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Multimodal Large Language Models (MLLMs) have showcased exceptional Chain-of-Thought (CoT) reasoning ability in complex textual inference tasks including causal reasoning.
Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019b · 1905
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Deepreid: Deep filter pairing neural network for person re-identification
Wei Li, Rui Zhao, Tong Xiao, and Xiaogang Wang. 2014 · 2014
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XNLI: Evaluating cross-lingual sentence representations
Alexis Conneau, Ruty Rinott, Guillaume Lample, Adina Williams, Samuel Bowman, Holger Schwenk, and Veselin Stoyanov. 2018 · 2018
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The natural language decathlon: Multitask learning as question answering
Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, and Richard Socher. 2018 · 2018
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CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning
Rohit Girdhar and Deva Ramanan. 2020 · 2020
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Xtreme: A massively multilingual multi-task benchmark for evaluating cross-lingual generalisation
Junjie Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, and Melvin Johnson. 2020 · 2020
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Measuring compositional generalization: A comprehensive method on realistic data
Daniel Keysers, Nathanael Schärli, Nathan Scales, Hylke Buisman, Daniel Furrer, Sergii Kashubin, Nikola Momchev, Danila Sinopalnikov, Lukasz Stafiniak, Tibor Tihon, et al. 2020 · 2020
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COGS: A compositional generalization challenge based on semantic interpretation
Najoung Kim and Tal Linzen. 2020 · 2020
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Guided generation of cause and effect
Zhongyang Li, Xiao Ding, Ting Liu, J. Edward Hu, and Benjamin Van Durme. 2021 · 2021
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Dall·e: Creating images from text
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. 2021 · 2021
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COM2SENSE: A commonsense reasoning benchmark with complementary sentences
Shikhar Singh, Nuan Wen, Yu Hou, Pegah Alipoormolabashi, Te-Lin Wu, Xuezhe Ma, and Nanyun Peng. 2021 · 2021
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Adversarial glue: A multi-task benchmark for robustness evaluation of language models
Boxin Wang, Chejian Xu, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, and Bo Li. 2021 · 2021
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Acre: Abstract causal reasoning beyond covariation
Chi Zhang, Baoxiong Jia, Mark Edmonds, Song-Chun Zhu, and Yixin Zhu. 2021 · 2021
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e-care: a new dataset for exploring explainable causal reasoning
Li Du, Xiao Ding, Kai Xiong, Ting Liu, and Bing Qin. 2022 · 2022
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CRASS: A novel data set and benchmark to test counterfactual reasoning of large language models
Jörg Frohberg and Frank Binder. 2022 · 2022
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The abduction of sherlock holmes: A dataset for visual abductive reasoning
Jack Hessel, Jena D Hwang, Jae Sung Park, Rowan Zellers, Chandra Bhagavatula, Anna Rohrbach, Kate Saenko, and Yejin Choi. 2022 · 2022
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Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al. 2022 · 2022
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Openflamingo: An open-source framework for training large autoregressive vision-language models
Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, and Ludwig Schmidt. 2023 · 2023
Cited alongside, same era.
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 C. H. Hoi. 2023 · 2023
Cited alongside, same era.
Cladder: Assessing causal reasoning in language models
Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, LYU Zhiheng, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, et al. 2023 · 2023
Cited alongside, same era.
Causal reasoning and large language models: Opening a new frontier for causality
Emre Kiciman, Robert Ness, Amit Sharma, and Chenhao Tan. 2023 · 2023
Cited alongside, same era.
Gemini 1.5 models
DeepMind. 2024 · 2024
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Introducing flux.1 tools
FLUXAI. 2024 · 2024
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Blink: Multimodal large language models can see but not perceive
Xingyu Fu, Yushi Hu, Bangzheng Li, Yu Feng, Haoyu Wang, Xudong Lin, Dan Roth, Noah A Smith, Wei-Chiu Ma, and Ranjay Krishna. 2024 · 2024
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Lcm-lookahead for encoder-based text-to-image personalization
Rinon Gal, Or Lichter, Elad Richardson, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or. 2024 · 2024
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Visual riddles: a commonsense and world knowledge challenge for large vision and language models
Nitzan Bitton Guetta, Aviv Slobodkin, Aviya Maimon, Eliya Habba, Royi Rassin, Yonatan Bitton, Idan Szpektor, Amir Globerson, and Yuval Elovici. 2024 · 2024
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Can large language models infer causation from correlation?
Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona Diab, and Bernhard Schölkopf. 2024 · 2024
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Jianling Li, Meishan Zhang, Peiming Guo, Min Zhang, and Yue Zhang. 2023 · 2023
Cited alongside, same era.
Crab: Assessing the strength of causal relationships between real-world events
Angelika Romanou, Syrielle Montariol, Debjit Paul, Leo Laugier, Karl Aberer, and Antoine Bosselut. 2023 · 2023
Cited alongside, same era.
Stability ai: Image generation
Stability AI. 2023 · 2023
Cited alongside, same era.
Causal inference using llm-guided discovery
Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N Balasubramanian, and Amit Sharma. 2023 · 2023
Cited alongside, same era.
Ip-adapter: Text compatible image prompt adapter for text-to-image diffusion models
Hu Ye, Jun Zhang, Sibo Liu, Xiao Han, and Wei Yang. 2023 · 2023
Cited alongside, same era.
Multimodal chain-of-thought reasoning in language models
Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, and Alex Smola. 2023 · 2023
Cited alongside, same era.
Minigpt-4: Enhancing vision-language understanding with advanced large language models
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny. 2023 · 2023
Cited alongside, same era.
Cause and effect: Can large language models truly understand causality?
Swagata Ashwani, Kshiteesh Hegde, Nishith Reddy Mannuru, Mayank Jindal, Dushyant Singh Sengar, Krishna Chaitanya Rao Kathala, Dishant Banga, Vinija Jain, and Aman Chadha. 2024 · 2024
Cited alongside, same era.
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Llava-next-interleave: Tackling multi-image, video, and 3d in large multimodal models
Feng Li, Renrui Zhang, Hao Zhang, Yuanhan Zhang, Bo Li, Wei Li, Zejun Ma, and Chunyuan Li. 2024 · 2024
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Videostudio: Generating consistent-content and multi-scene videos
Fuchen Long, Zhaofan Qiu, Ting Yao, and Tao Mei. 2024 · 2024
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Llama 3.2: Revolutionizing edge ai and vision with open, customizable models
Meta. 2024 · 2024
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Compositional chain-of-thought prompting for large multimodal models
Chancharik Mitra, Brandon Huang, Trevor Darrell, and Roei Herzig. 2024 · 2024
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al. 2024 · 2024
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Geng: An llm-based generic time series data generation approach for edge intelligence via cross-domain collaboration
Xiaomao Zhou, Qingmin Jia, Yujiao Hu, Renchao Xie, Tao Huang, and F Richard Yu. 2024 · 2024
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Ouroboros-diffusion: Exploring consistent content generation in tuning-free long video diffusion
Jingyuan Chen, Fuchen Long, Jie An, Zhaofan Qiu, Ting Yao, Jiebo Luo, and Tao Mei. 2025 · 2025
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Gemini 2.0 models
DeepMind. 2025 · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al. 2025 · 2025
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Muennighoff Niklas, Yang Zitong, Shi Weijia, Li Xiang Lisa, Fei-Fei Li, Hajishirzi Hannaneh, Zettlemoyer Luke, Liang Percy, Candès Emmanuel, and Hashimoto Tatsunori. 2025 · 2025
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