Fetching the paper…
Reading the bibliography…
Large language models (LLMs) exhibit a wide range of promising capabilities -- from step-by-step planning to commonsense reasoning -- that may provide utility for robots, but remain prone to confidently hallucinated predictions.
Algorithmic Learning in a Random World , volume 29
V. Vovk, A. Gammerman, and G. Shafer · 2005
Earlier work this paper cites.
Conditional validity of inductive conformal predictors
V. Vovk · 2012
Earlier work this paper cites.
The winograd schema challenge
H. Levesque, E. Davis, and L. Morgenstern · 2012
Earlier work this paper cites.
Polylabel: a fast algorithm for finding the pole of inaccessibility of a polygon, July 2016
V. Agafonkin · 2016
Earlier work this paper cites.
On calibration of modern neural networks
C. Guo, G. Pleiss, Y. Sun, and K. Q. Weinberger · 2017
Earlier work this paper cites.
Active preference-based learning of reward functions
D. Sadigh, A. D. Dragan, S. S. Sastry, and S. A. Seshia · 2017
Earlier work this paper cites.
Correcting length bias in neural machine translation
K. Murray and D. Chiang · 2018
Earlier work this paper cites.
Least ambiguous set-valued classifiers with bounded error levels
M. Sadinle, J. Lei, and L. Wasserman · 2019
Earlier work this paper cites.
Quantifying uncertainties in natural language processing tasks
Y. Xiao and W. Y. Wang · 2019
Earlier work this paper cites.
Measuring massive multitask language understanding
D. Hendrycks, C. Burns, S. Basart, A. Zou, M. Mazeika, D. Song, and J. Steinhardt · 2020
Earlier work this paper cites.
Uncertainty sets for image classifiers using conformal prediction
A. Angelopoulos, S. Bates, J. Malik, and M. I. Jordan · 2020
Earlier work this paper cites.
Vision-and-dialog navigation
J. Thomason, M. Murray, M. Cakmak, and L. Zettlemoyer · 2020
Earlier work this paper cites.
Better-than-demonstrator imitation learning via automatically-ranked demonstrations
D. S. Brown, W. Goo, and S. Niekum · 2020
Earlier work this paper cites.
How can we know when language models know? on the calibration of language models for question answering
Z. Jiang, J. Araki, H. Ding, and G. Neubig · 2021
Earlier work this paper cites.
Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity
Y. Lu, M. Bartolo, A. Moore, S. Riedel, and P. Stenetorp · 2021
Earlier work this paper cites.
Consistent accelerated inference via confident adaptive transformers
T. Schuster, A. Fisch, T. Jaakkola, and R. Barzilay · 2021
Earlier work this paper cites.
Transformer-based conformal predictors for paraphrase detection
P. Giovannotti and A. Gammerman · 2021
Earlier work this paper cites.
The robotslang benchmark: Dialog-guided robot localization and navigation
S. Banerjee, J. Thomason, and J. Corso · 2021
Earlier work this paper cites.
MDETR-modulated detection for end-to-end multi-modal understanding
A. Kamath, M. Singh, Y. LeCun, G. Synnaeve, I. Misra, and N. Carion · 2021
Earlier work this paper cites.
Do as I can, not as I say: Grounding language in robotic affordances
M. Ahn, A. Brohan, N. Brown, Y. Chebotar, O. Cortes, B. David, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog, et al · 2022
Earlier work this paper cites.
Inner monologue: Embodied reasoning through planning with language models
W. Huang, F. Xia, T. Xiao, H. Chan, J. Liang, P. Florence, A. Zeng, J. Tompson, I. Mordatch, Y. Chebotar, P. Sermanet, T. Jackson, N. Brown, L. Luu, S. Levine, K. Hausman, and B. Ichter · 2022
Earlier work this paper cites.
Code as policies: Language model programs for embodied control
J. Liang, W. Huang, F. Xia, P. Xu, K. Hausman, B. Ichter, P. Florence, and A. Zeng · 2022
Earlier work this paper cites.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A. Srivastava, A. Rastogi, A. Rao, A. A. M. Shoeb, A. Abid, A. Fisch, A. R. Brown, A. Santoro, A. Gupta, A. Garriga-Alonso, et al · 2022
Cited alongside, same era.
Efficient and differentiable conformal prediction with general function classes
Y. Bai, S. Mei, H. Wang, Y. Zhou, and C. Xiong · 2022
Cited alongside, same era.
Pybullet, a python module for physics simulation for games, robotics and machine learning
E. Coumans and Y. Bai · 2022
Cited alongside, same era.
Chain of thought prompting elicits reasoning in large language models
J. Wei, X. Wang, D. Schuurmans, M. Bosma, B. Ichter, F. Xia, E. Chi, Q. Le, and D. Zhou · 2022
Cited alongside, same era.
Simple open-vocabulary object detection with vision transformers
M. Minderer, A. Gritsenko, A. Stone, M. Neumann, D. Weissenborn, A. Dosovitskiy, A. Mahendran, A. Arnab, M. Dehghani, Z. Shen, et al · 2022
Later among the works it cites.
Optimizing trajectories with closed-loop dynamic SQP
S. Singh, J.-J. Slotine, and V. Sindhwani · 2022
Later among the works it cites.
RT-1: Robotics transformer for real-world control at scale
A. Brohan, N. Brown, J. Carbajal, Y. Chebotar, J. Dabis, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog, J. Hsu, et al · 2022
Later among the works it cites.
Conformal prediction: A gentle introduction
A. N. Angelopoulos, S. Bates, et al · 2023
Closest in time.
PaLM 2 technical report, 2023
Google · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
T. Kojima, S. S. Gu, M. Reid, Y. Matsuo, and Y. Iwasawa · 2022
Cited alongside, same era.
Challenging big-bench tasks and whether chain-of-thought can solve them
M. Suzgun, N. Scales, N. Schärli, S. Gehrmann, Y. Tay, H. W. Chung, A. Chowdhery, Q. V. Le, E. H. Chi, D. Zhou, et al · 2022
Cited alongside, same era.
Solving quantitative reasoning problems with language models
A. Lewkowycz, A. Andreassen, D. Dohan, E. Dyer, H. Michalewski, V. Ramasesh, A. Slone, C. Anil, I. Schlag, T. Gutman-Solo, et al · 2022
Cited alongside, same era.
Mind’s eye: Grounded language model reasoning through simulation
R. Liu, J. Wei, S. S. Gu, T.-Y. Wu, S. Vosoughi, C. Cui, D. Zhou, and A. M. Dai · 2022
Cited alongside, same era.
Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
W. Huang, P. Abbeel, D. Pathak, and I. Mordatch · 2022
Cited alongside, same era.
Socratic models: Composing zero-shot multimodal reasoning with language
A. Zeng, M. Attarian, B. Ichter, K. Choromanski, A. Wong, S. Welker, F. Tombari, A. Purohit, M. Ryoo, V. Sindhwani, J. Lee, V. Vanhoucke, and P. Florence · 2022
Cited alongside, same era.
Progprompt: Generating situated robot task plans using large language models
I. Singh, V. Blukis, A. Mousavian, A. Goyal, D. Xu, J. Tremblay, D. Fox, J. Thomason, and A. Garg · 2022
Cited alongside, same era.
Uncertainty quantification with pre-trained language models: A large-scale empirical analysis
Y. Xiao, P. P. Liang, U. Bhatt, W. Neiswanger, R. Salakhutdinov, and L.-P. Morency · 2022
Cited alongside, same era.
Selection-inference: Exploiting large language models for interpretable logical reasoning
A. Creswell, M. Shanahan, and I. Higgins · 2023
Closest in time.
Leveraging language for accelerated learning of tool manipulation
A. Z. Ren, B. Govil, T.-Y. Yang, K. R. Narasimhan, and A. Majumdar · 2023
Closest in time.
Translating natural language to planning goals with large-language models
Y. Xie, C. Yu, T. Zhu, J. Bai, Z. Gong, and H. Soh · 2023
Closest in time.
Task and motion planning with large language models for object rearrangement
Y. Ding, X. Zhang, C. Paxton, and S. Zhang · 2023
Closest in time.
LLM+P: Empowering large language models with optimal planning proficiency
B. Liu, Y. Jiang, X. Zhang, Q. Liu, S. Zhang, J. Biswas, and P. Stone · 2023
Closest in time.
Tidybot: Personalized robot assistance with large language models
J. Wu, R. Antonova, A. Kan, M. Lepert, A. Zeng, S. Song, J. Bohg, S. Rusinkiewicz, and T. Funkhouser · 2023
Closest in time.
Parsel: A (de-) compositional framework for algorithmic reasoning with language models
E. Zelikman, Q. Huang, G. Poesia, N. D. Goodman, and N. Haber · 2023
Closest in time.
Clara: Classifying and disambiguating user commands for reliable interactive robotic agents
J. Park, S. Lim, J. Lee, S. Park, Y. Yu, and S. Choi · 2023
Closest in time.
Navigating the grey area: Expressions of overconfidence and uncertainty in language models
K. Zhou, D. Jurafsky, and T. Hashimoto · 2023
Closest in time.
L. Kuhn, Y. Gal, and S. Farquhar · 2023
Closest in time.
V. Quach, A. Fisch, T. Schuster, A. Yala, J. H. Sohn, T. S. Jaakkola, and R. Barzilay · 2023
Closest in time.
Conformal prediction with large language models for multi-choice question answering
B. Kumar, C. Lu, G. Gupta, A. Palepu, D. Bellamy, R. Raskar, and A. Beam · 2023
Closest in time.
Sample-efficient safety assurances using conformal prediction
R. Luo, S. Zhao, J. Kuck, B. Ivanovic, S. Savarese, E. Schmerling, and M. Pavone · 2023
Closest in time.
Conformal prediction for STL runtime verification
L. Lindemann, X. Qin, J. V. Deshmukh, and G. J. Pappas · 2023
Closest in time.
Active reward learning from online preferences
V. Myers, E. Biyik, and D. Sadigh · 2023
Closest in time.
A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo, P. Dollár, and R. Girshick · 2023
Closest in time.