Fetching the paper…
Reading the bibliography…
Multimodal Large Language Models (MLLMs) excel in understanding complex language and visual data, enabling generalist robotic systems to interpret instructions and perform embodied tasks.
The open motion planning library
Ioan A Sucan, Mark Moll, and Lydia E Kavraki · 2012
Earlier work this paper cites.
Outrageously large neural networks: The sparsely-gated mixture-of-experts layer, 2017
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean · 2017
Earlier work this paper cites.
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach, 2019
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
Earlier work this paper cites.
Rlbench: The robot learning benchmark & learning environment
Stephen James, Zicong Ma, David Rovick Arrojo, and Andrew J Davison · 2020
Earlier work this paper cites.
Calvin: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks
Oier Mees, Lukas Hermann, Erick Rosete-Beas, and Wolfram Burgard · 2022
Earlier work this paper cites.
Efficientvlm: Fast and accurate vision-language models via knowledge distillation and modal-adaptive pruning, 2022
Tiannan Wang, Wangchunshu Zhou, Yan Zeng, and Xinsong Zhang · 2022
Earlier work this paper cites.
Openflamingo: An open-source framework for training large autoregressive vision-language models, 2023
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
Earlier work this paper cites.
Skipdecode: Autoregressive skip decoding with batching and caching for efficient llm inference
Luciano Del Corro, Allie Del Giorno, Sahaj Agarwal, Bin Yu, Ahmed Awadallah, and Subhabrata Mukherjee · 2023
Earlier work this paper cites.
Minillm: Knowledge distillation of large language models
Yuxian Gu, Li Dong, Furu Wei, and Minlie Huang · 2023
Earlier work this paper cites.
Vision-language foundation models as effective robot imitators
Xinghang Li, Minghuan Liu, Hanbo Zhang, Cunjun Yu, Jie Xu, Hongtao Wu, Chilam Cheang, Ya Jing, Weinan Zhang, Huaping Liu, et al · 2023
Earlier work this paper cites.
Visual instruction tuning, 2023
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
Cited alongside, same era.
Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer, 2023
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2023
Cited alongside, same era.
How deep is the brain? the shallow brain hypothesis
Mototaka Suzuki, Cyriel MA Pennartz, and Jaan Aru · 2023
Cited alongside, same era.
Llama: Open and efficient foundation language models, 2023
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample · 2023
Cited alongside, same era.
Prismatic vlms: Investigating the design space of visually-conditioned language models, 2024
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, and Dorsa Sadigh · 2024
Later among the works it cites.
Openvla: An open-source vision-language-action model, 2024
Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Foster, Grace Lam, Pannag Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, and Chelsea Finn · 2024
Later among the works it cites.
Moe-llava: Mixture of experts for large vision-language models, 2024
Bin Lin, Zhenyu Tang, Yang Ye, Jinfa Huang, Junwu Zhang, Yatian Pang, Peng Jin, Munan Ning, Jiebo Luo, and Li Yuan · 2024
Later among the works it cites.
Robomamba: Efficient vision-language-action model for robotic reasoning and manipulation, 2024
Jiaming Liu, Mengzhen Liu, Zhenyu Wang, Pengju An, Xiaoqi Li, Kaichen Zhou, Senqiao Yang, Renrui Zhang, Yandong Guo, and Shanghang Zhang · 2024
Later among the works it cites.
Llm as dataset analyst: Subpopulation structure discovery with large language model
Yulin Luo, Ruichuan An, Bocheng Zou, Yiming Tang, Jiaming Liu, and Shanghang Zhang · 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sigmoid loss for language image pre-training
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, and Lucas Beyer · 2023
Cited alongside, same era.
Mc-llava: Multi-concept personalized vision-language model
Ruichuan An, Sihan Yang, Ming Lu, Kai Zeng, Yulin Luo, Ying Chen, Jiajun Cao, Hao Liang, Qi She, Shanghang Zhang, et al · 2024
Cited alongside, same era.
Universal manipulation interface: In-the-wild robot teaching without in-the-wild robots
Cheng Chi, Zhenjia Xu, Chuer Pan, Eric Cousineau, Benjamin Burchfiel, Siyuan Feng, Russ Tedrake, and Shuran Song · 2024
Cited alongside, same era.
Deepseekmoe: Towards ultimate expert specialization in mixture-of-experts language models, 2024
Damai Dai, Chengqi Deng, Chenggang Zhao, R. X. Xu, Huazuo Gao, Deli Chen, Jiashi Li, Wangding Zeng, Xingkai Yu, Y. Wu, Zhenda Xie, Y. K. Li, Panpan Huang, Fuli Luo, Chong Ruan, Zhifang Sui, and Wenfeng Liang · 2024
Cited alongside, same era.
Mamba: Linear-time sequence modeling with selective state spaces, 2024
Albert Gu and Tri Dao · 2024
Cited alongside, same era.
Yueru Jia, Jiaming Liu, Sixiang Chen, Chenyang Gu, Zhilue Wang, Longzan Luo, Lily Lee, Pengwei Wang, Zhongyuan Wang, Renrui Zhang, et al · 2024
Cited alongside, same era.
Flamingo: a visual language model for few-shot learning, 2022a
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katie Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andrew Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, and Karen Simonyan
Cited in the paper.
Later among the works it cites.
Gpt-4 technical report, 2024
OpenAI et al · 2024
Later among the works it cites.
Mixture-of-depths: Dynamically allocating compute in transformer-based language models, 2024
David Raposo, Sam Ritter, Blake Richards, Timothy Lillicrap, Peter Conway Humphreys, and Adam Santoro · 2024
Later among the works it cites.
Vitkd: Feature-based knowledge distillation for vision transformers
Zhendong Yang, Zhe Li, Ailing Zeng, Zexian Li, Chun Yuan, and Yu Li · 2024
Later among the works it cites.
Fit and prune: Fast and training-free visual token pruning for multi-modal large language models
Weihao Ye, Qiong Wu, Wenhao Lin, and Yiyi Zhou · 2024
Later among the works it cites.
Deer-vla: Dynamic inference of multimodal large language models for efficient robot execution, 2024
Yang Yue, Yulin Wang, Bingyi Kang, Yizeng Han, Shenzhi Wang, Shiji Song, Jiashi Feng, and Gao Huang · 2024
Later among the works it cites.
Move-kd: Knowledge distillation for vlms with mixture of visual encoders
Jiajun Cao, Yuan Zhang, Tao Huang, Ming Lu, Qizhe Zhang, Ruichuan An, Ningning Ma, and Shanghang Zhang · 2025
Closest in time.