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In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts.
All you may need for VQA are image captions
Soravit Changpinyo, Doron Kukliansy, Idan Szpektor, Xi Chen, Nan Ding, and Radu Soricut. 2022 · 1963
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Cognitive tutors: Lessons learned
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The iam-database: an english sentence database for offline handwriting recognition
U-V Marti. 2002 · 2002
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Iam-ondb - an on-line english sentence database acquired from handwritten text on a whiteboard
M. Liwicki and H. Bunke. 2005 · 2005
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Hit-or3c: an opening recognition corpus for chinese characters
Shusen Zhou, Qingcai Chen, and Xiaolong Wang. 2010 · 2010
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Crohme2011: Competition on recognition of online handwritten mathematical expressions
Harold Mouchere, Christian Viard-Gaudin, Dae Hwan Kim, Jin Hyung Kim, and Utpal Garain. 2011 · 2011
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Common core standards: The new us intended curriculum
Andrew Porter, Jennifer McMaken, Jun Hwang, and Rui Yang. 2011 · 2011
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David Ebert. 2014 · 2014
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The assistments ecosystem: Building a platform that brings scientists and teachers together for minimally invasive research on human learning and teaching
Neil T Heffernan and Cristina Lindquist Heffernan. 2014 · 2014
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Bag of what? simple noun phrase extraction for text analysis
Abram Handler, Matthew Denny, Hanna Wallach, and Brendan O’Connor. 2016 · 2016
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Emnist: Extending mnist to handwritten letters
Gregory Cohen, Saeed Afshar, Jonathan Tapson, and André van Schaik. 2017 · 2017
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Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017 · 2017
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Connecting vision and language with localized narratives
Jordi Pont-Tuset, Jasper R. R. Uijlings, Soravit Changpinyo, Radu Soricut, and Vittorio Ferrari. 2019 · 2019
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Computational grounded theory: A methodological framework
Laura K Nelson. 2020 · 2020
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Supporting children’s math learning with feedback-augmented narrative technology
Sherry Ruan, Jiayu He, Rui Ying, Jonathan Burkle, Dunia Hakim, Anna Wang, Yufeng Yin, Lily Zhou, Qianyao Xu, Abdallah AbuHashem, et al. 2020 · 2020
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Khan academy effectiveness: The case of math secondary students’ perceptions
Hava E Vidergor and Paz Ben-Amram. 2020 · 2020
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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Improving automated scoring of student open responses in mathematics
Sami Baral, Anthony F Botelho, John A Erickson, Priyanka Benachamardi, and Neil T Heffernan. 2021 · 2021
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GeoQA: A geometric question answering benchmark towards multimodal numerical reasoning
Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric Xing, and Liang Lin. 2021 · 2021
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The Claude 3 model family: Opus, Sonnet, Haiku
AI Anthropic. 2024 · 2024
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Molmo and pixmo: Open weights and open data for state-of-the-art multimodal models
Matt Deitke, Christopher Clark, Sangho Lee, Rohun Tripathi, Yue Yang, Jae Sung Park, Mohammadreza Salehi, Niklas Muennighoff, Kyle Lo, Luca Soldaini, Jiasen Lu, Taira Anderson, Erin Bransom, Kiana Ehsani, Huong Ngo, YenSung Chen, Ajay Patel, Mark Yatskar, Christopher Callison-Burch, Andrew Head, Rose Hendrix, Favyen Bastani, Eli VanderBilt, Nathan Lambert, Yvonne Chou, Arnavi Chheda, Jenna Sparks, Sam Skjonsberg, Michael Schmitz, Aaron Sarnat, Byron Bischoff, Pete Walsh, Christopher Newell, Piper Wolters, Tanmay Gupta, Kuo-Hao Zeng, Jon Borchardt, Dirk Groeneveld, Jennifer Dumas, Crystal Nam, Sophie Lebrecht, Caitlin Wittlif, Carissa Schoenick, Oscar Michel, Ranjay Krishna, Luca Weihs, Noah A. Smith, Hanna Hajishirzi, Ross Girshick, Ali Farhadi, and Aniruddha Kembhavi. 2024 · 2024
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Ai-powered innovations in mathematics teaching and learning: Request for information
Bill & Melinda Gates Foundation. 2024 · 2024
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Mathwriting: A dataset for handwritten mathematical expression recognition
Philippe Gervais, Asya Fadeeva, and Andrii Maksai. 2024 · 2024
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021
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Inter-GPS: Interpretable geometry problem solving with formal language and symbolic reasoning
Pan Lu, Ran Gong, Shibiao Jiang, Liang Qiu, Siyuan Huang, Xiaodan Liang, and Song-Chun Zhu. 2021 · 2021
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Algorithmic fairness in education
René F Kizilcec and Hansol Lee. 2022 · 2022
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Beyond “fairness”: Structural (in) justice lenses on ai for education
Michael Madaio, Su Lin Blodgett, Elijah Mayfield, and Ezekiel Dixon-Román. 2022 · 2022
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Robust speech recognition via large-scale weak supervision
Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, and Ilya Sutskever. 2022 · 2022
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Auto-scoring student responses with images in mathematics
Sami Baral, Anthony Botelho, Abhishek Santhanam, Ashish Gurung, Li Cheng, and Neil Heffernan. 2023 · 2023
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Leveraging natural language processing to support automated assessment and feedback for student open responses in mathematics
Anthony Botelho, Sami Baral, John A Erickson, Priyanka Benachamardi, and Neil T Heffernan. 2023 · 2023
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Google learnlm and gemini: How google’s generative ai is transforming learning
Google. 2023 · 2024
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Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2024 · 2024
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Why we’re deeply invested in making ai better at math tutoring (and what we’ve been up to lately)
Khan Academy. 2024 · 2024
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Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, and Jianfeng Gao. 2024 · 2024
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Scaling high-leverage curriculum scaffolding in middle-school mathematics
Rizwaan Malik, Dorna Abdi, Rose Wang, and Dorottya Demszky. 2024 · 2024
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Llama 3.2: Revolutionizing edge ai and vision with open, customizable models
Meta AI. 2024 · 2024
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Khan academy and microsoft partner to expand access to ai tools
Microsoft News Center. 2024 · 2024
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Chatgpt-generated help produces learning gains equivalent to human tutor-authored help on mathematics skills
Zachary A Pardos and Shreya Bhandari. 2024 · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al. 2024 · 2024
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MMMU: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al. 2024 · 2024
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Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems?
Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Peng Gao, and Hongsheng Li. 2024 · 2024
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