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Throughout rapid development of multimodal large language models, a crucial ingredient is a fair and accurate evaluation of their multimodal comprehension abilities.
An analysis of visual question answering algorithms. In Proceedings of the IEEE international conference on computer vision . 1965–1973
Kushal Kafle and Christopher Kanan. 2017 · 1973
Earlier work this paper cites.
Brown corpus manual
W Nelson Francis and Henry Kucera. 1979 · 1979
Earlier work this paper cites.
Introduction to WordNet: An On-line Lexical Database
George A. Miller, Richard Beckwith, Christiane Fellbaum, Derek Gross, and Katherine J. Miller. 1990 · 1990
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics . 311–318
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries. In Text summarization branches out . 74–81
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization . 65–72
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
Earlier work this paper cites.
Computing Krippendorff’s alpha-reliability
Klaus Krippendorff. 2011 · 2011
Earlier work this paper cites.
SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity.* SEM 2012: The First Joint Conference on Lexical and Computational Semantics—. In Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012), Montréal, QC, Canada . 7–8
Eneko Agirre, Daniel Cer, Mona Diab, and Aitor Gonzalez-Agirre. 2012 · 2012
Earlier work this paper cites.
* SEM 2013 shared task: Semantic textual similarity. In Second joint conference on lexical and computational semantics (* SEM), volume 1: proceedings of the Main conference and the shared task: semantic textual similarity . 32–43
Eneko Agirre, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, and Weiwei Guo. 2013 · 2013
Earlier work this paper cites.
Semeval-2014 task 10: Multilingual semantic textual similarity. In Proceedings of the 8th international workshop on semantic evaluation (SemEval 2014) . 81–91
Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Rada Mihalcea, German Rigau, and Janyce Wiebe. 2014 · 2014
Earlier work this paper cites.
A multi-world approach to question answering about real-world scenes based on uncertain input
Mateusz Malinowski and Mario Fritz. 2014 · 2014
Earlier work this paper cites.
A SICK cure for the evaluation of compositional distributional semantic models. In 9th Language Resources and Evaluation Conference . Reykjavik
Marco Marelli, Stefano Menini, Marco Baroni, Luisa Bentivogli, Raffaella Bernardi, and Roberto Zamparelli. 2014 · 2014
Earlier work this paper cites.
Semeval-2015 task 2: Semantic textual similarity, english, spanish and pilot on interpretability. In Proceedings of the 9th international workshop on semantic evaluation (SemEval 2015) . 252–263
Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Inigo Lopez-Gazpio, Montse Maritxalar, Rada Mihalcea, et al · 2015
Earlier work this paper cites.
Vqa: Visual question answering. In Proceedings of the IEEE international conference on computer vision . 2425–2433
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
Earlier work this paper cites.
Exploring models and data for image question answering
Mengye Ren, Ryan Kiros, and Richard Zemel. 2015 · 2015
Earlier work this paper cites.
Explicit knowledge-based reasoning for visual question answering
Peng Wang, Qi Wu, Chunhua Shen, Anton van den Hengel, and Anthony Dick. 2015 · 2015
Earlier work this paper cites.
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 2015
Earlier work this paper cites.
Semeval-2016 task 1: Semantic textual similarity, monolingual and cross-lingual evaluation. In SemEval-2016. 10th International Workshop on Semantic Evaluation; 2016 Jun 16-17; San Diego, CA. Stroudsburg (PA): ACL; 2016. p. 497-511. ACL (Association for Computational Linguistics)
Eneko Agirre, Carmen Banea, Daniel Cer, Mona Diab, Aitor Gonzalez Agirre, Rada Mihalcea, German Rigau Claramunt, and Janyce Wiebe. 2016 · 2016
Earlier work this paper cites.
Image question answering using convolutional neural network with dynamic parameter prediction. In Proceedings of the IEEE conference on computer vision and pattern recognition . 30–38
Hyeonwoo Noh, Paul Hongsuck Seo, and Bohyung Han. 2016 · 2016
Earlier work this paper cites.
Stacked attention networks for image question answering. In Proceedings of the IEEE conference on computer vision and pattern recognition . 21–29
Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, and Alex Smola. 2016 · 2016
Earlier work this paper cites.
Abcnn: Attention-based convolutional neural network for modeling sentence pairs
Wenpeng Yin, Hinrich Schütze, Bing Xiang, and Bowen Zhou. 2016 · 2016
Earlier work this paper cites.
Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Inigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
Earlier work this paper cites.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Making the v in vqa matter: Elevating the role of image understanding in visual question answering. In Proceedings of the IEEE conference on computer vision and pattern recognition . 6904–6913
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017 · 2017
Cited alongside, same era.
Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, et al · 2017
Cited alongside, same era.
Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter. 2017 · 2017
Cited alongside, same era.
Fvqa: Fact-based visual question answering
Peng Wang, Qi Wu, Chunhua Shen, Anthony Dick, and Anton Van Den Hengel. 2017 · 2017
Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
Later among the works it cites.
A-okvqa: A benchmark for visual question answering using world knowledge. In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part VIII . Springer, 146–162
Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, Kenneth Marino, and Roozbeh Mottaghi. 2022 · 2022
Later among the works it cites.
Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework. In International Conference on Machine Learning . PMLR, 23318–23340
Peng Wang, An Yang, Rui Men, Junyang Lin, Shuai Bai, Zhikang Li, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang. 2022 · 2022
Later among the works it cites.
Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, Binyuan Hui, Luo Ji, Mei Li, Junyang Lin, Runji Lin, Dayiheng Liu, Gao Liu, Chengqiang Lu, Keming Lu, Jianxin Ma, Rui Men, Xingzhang Ren, Xuancheng Ren, Chuanqi Tan, Sinan Tan, Jianhong Tu, Peng Wang, Shijie Wang, Wei Wang, Shengguang Wu, Benfeng Xu, Jin Xu, An Yang, Hao Yang, Jian Yang, Shusheng Yang, Yang Yao, Bowen Yu, Hongyi Yuan, Zheng Yuan, Jianwei Zhang, Xingxuan Zhang, Yichang Zhang, Zhenru Zhang, Chang Zhou, Jingren Zhou, Xiaohuan Zhou, and Tianhang Zhu. 2023a · 2023
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Cited alongside, same era.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel R Bowman. 2017 · 2017
Cited alongside, same era.
Image captioning and visual question answering based on attributes and external knowledge
Qi Wu, Chunhua Shen, Peng Wang, Anthony Dick, and Anton Van Den Hengel. 2017 · 2017
Cited alongside, same era.
Senteval: An evaluation toolkit for universal sentence representations
Alexis Conneau and Douwe Kiela. 2018 · 2018
Cited alongside, same era.
Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
Cited alongside, same era.
Vizwiz grand challenge: Answering visual questions from blind people. In Proceedings of the IEEE conference on computer vision and pattern recognition . 3608–3617
Danna Gurari, Qing Li, Abigale J Stangl, Anhong Guo, Chi Lin, Kristen Grauman, Jiebo Luo, and Jeffrey P Bigham. 2018 · 2018
Cited alongside, same era.
Multiway attention networks for modeling sentence pairs.. In IJCAI . 4411–4417
Chuanqi Tan, Furu Wei, Wenhui Wang, Weifeng Lv, and Ming Zhou. 2018 · 2018
Cited alongside, same era.
Gqa: A new dataset for real-world visual reasoning and compositional question answering. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 6700–6709
Drew A Hudson and Christopher D Manning. 2019 · 2019
Cited alongside, same era.
Later among the works it cites.
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou. 2023b · 2023
Later among the works it cites.
Baichuan 2: Open Large-scale Language Models
Baichuan. 2023 · 2023
Later among the works it cites.
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
Fu Chaoyou, Chen Peixian, Shen Yunhang, Qin Yulei, Zhang Mengdan, Lin Xu, Yang Jinrui, Zheng Xiawu, Li Ke, Sun Xing, Wu Yunsheng, and Ji Rongrong. 2023 · 2023
Later among the works it cites.
Jianlv Chen, Shitao Xiao, Peitian Zhang, Kun Luo, Defu Lian, and Zheng Liu. 2023 · 2023
Later among the works it cites.
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven Hoi. 2023 · 2023
Later among the works it cites.
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
Later among the works it cites.
Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023 · 2023
Later among the works it cites.
AnglE-optimized Text Embeddings
Xianming Li and Jing Li. 2023 · 2023
Later among the works it cites.
Improved baselines with visual instruction tuning
Haotian Liu, Chunyuan Li, Yuheng Li, and Yong Jae Lee. 2023 · 2023
Later among the works it cites.
Tiny lvlm-ehub: Early multimodal experiments with bard
Wenqi Shao, Yutao Hu, Peng Gao, Meng Lei, Kaipeng Zhang, Fanqing Meng, Peng Xu, Siyuan Huang, Hongsheng Li, Yu Qiao, et al · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
Later among the works it cites.
mplug-owl: Modularization empowers large language models with multimodality
Qinghao Ye, Haiyang Xu, Guohai Xu, Jiabo Ye, Ming Yan, Yiyang Zhou, Junyang Wang, Anwen Hu, Pengcheng Shi, Yaya Shi, et al · 2023
Later among the works it cites.
Mm-vet: Evaluating large multimodal models for integrated capabilities
Weihao Yu, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu, Xinchao Wang, and Lijuan Wang. 2023 · 2023
Later among the works it cites.
Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2024a · 2024
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Shuo Liu, Kaining Ying, Hao Zhang, Yue Yang, Yuqi Lin, Tianle Zhang, Chuanhao Li, Yu Qiao, Ping Luo, Wenqi Shao, et al · 2024
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Generative Representational Instruction Tuning
Muennighoff Niklas, Su Hongjin, Wang Liang, Yang Nan, Wei Furu, Yu Tao, Singh Amanpreet, and Kiela Douwe. 2024 · 2024
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Kaining Ying, Fanqing Meng, Jin Wang, Zhiqian Li, Han Lin, Yue Yang, Hao Zhang, Wenbo Zhang, Yuqi Lin, Shuo Liu, et al · 2024
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