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Embodied robots which can interact with their environment and neighbours are increasingly being used as a test case to develop Artificial Intelligence.
Language models are few-shot learners
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Learning from dialogue after deployment: Feed yourself, chatbot!
Hancock, B., Bordes, A., Mazare, P.-E., and Weston, J. (2019) · 1901
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Understanding artificial intelligence ethics and safety
Leslie, D. (2019) · 1906
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Collaborative multi-agent dialogue model training via reinforcement learning
Papangelis, A., Wang, Y.-C., Molino, P., and Tur, G. (2019) · 1907
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Sentence-bert: Sentence embeddings using siamese bert-networks
Reimers, N. and Gurevych, I. (2019) · 1908
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Adversarial examples in modern machine learning: A review
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Large language models in medicine
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Three laws of robotics
Asimov, I. (1941) · 1941
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Towards quantitative modeling of task confirmations in human-robot dialog
Sattar, J. and Dudek, G. (2011) · 1963
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Artificial intelligence, language, and the study of knowledge
Goldstein, I. and Papert, S. (1977) · 1977
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Society of mind
Minsky, M. (1988) · 1988
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Intelligence without representation
Brooks, R. A. (1991) · 1991
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Grounding in communication
Clark, H. H. and Brennan, S. E. (1991) · 1991
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Class-based n-gram models of natural language
Brown, P. F., Della Pietra, V. J., Desouza, P. V., Lai, J. C., and Mercer, R. L. (1992) · 1992
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Thinking through language
Bloom, P. and Keil, F. C. (2001) · 2001
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The language instinct: How the mind creates language
Pinker, S. (2003) · 2003
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Influence of team composition and task complexity on team performance
Higgs, M., Plewnia, U., and Ploch, J. (2005) · 2005
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Software engineering team diversity and performance
Pieterse, V., Kourie, D. G., and Sonnekus, I. P. (2006) · 2006
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Ai armageddon and the three laws of robotics
McCauley, L. (2007) · 2007
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Investigating the relationship between team role diversity and team performance in information systems teams
Pollock, M. (2009) · 2009
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Ad hoc autonomous agent teams: Collaboration without pre-coordination
Stone, P., Kaminka, G., Kraus, S., and Rosenschein, J. (2010) · 2010
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How language shapes thought
Boroditsky, L. (2011) · 2011
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Language and other cognitive systems. what is special about language?
Chomsky, N. (2011) · 2011
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Relations between language and thought
Gleitman, L. and Papafragou, A. (2013) · 2013
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Reinforcement learning in robotics: A survey
Kober, J., Bagnell, J. A., and Peters, J. (2013) · 2013
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Sorry dave, i’m afraid i can’t do that: Explaining unachievable robot tasks using natural language
Raman, V., Lignos, C., Finucane, C., Lee, K. C., Marcus, M. P., and Kress-Gazit, H. (2013) · 2013
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Are balanced groups better? belbin roles in collaborative learning groups
Meslec, N. and Curșeu, P. L. (2015) · 2015
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Concrete problems in ai safety
Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., and Mané, D. (2016) · 2016
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Information density and linguistic encoding (ideal)
Crocker, M. W., Demberg, V., and Teich, E. (2016) · 2016
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A framework for collaborative robot (cobot) integration in advanced manufacturing systems
Djuric, A. M., Urbanic, R., and Rickli, J. (2016) · 2016
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what scientific term or concept ought to be more widely known??
Dawkins, R. (2017) · 2017
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Learning modular neural network policies for multi-task and multi-robot transfer
Devin, C., Gupta, A., Darrell, T., Abbeel, P., and Levine, S. (2017) · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I. (2017) · 2017
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Visual question answering: A survey of methods and datasets
Wu, Q., Teney, D., Wang, P., Shen, C., Dick, A., and Van Den Hengel, A. (2017) · 2017
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The multimodal speech and visual gesture (msvg) control model for a practical patrol, search, and rescue aerobot
Abioye, A. O., Prior, S. D., Thomas, G. T., Saddington, P., and Ramchurn, S. D. (2018) · 2018
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Working with walt: How a cobot was developed and inserted on an auto assembly line
El Makrini, I., Elprama, S. A., Van den Bergh, J., Vanderborght, B., Knevels, A.-J., Jewell, C. I., Stals, F., De Coppel, G., Ravyse, I., Potargent, J., et al. (2018) · 2018
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Explain yourself: A natural language interface for scrutable autonomous robots
Garcia, F. J. C., Robb, D. A., Liu, X., Laskov, A., Patron, P., and Hastie, H. (2018) · 2018
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Behavior explanation as intention signaling in human-robot teaming
Gong, Z. and Zhang, Y. (2018) · 2018
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Irving, G., Christiano, P., and Amodei, D. (2018) · 2018
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The role of trust in human-robot interaction
Lewis, M., Sycara, K., and Walker, P. (2018) · 2018
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Facilitators and barriers to ad hoc team performance
White, B. A. A., Eklund, A., McNeal, T., Hochhalter, A., and Arroliga, A. C. (2018) · 2018
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Human-cobot teams: Exploring design principles and behaviour models to facilitate the understanding of non-verbal communication from cobots
Bergman, M., de Joode, E., de Geus, M., and Sturm, J. (2019) · 2019
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Cobot programming for collaborative industrial tasks: An overview
El Zaatari, S., Marei, M., Li, W., and Usman, Z. (2019) · 2019
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Explainability in human–agent systems
Rosenfeld, A. and Richardson, A. (2019) · 2019
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Videobert: A joint model for video and language representation learning
Sun, C., Myers, A., Vondrick, C., Murphy, K., and Schmid, C. (2019) · 2019
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The mit humanoid robot: Design, motion planning, and control for acrobatic behaviors
Chignoli, M., Kim, D., Stanger-Jones, E., and Kim, S. (2021) · 2020
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Wiki-40b: Multilingual language model dataset
Guo, M., Dai, Z., Vrandečić, D., and Al-Rfou, R. (2020) · 2020
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Intelligence without representation: a historical perspective
Jordanous, A. (2020) · 2020
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A penny for your thoughts: The value of communication in ad hoc teamwork
Mirsky, R., Macke, W., Wang, A., Yedidsion, H., and Stone, P. (2020) · 2020
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Explainable robotics in human-robot interactions
Setchi, R., Dehkordi, M. B., and Khan, J. S. (2020) · 2020
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Jointly improving parsing and perception for natural language commands through human-robot dialog
Thomason, J., Padmakumar, A., Sinapov, J., Walker, N., Jiang, Y., Yedidsion, H., Hart, J., Stone, P., and Mooney, R. (2020) · 2020
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The robotslang benchmark: Dialog-guided robot localization and navigation
Banerjee, S., Thomason, J., and Corso, J. (2021) · 2021
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Explainable ai for robot failures: Generating explanations that improve user assistance in fault recovery
Das, D., Banerjee, S., and Chernova, S. (2021) · 2021
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Bottom-up and top-down neural processing systems design: Neuromorphic intelligence as the convergence of natural and artificial intelligence
Frenkel, C. P., Bol, D., and Indiveri, G. (2021) · 2021
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The need for verbal robot explanations and how people would like a robot to explain itself
Han, Z., Phillips, E., and Yanco, H. A. (2021) · 2021
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Lora: Low-rank adaptation of large language models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W. (2021) · 2021
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Programming cobots by voice: A human-centered, web-based approach
Ionescu, T. B. and Schlund, S. (2021) · 2021
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Lifelong learning and personalization in long-term human-robot interaction (leap-hri)
Irfan, B., Ramachandran, A., Spaulding, S., Kalkan, S., Parisi, G. I., and Gunes, H. (2021) · 2021
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Multilingual lama: Investigating knowledge in multilingual pretrained language models
Kassner, N., Dufter, P., and Schütze, H. (2021) · 2021
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A lifelong learning approach to mobile robot navigation
Liu, B., Xiao, X., and Stone, P. (2021) · 2021
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Zero-shot text-to-image generation
Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., and Sutskever, I. (2021) · 2021
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Bot-adversarial dialogue for safe conversational agents
Xu, J., Ju, D., Li, M., Boureau, Y.-L., Weston, J., and Dinan, E. (2021) · 2021
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Building a role specified open-domain dialogue system leveraging large-scale language models
Bae, S., Kwak, D., Kim, S., Ham, D., Kang, S., Lee, S.-W., and Park, W. (2022) · 2022
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Rt-1: Robotics transformer for real-world control at scale
Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Dabis, J., Finn, C., Gopalakrishnan, K., Hausman, K., Herzog, A., Hsu, J., et al. (2022) · 2022
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Asking follow-up clarifications to resolve ambiguities in human-robot conversation
Doğan, F. I., Torre, I., and Leite, I. (2022) · 2022
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Lila: Language-informed latent actions
Karamcheti, S., Srivastava, M., Liang, P., and Sadigh, D. (2022) · 2022
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How linguistic framing affects factory workers’ initial trust in collaborative robots: the interplay between anthropomorphism and technological replacement
Kopp, T., Baumgartner, M., and Kinkel, S. (2022) · 2022
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Rethinking explainability as a dialogue: A practitioner’s perspective
Lakkaraju, H., Slack, D., Chen, Y., Tan, C., and Singh, S. (2022) · 2022
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A path towards autonomous machine intelligence version 0.9. 2, 2022-06-27
LeCun, Y. (2022) · 2022
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Impact of cobots on automation
Lefranc, G., Lopez-Juarez, I., Osorio-Comparán, R., and Peña-Cabrera, M. (2022) · 2022
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Transformer adapters for robot learning
Liang, A., Singh, I., Pertsch, K., and Thomason, J. (2022) · 2022
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Learning language-conditioned robot behavior from offline data and crowd-sourced annotation
Nair, S., Mitchell, E., Chen, K., Savarese, S., Finn, C., et al. (2022) · 2022
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Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al. (2022) · 2022
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Planning with large language models via corrective re-prompting
Raman, S. S., Cohen, V., Rosen, E., Idrees, I., Paulius, D., and Tellex, S. (2022) · 2022
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Reed, S., Zolna, K., Parisotto, E., Colmenarejo, S. G., Novikov, A., Barth-Maron, G., Gimenez, M., Sulsky, Y., Kay, J., Springenberg, J. T., et al. (2022) · 2022
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Non-dyadic interaction: A literature review of 15 years of human-robot interaction conference publications
Schneiders, E., Cheon, E., Kjeldskov, J., Rehm, M., and Skov, M. B. (2022) · 2022
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Pddl planning with pretrained large language models
Silver, T., Hariprasad, V., Shuttleworth, R. S., Kumar, N., Lozano-Pérez, T., and Kaelbling, L. P. (2022) · 2022
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Lamda: Language models for dialog applications
Thoppilan, R., De Freitas, D., Hall, J., Shazeer, N., Kulshreshtha, A., Cheng, H.-T., Jin, A., Bos, T., Baker, L., Du, Y., et al. (2022) · 2022
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Self-instruct: Aligning language models with self-generated instructions
Wang, Y., Kordi, Y., Mishra, S., Liu, A., Smith, N. A., Khashabi, D., and Hajishirzi, H. (2022) · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q. V., Zhou, D., et al. (2022) · 2022
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A systematic evaluation of large language models of code
Xu, F. F., Alon, U., Neubig, G., and Hellendoorn, V. J. (2022) · 2022
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Socratic models: Composing zero-shot multimodal reasoning with language
Zeng, A., Attarian, M., Ichter, B., Choromanski, K., Wong, A., Welker, S., Tombari, F., Purohit, A., Ryoo, M., Sindhwani, V., et al. (2022) · 2022
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Jarvis: A neuro-symbolic commonsense reasoning framework for conversational embodied agents
Zheng, K., Zhou, K., Gu, J., Fan, Y., Wang, J., Di, Z., He, X., and Wang, X. E. (2022) · 2022
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On specifying for trustworthiness
Abeywickrama, D. B., Bennaceur, A., Chance, G., Demiris, Y., Kordoni, A., Levine, M., Moffat, L., Moreau, L., Mousavi, M. R., Nuseibeh, B., et al. (2023) · 2023
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Large language models and intelligence analysis
Adam, C. and Carter, R. (2023) · 2023
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Saytap: Language to quadrupedal locomotion
Tang, Y., Yu, W., Tan, J., Zen, H., Faust, A., and Harada, T. (2023) · 2023
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Lingo-1: Exploring natural language for autonomous driving
Wayve (2023) · 2023
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Dilu: A knowledge-driven approach to autonomous driving with large language models
Wen, L., Fu, D., Li, X., Cai, X., Ma, T., Cai, P., Dou, M., Shi, B., He, L., and Qiao, Y. (2023) · 2023
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Reasoning about the unseen for efficient outdoor object navigation
Xie, Q., Zhang, T., Xu, K., Johnson-Roberson, M., and Bisk, Y. (2023) · 2023
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Retroformer: Retrospective large language agents with policy gradient optimization
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Incremental learning of humanoid robot behavior from natural interaction and large language models
Bärmann, L., Kartmann, R., Peller-Konrad, F., Waibel, A., and Asfour, T. (2023) · 2023
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Graph of thoughts: Solving elaborate problems with large language models
Besta, M., Blach, N., Kubicek, A., Gerstenberger, R., Gianinazzi, L., Gajda, J., Lehmann, T., Podstawski, M., Niewiadomski, H., Nyczyk, P., et al. (2023) · 2023
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Bianchi, F., Suzgun, M., Attanasio, G., Röttger, P., Jurafsky, D., Hashimoto, T., and Zou, J. (2023) · 2023
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Embodied agents for efficient exploration and smart scene description
Bigazzi, R., Cornia, M., Cascianelli, S., Baraldi, L., and Cucchiara, R. (2023) · 2023
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Meta-reinforcement learning via language instructions
Bing, Z., Koch, A., Yao, X., Huang, K., and Knoll, A. (2023) · 2023
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Language, common sense, and the winograd schema challenge
Browning, J. and LeCun, Y. (2023) · 2023
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Latte: Language trajectory transformer
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Yao, W., Heinecke, S., Niebles, J. C., Liu, Z., Feng, Y., Xue, L., Murthy, R., Chen, Z., Zhang, J., Arpit, D., et al. (2023) · 2023
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Reasoning about responsibility in autonomous systems: challenges and opportunities
Yazdanpanah, V., Gerding, E. H., Stein, S., Dastani, M., Jonker, C. M., Norman, T. J., and Ramchurn, S. D. (2023) · 2023
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Selfee: Iterative self-revising llm empowered by self-feedback generation
Ye, S., Jo, Y., Kim, D., Kim, S., Hwang, H., and Seo, M. (2023) · 2023
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Statler: State-maintaining language models for embodied reasoning
Yoneda, T., Fang, J., Li, P., Zhang, H., Jiang, T., Lin, S., Picker, B., Yunis, D., Mei, H., and Walter, M. R. (2023) · 2023
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Large language models for chemistry robotics
Yoshikawa, N., Skreta, M., Darvish, K., Arellano-Rubach, S., Ji, Z., Bjørn Kristensen, L., Li, A. Z., Zhao, Y., Xu, H., Kuramshin, A., et al. (2023) · 2023
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Large language models for robotics: A survey
Zeng, F., Gan, W., Wang, Y., Liu, N., and Yu, P. S. (2023) · 2023
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Bridging intelligence and instinct: A new control paradigm for autonomous robots
Zhang, S. and Lu, Q. (2023) · 2023
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Analyzing and mitigating object hallucination in large vision-language models
Zhou, Y., Cui, C., Yoon, J., Zhang, L., Deng, Z., Finn, C., Bansal, M., and Yao, H. (2023) · 2023
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Zhu, X., Chen, Y., Tian, H., Tao, C., Su, W., Yang, C., Huang, G., Li, B., Lu, L., Wang, X., et al. (2023) · 2023
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Autort: Embodied foundation models for large scale orchestration of robotic agents
Ahn, M., Dwibedi, D., Finn, C., Arenas, M. G., Gopalakrishnan, K., Hausman, K., Ichter, B., Irpan, A., Joshi, N., Julian, R., et al. (2024) · 2024
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Grounding llms for robot task planning using closed-loop state feedback
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Model parallelism on distributed infrastructure: A literature review from theory to llm case-studies
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Video generation models as world simulators
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(security) assertions by large language models
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Pretrained visual uncertainties
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Uncertainty decomposition and quantification for in-context learning of large language models
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Large language models: A survey
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Evolutionary reward design and optimization with multimodal large language models
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