stojnic and Sergey Edunov and Thomas Scialom},
      year={2023},
      eprint={2307.09288},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{bai2023qwen,
      title={Qwen Technical Report}, 
      author={Jinze Bai and Shuai Bai and Yunfei Chu and Zeyu Cui and Kai Dang and Xiaodong Deng and Yang Fan and Wenbin Ge and Yu Han and Fei Huang and Binyuan Hui and Luo Ji and Mei Li and Junyang Lin and Runji Lin and Dayiheng Liu and Gao Liu and Chengqiang Lu and Keming Lu and Jianxin Ma and Rui Men and Xingzhang Ren and Xuancheng Ren and Chuanqi Tan and Sinan Tan and Jianhong Tu and Peng Wang and Shijie Wang and Wei Wang and Shengguang Wu and Benfeng Xu and Jin Xu and An Yang and Hao Yang and Jian Yang and Shusheng Yang and Yang Yao and Bowen Yu and Hongyi Yuan and Zheng Yuan and Jianwei Zhang and Xingxuan Zhang and Yichang Zhang and Zhenru Zhang and Chang Zhou and Jingren Zhou and Xiaohuan Zhou and Tianhang Zhu},
      year={2023},
      eprint={2309.16609},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{jiang2023mistral,
      title={Mistral 7B}, 
      author={Albert Q. Jiang and Alexandre Sablayrolles and Arthur Mensch and Chris Bamford and Devendra Singh Chaplot and Diego de las Casas and Florian Bressand and Gianna Lengyel and Guillaume Lample and Lucile Saulnier and Lélio Renard Lavaud and Marie-Anne Lachaux and Pierre Stock and Teven Le Scao and Thibaut Lavril and Thomas Wang and Timothée Lacroix and William El Sayed},
      year={2023},
      eprint={2310.06825},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{alayrac2022flamingo,
      title={Flamingo: a Visual Language Model for Few-Shot Learning}, 
      author={Jean-Baptiste Alayrac and Jeff Donahue and Pauline Luc and Antoine Miech and Iain Barr and Yana Hasson and Karel Lenc and Arthur Mensch and Katie Millican and Malcolm Reynolds and Roman Ring and Eliza Rutherford and Serkan Cabi and Tengda Han and Zhitao Gong and Sina Samangooei and Marianne Monteiro and Jacob Menick and Sebastian Borgeaud and Andrew Brock and Aida Nematzadeh and Sahand Sharifzadeh and Mikolaj Binkowski and Ricardo Barreira and Oriol Vinyals and Andrew Zisserman and Karen Simonyan},
      year={2022},
      eprint={2204.14198},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}



@misc{zhu2023minigpt4,
      title={MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models}, 
      author={Deyao Zhu and Jun Chen and Xiaoqian Shen and Xiang Li and Mohamed Elhoseiny},
      year={2023},
      eprint={2304.10592},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@misc{ye2023mplugowl,
      title={mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality}, 
      author={Qinghao Ye and Haiyang Xu and Guohai Xu and Jiabo Ye and Ming Yan and Yiyang Zhou and Junyang Wang and Anwen Hu and Pengcheng Shi and Yaya Shi and Chenliang Li and Yuanhong Xu and Hehong Chen and Junfeng Tian and Qian Qi and Ji Zhang and Fei Huang},
      year={2023},
      eprint={2304.14178},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{li2024videochat,
      title={VideoChat: Chat-Centric Video Understanding}, 
      author={KunChang Li and Yinan He and Yi Wang and Yizhuo Li and Wenhai Wang and Ping Luo and Yali Wang and Limin Wang and Yu Qiao},
      year={2024},
      eprint={2305.06355},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@misc{dai2023instructblip,
      title={InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning}, 
      author={Wenliang Dai and Junnan Li and Dongxu Li and Anthony Meng Huat Tiong and Junqi Zhao and Weisheng Wang and Boyang Li and Pascale Fung and Steven Hoi},
      year={2023},
      eprint={2305.06500},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@misc{maaz2023videochatgpt,
      title={Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models}, 
      author={Muhammad Maaz and Hanoona Rasheed and Salman Khan and Fahad Shahbaz Khan},
      year={2023},
      eprint={2306.05424},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@misc{lin2023videollava,
      title={Video-LLaVA: Learning United Visual Representation by Alignment Before Projection}, 
      author={Bin Lin and Yang Ye and Bin Zhu and Jiaxi Cui and Munan Ning and Peng Jin and Li Yuan},
      year={2023},
      eprint={2311.10122},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@misc{li2024mvbench,
      title={MVBench: A Comprehensive Multi-modal Video Understanding Benchmark}, 
      author={Kunchang Li and Yali Wang and Yinan He and Yizhuo Li and Yi Wang and Yi Liu and Zun Wang and Jilan Xu and Guo Chen and Ping Luo and Limin Wang and Yu Qiao},
      year={2024},
      eprint={2311.17005},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}



@article{ASLAM2023110494,
title = {Attention-based multimodal sentiment analysis and emotion recognition using deep neural networks},
journal = {Applied Soft Computing},
volume = {144},
pages = {110494},
year = {2023},
issn = {1568-4946},
doi = {https://doi.org/10.1016/j.asoc.2023.110494},
url = {https://www.sciencedirect.com/science/article/pii/S1568494623005124},
author = {Ajwa Aslam and Allah Bux Sargano and Zulfiqar Habib},
keywords = {Sentiment analysis, Emotion recognition, Multimodal attention, Deep neural networks},
}

@misc{girdhar2023imagebind,
      title={ImageBind: One Embedding Space To Bind Them All}, 
      author={Rohit Girdhar and Alaaeldin El-Nouby and Zhuang Liu and Mannat Singh and Kalyan Vasudev Alwala and Armand Joulin and Ishan Misra},
      year={2023},
      eprint={2305.05665},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@misc{lei2023instructerc,
      title={InstructERC: Reforming Emotion Recognition in Conversation with a Retrieval Multi-task LLMs Framework}, 
      author={Shanglin Lei and Guanting Dong and Xiaoping Wang and Keheng Wang and Sirui Wang},
      year={2023},
      eprint={2309.11911},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@inproceedings{Nguyen_2023,
   title={Conversation Understanding using Relational Temporal Graph Neural Networks with Auxiliary Cross-Modality Interaction},
   url={http://dx.doi.org/10.18653/v1/2023.emnlp-main.937},
   DOI={10.18653/v1/2023.emnlp-main.937},
   booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
   publisher={Association for Computational Linguistics},
   author={Nguyen, Cam Van Thi and Mai, Tuan and The, Son and Kieu, Dang and Le, Duc-Trong},
   year={2023} }

@misc{joshi2022cogmen,
      title={COGMEN: COntextualized GNN based Multimodal Emotion recognitioN}, 
      author={Abhinav Joshi and Ashwani Bhat and Ayush Jain and Atin Vikram Singh and Ashutosh Modi},
      year={2022},
      eprint={2205.02455},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}



@ARTICLE{9926166,
  author={Li, Wei and Li, Yang and Pandelea, Vlad and Ge, Mengshi and Zhu, Luyao and Cambria, Erik},
  journal={IEEE Transactions on Affective Computing}, 
  title={ECPEC: Emotion-Cause Pair Extraction in Conversations}, 
  year={2023},
  volume={14},
  number={3},
  pages={1754-1765},
  keywords={Task analysis;Emotion recognition;Oral communication;Sentiment analysis;Annotations;Feature extraction;Data mining;Conversational sentiment analysis;emotional recurrent unit;contextual encoding;dialogue systems;multi-task learning},
  doi={10.1109/TAFFC.2022.3216551}}

@misc{zheng2023ecqed,
      title={ECQED: Emotion-Cause Quadruple Extraction in Dialogs}, 
      author={Li Zheng and Donghong Ji and Fei Li and Hao Fei and Shengqiong Wu and Jingye Li and Bobo Li and Chong Teng},
      year={2023},
      eprint={2306.03969},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{li2023blip2,
      title={BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models}, 
      author={Junnan Li and Dongxu Li and Silvio Savarese and Steven Hoi},
      year={2023},
      eprint={2301.12597},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@inproceedings{multimodal_survey,
    author = {J. Wu and W. Gan and Z. Chen and S. Wan and P. S. Yu},
    booktitle = {2023 IEEE International Conference on Big Data (BigData)},
    title = {Multimodal Large Language Models: A Survey},
    year = {2023},
    volume = {},
    issn = {},
    pages = {2247-2256},
    doi = {10.1109/BigData59044.2023.10386743},
    publisher = {IEEE Computer Society},
    address = {Los Alamitos, CA, USA},
    month = {dec}
}

@misc{hu2021lora,
      title={LoRA: Low-Rank Adaptation of Large Language Models}, 
      author={Edward J. Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen-Zhu and Yuanzhi Li and Shean Wang and Lu Wang and Weizhu Chen},
      year={2021},
      eprint={2106.09685},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@InProceedings{wang-EtAl:2024:SemEval20244,
  author = {Wang, Fanfan  and  Ma, Heqing  and  Xia, Rui  and  Yu, Jianfei  and  Cambria, Erik},
  title = {SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations},
  booktitle = {Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)},
  month = {June},
  year = {2024},
  address = {Mexico City, Mexico},
  publisher = {Association for Computational Linguistics},
  pages = {2022--2033},
  url = {https://aclanthology.org/2024.semeval2024-1.273}
}

@ARTICLE{wang2021multimodal,
    author={Wang, Fanfan and Ding, Zixiang and Xia, Rui and Li, Zhaoyu and Yu, Jianfei},
    journal={IEEE Transactions on Affective Computing},
    title={Multimodal Emotion-Cause Pair Extraction in Conversations},
    year={2023},
    volume={14},
    number={3},
    pages={1832-1844},
}
@inproceedings{xia2019emotion,
    title={Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in Texts},
    author={Xia, Rui and Ding, Zixiang},
    booktitle={Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
    pages={1003--1012},
    year={2019}
}