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Diffusion generative models have demonstrated remarkable success in visual domains such as image and video generation.
Mish: A Self Regularized Non-Monotonic Activation Function
Misra, D. (2019) · 1908
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G-HOP: Generative Hand-Object Prior for Interaction Reconstruction and Grasp Synthesis
Ye, Y., Gupta, A., Kitani, K., and Tulsiani, S. (2024) · 1920
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Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models
Carvalho, J., Le, A. T., Baierl, M., Koert, D., and Peters, J. (2023) · 1923
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D4RL: Datasets for Deep Data-Driven Reinforcement Learning
Fu, J., Kumar, A., Nachum, O., Tucker, G., and Levine, S. (2020) · 2004
Earlier work this paper cites.
Offline reinforcement learning: Tutorial, review, and perspectives on open problems
Levine, S., Kumar, A., Tucker, G., and Fu, J. (2020) · 2005
Earlier work this paper cites.
Efficient Reductions for Imitation Learning
Ross, S. and Bagnell, D. (2010) · 2010
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Receding Horizon Control
Mattingley, J., Wang, Y., and Boyd, S. (2011) · 2011
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Data-driven grasp synthesis—a survey
Bohg, J., Morales, A., Asfour, T., and Kragic, D. (2013) · 2013
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., and Brox, T. (2015) · 2015
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Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S. (2015) · 2015
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Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., and Sun, J. (2016) · 2016
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Generative Adversarial Imitation Learning
Ho, J. and Ermon, S. (2016) · 2016
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Hindsight Experience Replay
Andrychowicz, M., Wolski, F., Ray, A., Schneider, J., Fong, R., Welinder, P., McGrew, B., Tobin, J., Pieter Abbeel, O., and Zaremba, W. (2017) · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Qi, C. R., Yi, L., Su, H., and Guibas, L. J. (2017) · 2017
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Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
Rajeswaran, A., Kumar, V., Gupta, A., Vezzani, G., Schulman, J., Todorov, E., and Levine, S. (2017) · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Tarvainen, A. and Valpola, H. (2017) · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
Tobin, J., Fong, R., Ray, A., Schneider, J., Zaremba, W., and Abbeel, P. (2017) · 2017
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Are GANs Created Equal? A Large-Scale Study
Lucic, M., Kurach, K., Google, M. M., Bousquet, B. O., and Gelly, S. (2018) · 2018
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FiLM: Visual Reasoning with a General Conditioning Layer
Perez, E., Strub, F., De Vries, H., Dumoulin, V., and Courville, A. (2018) · 2018
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Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization
Tremblay, J., Prakash, A., Acuna, D., Brophy, M., Jampani, V., Anil, C., To, T., Cameracci, E., Boochoon, S., and Birchfield, S. (2018) · 2018
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Occupancy networks: Learning 3d reconstruction in function space
Mescheder, L., Oechsle, M., Niemeyer, M., Nowozin, S., and Geiger, A. (2019) · 2019
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6-DOF GraspNet: Variational Grasp Generation for Object Manipulation
Mousavian, A., Eppner, C., and Fox, D. (2019) · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
Park, J. J., Florence, P., Straub, J., Newcombe, R., and Lovegrove, S. (2019) · 2019
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Efficient learning on point clouds with basis point sets
Prokudin, S., Lassner, C., and Romero, J. (2019) · 2019
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Generative Modeling by Estimating Gradients of the Data Distribution
Song, Y. and Ermon, S. (2019) · 2019
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al. (2020) · 2020
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Graspnet-1billion: A large-scale benchmark for general object grasping
Fang, H.-S., Wang, C., Gou, M., and Lu, C. (2020) · 2020
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Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning
Gupta, A., Kumar, V., Lynch, C., Levine, S., and Hausman, K. (2020) · 2020
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Denoising Diffusion Probabilistic Models
Ho, J., Jain, A., and Abbeel, P. (2020) · 2020
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RLBench: The Robot Learning Benchmark & Learning Environment
James, S., Ma, Z., Arrojo, D. R., and Davison, A. J. (2020) · 2020
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NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
Mildenhall, B., Srinivasan, P. P., Tancik, M., Barron, J. T., Ramamoorthi, R., and Ng, R. (2020) · 2020
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., and Liu, P. J. (2020) · 2020
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Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Yu, T., Quillen, D., He, Z., Julian, R., Hausman, K., Finn, C., and Levine, S. (2020) · 2020
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Transporter Networks: Rearranging the Visual World for Robotic Manipulation
Zeng, A., Florence, P., Tompson, J., Welker, S., Chien, J., Attarian, M., Armstrong, T., Krasin, I., Duong, D., Sindhwani, V., and Lee, J. (2021) · 2020
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Volumetric grasping network: Real-time 6 dof grasp detection in clutter
Breyer, M., Chung, J. J., Ott, L., Siegwart, R., and Nieto, J. (2021) · 2021
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The EPIC-KITCHENS Dataset: Collection, Challenges and Baselines
Damen, D., Doughty, H., Farinella, G. M., Fidler, S., Furnari, A., Kazakos, E., Moltisanti, D., Munro, J., Perrett, T., Price, W., and Wray, M. (2021) · 2021
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Vector neurons: A general framework for so (3)-equivariant networks
Deng, C., Litany, O., Duan, Y., Poulenard, A., Tagliasacchi, A., and Guibas, L. J. (2021) · 2021
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Diffusion Models Beat GANs on Image Synthesis
Dhariwal, P. and Nichol, A. (2021) · 2021
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., and Houlsby, N. (2021) · 2021
Earlier work this paper cites.
Acronym: A large-scale grasp dataset based on simulation
Eppner, C., Mousavian, A., and Fox, D. (2021) · 2021
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Taming Transformers for High-Resolution Image Synthesis
Esser, P., Rombach, R., and Ommer, B. (2021) · 2021
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Classifier-Free Diffusion Guidance
Ho, J., Research, G., and Salimans, T. (2021) · 2021
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Synergies between affordance and geometry: 6-dof grasp detection via implicit representations
Jiang, Z., Zhu, Y., Svetlik, M., Fang, K., and Zhu, Y. (2021) · 2021
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Gotta Go Fast with Score-Based Generative Models
Jolicoeur-Martineau, A., Li, K., Piché-Taillefer, R., and Kachman, T. (2021) · 2021
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Learning Transferable Visual Models From Natural Language Supervision
Meila, M. and Zhang, T. (2021) · 2021
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Improved Denoising Diffusion Probabilistic Models
Nichol, A. Q. and Dhariwal, P. (2021) · 2021
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Learning transferable visual models from natural language supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al. (2021) · 2021
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Taps: Task-agnostic policy sequencing
Agia, C., Migimatsu, T., Wu, J., and Bohg, J. (2022) · 2022
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Xmem: Long-term video object segmentation with an atkinson-shiffrin memory model
Cheng, H. K. and Schwing, A. G. (2022) · 2022
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Implicit Behavioral Cloning
Florence, P., Lynch, C., Zeng, A., Ramirez, O., Wahid, A., Downs, L., Wong, A., Lee, J., Mordatch, I., and Tompson, J. (2022) · 2022
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Vector Quantized Diffusion Model for Text-to-Image Synthesis
Gu, S., Chen, D., Bao, J., Wen, F., Zhang, B., Chen, D., Yuan, L., and Guo, B. (2022) · 2022
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Planning with Diffusion for Flexible Behavior Synthesis
Janner, M., Du, Y., Tenenbaum, J., and Levine, S. (2022) · 2022
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Elucidating the Design Space of Diffusion-Based Generative Models
Karras, T., Aittala, M., Aila, T., and Laine, S. (2022) · 2022
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Diffusion-LM Improves Controllable Text Generation
Li, X., Thickstun, J., Gulrajani, I., Liang, P. S., and Hashimoto, T. B. (2022) · 2022
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DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps
Lu, C., Zhou, Y., Bao, F., Chen, J., Li, C., and Zhu, J. (2022) · 2022
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Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression
Ma, J. Y., Yan, J., Jayaraman, D., and Bastani, O. (2022) · 2022
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CACTI: A framework for scalable multi-task multi-scene visual imitation learning
Mandi, Z., Bharadhwaj, H., Moens, V., Song, S., Rajeswaran, A., and Kumar, V. (2022) · 2022
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What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
Mandlekar, A., Xu, D., Wong, J., Nasiriany, S., Wang, C., Kulkarni, R., Fei-Fei, L., Savarese, S., Zhu, Y., and Martín-Martín, R. (2022) · 2022
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Hyperspectral endoscopy using deep learning for laryngeal cancer segmentation
Meyer-Veit, F., Rayyes, R., Gerstner, A. O. H., and Steil, J. (2022b) · 2022
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Imitating Human Behaviour with Diffusion Models
Pearce, T., Rashid, T., Kanervisto, A., Bignell, D., Sun, M., Georgescu, R., Macua, S. V., Tan, S. Z., Momennejad, I., Hofmann, K., and Devlin, S. (2022) · 2022
Earlier work this paper cites.
Hierarchical Text-Conditional Image Generation with CLIP Latents
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M. (2022) · 2022
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Progressive Distillation for Fast Sampling of Diffusion Models
Salimans, T. and Ho, J. (2022) · 2022
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CLIPort: What and Where Pathways for Robotic Manipulation
Shridhar, M., Manuelli, L., and Fox, D. (2022) · 2022
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BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
Srivastava, S., Li, C., Lingelbach, M., Martín-Martín, R., Xia, F., Vainio, K. E., Lian, Z., Gokmen, C., Buch, S., Liu, K., Savarese, S., Gweon, H., Wu, J., and Fei-Fei, L. (2022) · 2022
Cited alongside, same era.
Learning Fast Samplers for Diffusion Models by Differentiating trough Sample Quality
Watson, D., Chan, W., Ho, J., and Norouzi, M. (2022) · 2022
Cited alongside, same era.
Oakink: A large-scale knowledge repository for understanding hand-object interaction
Yang, L., Li, K., Zhan, X., Wu, F., Xu, A., Liu, L., and Lu, C. (2022) · 2022
Cited alongside, same era.
Latent Diffusion Energy-Based Model for Interpretable Text Modelling
Yu, P., Xie, S., Ma, X., Jia, B., Pang, B., Gao, R., Zhu, Y., Zhu, S.-C., and Wu, Y. N. (2022) · 2022
Cited alongside, same era.
DA 2 Dataset: Toward Dexterity-Aware Dual-Arm Grasping
Zhai, G., Zheng, Y., Xu, Z., Kong, X., Liu, Y., Busam, B., Ren, Y., Navab, N., and Zhang, Z. (2022) · 2022
Cited alongside, same era.
Diffusion Reward: Learning Rewards via Conditional Video Diffusion
Huang, T., Jiang, G., Ze, Y., Xu, H., Qi, S., and Institute, Z. (2025b) · 2024
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Subgoal Diffuser: Coarse-to-fine Subgoal Generation to Guide Model Predictive Control for Robot Manipulation
Huang, Z., Lin, Y., Yang, F., and Berenson, D. (2024b) · 2024
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Diffusionnocs: Managing symmetry and uncertainty in sim2real multi-modal category-level pose estimation
Ikeda, T., Zakharov, S., Ko, T., Irshad, M. Z., Lee, R., Liu, K., Ambrus, R., and Nishiwaki, K. (2024) · 2024
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Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations
Jia, X., Blessing, D., Jiang, X., Reuss, M., Donat, A., Lioutikov, R., and Neumann, G. (2024) · 2024
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Dream2Real: Zero-Shot 3D Object Rearrangement with Vision-Language Models
Kapelyukh, I., Ren, Y., Alzugaray, I., and Johns, E. (2024) · 2024
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IS Conditional Generative Modeling All You Need for Decision-Making?
Ajay, A., Du, Y., Gupta, A., Tenenbaum, J., Jaakkola, T., and Agrawal, P. (2023) · 2023
Cited alongside, same era.
EDGI: Equivariant diffusion for planning with embodied agents
Brehmer, J., Bose, J., de Haan, P., and Cohen, T. S. (2023) · 2023
Cited alongside, same era.
Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
Chi, C., Feng, S., Du, Y., Xu, Z., Cousineau, E., Burchfiel, B., and Song, S. (2023) · 2023
Cited alongside, same era.
Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning
Ding, Z. and Jin, C. (2023) · 2023
Cited alongside, same era.
Learning Universal Policies via Text-Guided Video Generation
Du, Y., Yang, S., Dai, B., Dai, H., Nachum, O., Tenenbaum, J., Schuurmans, D., and Abbeel, P. (2023) · 2023
Cited alongside, same era.
Motion Policy Networks
Fishman, A., Murali, A., Eppner, C., Peele, B., Boots, B., and Fox, D. (2023) · 2023
Cited alongside, same era.
Diffusion Policies as Multi-Agent Reinforcement Learning Strategies
Geng, J., Liang, X., Wang, H., and Zhao, Y. (2023) · 2023
Cited alongside, same era.
RIC: Rotate-Inpaint-Complete for Generalizable Scene Reconstruction
Kasahara, I., Agrawal, S., Engin, S., Chavan-Dafle, N., Song, S., and Isler, V. (2024) · 2024
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Gen2Sim: Scaling up Robot Learning in Simulation with Generative Models
Katara, P., Xian, Z., and Fragkiadaki, K. (2024) · 2024
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3D Diffuser Actor: Policy Diffusion with 3D Scene Representations
Ke, T.-W., Gkanatsios, N., and Fragkiadaki, K. (2024) · 2024
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Learning to Act from Actionless Videos through Dense Correspondences
Ko, P.-C., Mao, J., Du, Y., Sun, S.-H., and Tenenbaum, J. B. (2024) · 2024
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Crossway Diffusion: Improving Diffusion-based Visuomotor Policy via Self-supervised Learning
Li, X., Belagali, V., Shang, J., and Ryoo, M. S. (2024c) · 2024
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SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task Execution
Liang, Z., Mu, Y., Ma, H., Tomizuka, M., Ding, M., and Luo, P. (2024) · 2024
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EquiGraspFlow: SE (3)-Equivariant 6-DoF Grasp Pose Generative Flows
Lim, B., Kim, J., Kim, J., Lee, Y., and Park, F. C. (2024) · 2024
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RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
Liu, S., Wu, L., Li, B., Tan, H., Chen, H., Wang, Z., Xu, K., Su, H., and Zhu, J. (2024) · 2024
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Grounding dino: Marrying dino with grounded pre-training for open-set object detection
Liu, S., Zeng, Z., Ren, T., Li, F., Zhang, H., Yang, J., Jiang, Q., Li, C., Yang, J., Su, H., Zhu, J., and Zhang, L. (2025) · 2024
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Ugg: Unified generative grasping
Lu, J., Kang, H., Li, H., Liu, B., Yang, Y., Huang, Q., and Hua, G. (2025) · 2024
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ReorientDiff: Diffusion Model based Reorientation for Object Manipulation
Mishra, U. A. and Chen, Y. (2024) · 2024
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Lightweight Language-driven Grasp Detection using Conditional Consistency Model
Nguyen, N., Vu, M. N., Huang, B., Vuong, A., Le, N., Vo, T., and Nguyen, A. (2024a) · 2024
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Language-Conditioned Affordance-Pose Detection in 3D Point Clouds
Nguyen, T., Vu, M. N., Huang, B., Van Vo, T., Truong, V., Le, N., Vo, T., Le, B., and Nguyen, A. (2024b) · 2024
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Exploiting Priors from 3D Diffusion Models for RGB-Based One-Shot View Planning
Pan, S., Jin, L., Huang, X., Stachniss, C., Popović, M., and Bennewitz, M. (2024b) · 2024
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On the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control
Pfrommer, D., Padmanabhan, S., Ahn, K., Umenberger, J., Marcucci, T., Mhammedi, Z., and Jadbabaie, A. (2024) · 2024
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Consistency Policy Accelerated Visuomotor Policies via Consistency Distillation
Prasad, A., Lin, K., Wu, J., Zhou, L., and Bohg, J. (2024) · 2024
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ThinkGrasp: A Vision-Language System for Strategic Part Grasping in Clutter
Qian, Y., Zhu, X., Biza, O., Jiang, S., Zhao, L., Huang, H., Qi, Y., and Platt, R. (2024) · 2024
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Diffusion Policy Policy Optimization
Ren, A. Z., Lidard, J., Ankile, L. L., Simeonov, A., Agrawal, P., Majumdar, A., Burchfiel, B., Dai, H., and Simchowitz, M. (2024) · 2024
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Diffusion Predictive Control with Constraints
Römer, R., von Rohr, A., and Schoellig, A. P. (2024) · 2024
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Flow Matching Imitation Learning for Multi-Support Manipulation
Rouxel, Q., Ferrari, A., Ivaldi, S., and Mouret, J.-B. (2024) · 2024
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Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation
Ryu, H., Kim, J., An, H., Chang, J., Seo, J., Kim, T., Kim, Y., Hwang, C., Choi, J., and Horowitz, R. (2024) · 2024
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EDMP: Ensemble-of-costs-guided Diffusion for Motion Planning
Saha, K., Mandadi, V., Reddy, J., Srikanth, A., Agarwal, A., Sen, B., Singh, A., and Krishna, M. (2024) · 2024
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Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects
Scheikl, P. M., Schreiber, N., Haas, C., Freymuth, N., Neumann, G., Lioutikov, R., and Mathis-Ullrich, F. (2024) · 2024
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From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control
Shentu, Y., Wu, P., Rajeswaran, A., and Abbeel, P. (2024) · 2024
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vMF-Contact: Uncertainty-aware Evidential Learning for Probabilistic Contact-grasp in Noisy Clutter
Shi, Y., Welte, E., Gilles, M., and Rayyes, R. (2024) · 2024
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Tilde: Teleoperation for Dexterous In-Hand Manipulation Learning with a DeltaHand
Si, Z., Zhang, K., Temel, Z., and Kroemer, O. (2024) · 2024
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Constrained 6-DoF Grasp Generation on Complex Shapes for Improved Dual-Arm Manipulation
Singh, G., Kalwar, S., Karim, M. F., Sen, B., Govindan, N., Sridhar, S., and Krishna, K. M. (2024) · 2024
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Octo: An Open-Source Generalist Robot Policy
Team, O. M., Ghosh, D., Walke, H., Pertsch, K., Black, K., Mees, O., Dasari, S., Hejna, J., Kreiman, T., Xu, C., Luo, J., Tan, Y. L., Chen, L. Y., Sanketi, P., Vuong, Q., Xiao, T., Sadigh, D., Finn, C., and Levine, S. (2024) · 2024
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Click to Grasp: Zero-Shot Precise Manipulation via Visual Diffusion Descriptors
Tsagkas, N., Rome, J., Ramamoorthy, S., Aodha, O. M., and Lu, C. X. (2024) · 2024
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Render and Diffuse: Aligning Image and Action Spaces for Diffusion-based Behaviour Cloning
Vosylius, V., Seo, Y., Uruç, J., and James, S. (2024) · 2024
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Language-driven Grasp Detection
Vuong, A. D., Vu, M. N., Huang, B., Nguyen, N., Le, H., Vo, T., and Nguyen, A. (2024) · 2024
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Diffusion-VLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression
Wen, J., Zhu, M., Zhu, Y., Tang, Z., Li, J., Zhou, Z., Li, C., Liu, X., Peng, Y., Shen, C., and Feng, F. (2024) · 2024
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DexDiffuser: Generating Dexterous Grasps With Diffusion Models
Weng, Z., Lu, H., Kragic, D., and Lundell, J. (2024) · 2024
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”Set It Up!”: Functional Object Arrangement with Compositional Generative Models
Xu, Y., Mao, J., Du, Y., Lozáno-Pérez, T., Pack Kaebling, L., and Hsu, D. (2024) · 2024
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Learning Interactive Real-World Simulators
Yang, S., Du, Y., Kamyar, S., Ghasemipour, S., Tompson, J., Kaelbling, L., Schuurmans, D., and Abbeel, P. (2024) · 2024
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A survey of imitation learning: Algorithms, recent developments, and challenges
Zare, M., Kebria, P. M., Khosravi, A., and Nahavandi, S. (2024) · 2024
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3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations
Ze, Y., Zhang, G., Zhang, K., Hu, C., Wang, M., Xu, H., Institute, S. Q., and Jiao, S. (2024) · 2024
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LVDiffusor: Distilling Functional Rearrangement Priors from Large Models into Diffusor
Zeng, Y., Wu, M., Yang, L., Zhang, J., Ding, H., Cheng, H., and Dong, H. (2024) · 2024
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Nl2contact: Natural language guided 3d hand-object contact modeling with diffusion model
Zhang, Z., Wang, H., Yu, Z., Cheng, Y., Yao, A., and Chang, H. J. (2025) · 2024
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3D-VLA: A 3D vision-language-action generative world model
Zhen, H., Qiu, X., Chen, P., Yang, J., Yan, X., Du, Y., Hong, Y., and Gan, C. (2024) · 2024
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Foundation models in robotics: Applications, challenges, and the future
Firoozi, R., Tucker, J., Tian, S., Majumdar, A., Sun, J., Liu, W., Zhu, Y., Song, S., Kapoor, A., Hausman, K., Ichter, B., Driess, D., Wu, J., Lu, C., and Schwager, M. (2025) · 2025
Closest in time.
One Step Diffusion via Shortcut Models
Frans, K., Hafner, D., Levine, S., and Abbeel, P. (2025) · 2025
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Diffusion for Multi-Embodiment Grasping
Freiberg, R., Qualmann, A., Vien, N. A., and Neumann, G. (2025) · 2025
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MetaMVUC: Active learning for sample-efficient sim-to-real domain adaptation in robotic grasping
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