Fetching the paper…
Reading the bibliography…
Large language models have demonstrated substantial advancements in reasoning capabilities.
Sequence transduction with recurrent neural networks
Alex Graves · 2012
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
Earlier work this paper cites.
A diagram is worth a dozen images
Aniruddha Kembhavi, Mike Salvato, Eric Kolve, Minjoon Seo, Hannaneh Hajishirzi, and Ali Farhadi · 2016
Earlier work this paper cites.
Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C. Lawrence Zitnick, and Ross Girshick · 2017
Earlier work this paper cites.
People in social context (pisc) dataset, 2017
Junnan Li, Yongkang Wong, Qi Zhao, and Mohan S. Kankanhalli · 2017
Earlier work this paper cites.
From recognition to cognition: Visual commonsense reasoning, 2019
Rowan Zellers, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
Earlier work this paper cites.
Neuro-symbolic visual reasoning: Disentangling
Saeed Amizadeh, Hamid Palangi, Alex Polozov, Yichen Huang, and Kazuhito Koishida · 2020
Earlier work this paper cites.
Commonsense reasoning for natural language processing
Maarten Sap, Vered Shwartz, Antoine Bosselut, Yejin Choi, and Dan Roth · 2020
Earlier work this paper cites.
Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies
Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, and Jonathan Berant · 2021
Earlier work this paper cites.
Docvqa: A dataset for vqa on document images
Minesh Mathew, Dimosthenis Karatzas, and C. V. Jawahar · 2021
Earlier work this paper cites.
An augmented benchmark dataset for geometric question answering through dual parallel text encoding
Jie Cao and Jing Xiao · 2022
Earlier work this paper cites.
Clevr-math: A dataset for compositional language, visual and mathematical reasoning
Adam Dahlgren Lindström and Savitha Sam Abraham · 2022
Earlier work this paper cites.
Large language models can self-improve
Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, and Jiawei Han · 2022
Earlier work this paper cites.
Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan · 2022
Earlier work this paper cites.
ChartQA: A benchmark for question answering about charts with visual and logical reasoning
Ahmed Masry, Do Long, Jia Qing Tan, Shafiq Joty, and Enamul Hoque · 2022
Earlier work this paper cites.
A-okvqa: A benchmark for visual question answering using world knowledge, 2022
Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, Kenneth Marino, and Roozbeh Mottaghi · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Earlier work this paper cites.
Foundational models defining a new era in vision: A survey and outlook
Muhammad Awais, Muzammal Naseer, Salman Khan, Rao Muhammad Anwer, Hisham Cholakkal, Mubarak Shah, Ming-Hsuan Yang, and Fahad Shahbaz Khan · 2023
Earlier work this paper cites.
Visual programming: Compositional visual reasoning without training
Tanmay Gupta and Aniruddha Kembhavi · 2023
Cited alongside, same era.
Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes, 2023
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, and Tomas Pfister · 2023
Cited alongside, same era.
Measuring faithfulness in chain-of-thought reasoning, 2023
Tamera Lanham, Anna Chen, Ansh Radhakrishnan, Benoit Steiner, Carson Denison, Danny Hernandez, Dustin Li, Esin Durmus, Evan Hubinger, Jackson Kernion, Kamilė Lukošiūtė, Karina Nguyen, Newton Cheng, Nicholas Joseph, Nicholas Schiefer, Oliver Rausch, Robin Larson, Sam McCandlish, Sandipan Kundu, Saurav Kadavath, Shannon Yang, Thomas Henighan, Timothy Maxwell, Timothy Telleen-Lawton, Tristan Hume, Zac Hatfield-Dodds, Jared Kaplan, Jan Brauner, Samuel R. Bowman, and Ethan Perez · 2023
Cited alongside, same era.
Weakly-supervised 3d spatial reasoning for text-based visual question answering
Hao Li, Jinfa Huang, Peng Jin, Guoli Song, Qi Wu, and Jie Chen · 2023
Cited alongside, same era.
Deductive verification of chain-of-thought reasoning, 2023
Chat-univi: Unified visual representation empowers large language models with image and video understanding
Peng Jin, Ryuichi Takanobu, Wancai Zhang, Xiaochun Cao, and Li Yuan · 2024
Closest in time.
Tokenpacker: Efficient visual projector for multimodal llm
Wentong Li, Yuqian Yuan, Jian Liu, Dongqi Tang, Song Wang, Jianke Zhu, and Lei Zhang · 2024
Closest in time.
Vila: On pre-training for visual language models
Ji Lin, Hongxu Yin, Wei Ping, Pavlo Molchanov, Mohammad Shoeybi, and Song Han · 2024
Closest in time.
Llama 3.2: Revolutionizing edge ai and vision with open, customizable models
Meta AI · 2024
Closest in time.
Gpt-4o mini: advancing cost-efficient intelligence
OpenAI · 2024
Closest in time.
Prism: A framework for decoupling and assessing the capabilities of vlms, 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zhan Ling, Yunhao Fang, Xuanlin Li, Zhiao Huang, Mingu Lee, Roland Memisevic, and Hao Su · 2023
Cited alongside, same era.
A review of emerging research directions in abstract visual reasoning
Mikołaj Małkiński and Jacek Mańdziuk · 2023
Cited alongside, same era.
Language models don’t always say what they think: Unfaithful explanations in chain-of-thought prompting, 2023
Miles Turpin, Julian Michael, Ethan Perez, and Samuel R. Bowman · 2023
Cited alongside, same era.
The dawn of lmms: Preliminary explorations with gpt-4v(ision), 2023
Zhengyuan Yang, Linjie Li, Kevin Lin, Jianfeng Wang, Chung-Ching Lin, Zicheng Liu, and Lijuan Wang · 2023
Cited alongside, same era.
Why johnny can’t prompt: how non-ai experts try (and fail) to design llm prompts
JD Zamfirescu-Pereira, Richmond Y Wong, Bjoern Hartmann, and Qian Yang · 2023
Cited alongside, same era.
Available at:
Claude 3.5 sonnet, 2024 · 2024
Cited alongside, same era.
Gpt-4o system card, 2024
OpenAI (2024) · 2024
Cited alongside, same era.
Variational best-of-n alignment, 2024
Afra Amini, Tim Vieira, and Ryan Cotterell · 2024
Cited alongside, same era.
Yuxuan Qiao, Haodong Duan, Xinyu Fang, Junming Yang, Lin Chen, Songyang Zhang, Jiaqi Wang, Dahua Lin, and Kai Chen · 2024
Closest in time.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context, 2024
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, and et al · 2024
Closest in time.
Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning, 2024
Hao Shao, Shengju Qian, Han Xiao, Guanglu Song, Zhuofan Zong, Letian Wang, Yu Liu, and Hongsheng Li · 2024
Closest in time.
Rethinking data selection for supervised fine-tuning
Ming Shen · 2024
Closest in time.
Scaling llm test-time compute optimally can be more effective than scaling model parameters, 2024
Charlie Snell, Jaehoon Lee, Kelvin Xu, and Aviral Kumar · 2024
Closest in time.
Deepseek-vl2: Mixture-of-experts vision-language models for advanced multimodal understanding, 2024
Zhiyu Wu, Xiaokang Chen, Zizheng Pan, Xingchao Liu, Wen Liu, Damai Dai, Huazuo Gao, Yiyang Ma, Chengyue Wu, Bingxuan Wang, Zhenda Xie, Yu Wu, Kai Hu, Jiawei Wang, Yaofeng Sun, Yukun Li, Yishi Piao, Kang Guan, Aixin Liu, Xin Xie, Yuxiang You, Kai Dong, Xingkai Yu, Haowei Zhang, Liang Zhao, Yisong Wang, and Chong Ruan · 2024
Closest in time.
Teilp: Time prediction over knowledge graphs via logical reasoning
Siheng Xiong, Yuan Yang, Ali Payani, James C Kerce, and Faramarz Fekri · 2024
Closest in time.
Minicpm-v: A gpt-4v level mllm on your phone
Yuan Yao, Tianyu Yu, Ao Zhang, Chongyi Wang, Junbo Cui, Hongji Zhu, Tianchi Cai, Haoyu Li, Weilin Zhao, Zhihui He, et al · 2024
Closest in time.
Improve vision language model chain-of-thought reasoning, 2024
Ruohong Zhang, Bowen Zhang, Yanghao Li, Haotian Zhang, Zhiqing Sun, Zhe Gan, Yinfei Yang, Ruoming Pang, and Yiming Yang · 2024
Closest in time.
Marco-o1: Towards open reasoning models for open-ended solutions, 2024
Yu Zhao, Huifeng Yin, Bo Zeng, Hao Wang, Tianqi Shi, Chenyang Lyu, Longyue Wang, Weihua Luo, and Kaifu Zhang · 2024
Closest in time.
Evaluation of openai o1: Opportunities and challenges of agi, 2024
Tianyang Zhong, Zhengliang Liu, Yi Pan, Yutong Zhang, Yifan Zhou, Shizhe Liang, Zihao Wu, Yanjun Lyu, Peng Shu, Xiaowei Yu, and et al · 2024
Closest in time.
Internlm-xcomposer2. 5-reward: A simple yet effective multi-modal reward model
Yuhang Zang, Xiaoyi Dong, Pan Zhang, Yuhang Cao, Ziyu Liu, Shengyuan Ding, Shenxi Wu, Yubo Ma, Haodong Duan, Wenwei Zhang, et al · 2025
Closest in time.