Advances in Transformers for Robotic Applications: A Review | Paper Citation Record

Observation 8c6f4bc0-50ee-42ab-8424-3741baae81ad · outbound

This paper cites Generating out-of-distribution scenarios using language models, 2024.

Advances in Transformers for Robotic Applications: A Review Generating out-of-distribution scenarios using language models, 2024

Reference 1

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Observation 69c9ab1d-4e31-4a81-88ba-06114a35a910 · outbound

This paper cites Constrained policy opti- mization, 2017.

Advances in Transformers for Robotic Applications: A Review Constrained policy opti- mization, 2017

Reference 2

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

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This paper cites Lstm inefficiency in long-term dependencies regression problems.

Advances in Transformers for Robotic Applications: A Review Lstm inefficiency in long-term dependencies regression problems

Reference 4

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This paper cites Advances in medical im- age analysis with vision transformers: A comprehensive review.

Advances in Transformers for Robotic Applications: A Review Advances in medical im- age analysis with vision transformers: A comprehensive review

Reference 5

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This paper cites The option-critic architecture, 2016.

Advances in Transformers for Robotic Applications: A Review The option-critic architecture, 2016

Reference 6

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This paper cites data2vec: A general framework for self-supervised learning in speech, vision and language, 2022.

Advances in Transformers for Robotic Applications: A Review data2vec: A general framework for self-supervised learning in speech, vision and language, 2022

Reference 7

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This paper cites Peters, and Arman Cohan.

Advances in Transformers for Robotic Applications: A Review Peters, and Arman Cohan

Reference 8

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Observation 6737f4ec-5eaf-42c0-a5d3-b7fb534961a2 · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

Advances in Transformers for Robotic Applications: A Review $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 9

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 10

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Observation 3858ac6d-e01e-48a4-b17e-dfa30ca60a2c · outbound

This paper cites Rt-2: Vision-language-action models transfer web knowledge to robotic control, 2023.

Advances in Transformers for Robotic Applications: A Review Rt-2: Vision-language-action models transfer web knowledge to robotic control, 2023

Reference 11

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This paper cites Rt-1: Robotics transformer for real-world control at scale, 2023.

Advances in Transformers for Robotic Applications: A Review Rt-1: Robotics transformer for real-world control at scale, 2023

Reference 12

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This paper cites Lewis, and Satinder Singh.

Advances in Transformers for Robotic Applications: A Review Lewis, and Satinder Singh

Reference 13

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 14

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Observation f425ce39-b950-4907-98d2-19e3c4ec5abe · outbound

This paper cites Plancritic: Formal planning with human feedback, 2024.

Advances in Transformers for Robotic Applications: A Review Plancritic: Formal planning with human feedback, 2024

Reference 15

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Observation 2a77b0ed-6211-47dd-9b35-06dfcb3b2733 · outbound

This paper cites Radfar, Athanasios Mouchtaris, Brian King, and Siegfried Kun- zmann.

Advances in Transformers for Robotic Applications: A Review Radfar, Athanasios Mouchtaris, Brian King, and Siegfried Kun- zmann

Reference 16

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Observation 3310df78-b4d2-4b84-88a3-829cbb45e715 · outbound

This paper cites Decision transformer: Reinforcement learning via sequence modeling, 2021.

Advances in Transformers for Robotic Applications: A Review Decision transformer: Reinforcement learning via sequence modeling, 2021

Reference 17

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This paper cites Clip2scene: Towards label-efficient 3d scene understanding by clip, 2023.

Advances in Transformers for Robotic Applications: A Review Clip2scene: Towards label-efficient 3d scene understanding by clip, 2023

Reference 18

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Observation 54e8c06f-19e2-4ebd-8a13-d88f7bf281c8 · outbound

This paper cites Generating long sequences with sparse transformers, 2019.

Advances in Transformers for Robotic Applications: A Review Generating long sequences with sparse transformers, 2019

Reference 19

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Observation 6aaac785-45df-4ca9-8676-72c8da0f4c4b · outbound

This paper cites Rethinking attention with performers, 2022.

Advances in Transformers for Robotic Applications: A Review Rethinking attention with performers, 2022

Reference 20

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 21

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Observation b46ababb-3141-4c3c-946a-71d1b7ba56db · outbound

This paper cites Instructblip: Towards general-purpose vision-language models with instruction tuning, 2023.

Advances in Transformers for Robotic Applications: A Review Instructblip: Towards general-purpose vision-language models with instruction tuning, 2023

Reference 22

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Observation d2a0898f-a33e-47f8-aa84-1485ba3bab4e · outbound

This paper cites Le, and Ruslan 17 Salakhutdinov.

Advances in Transformers for Robotic Applications: A Review Le, and Ruslan 17 Salakhutdinov

Reference 23

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Observation 437541b8-afce-4ff6-aa2c-0207d98f3d8f · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher R´ e.

Advances in Transformers for Robotic Applications: A Review Fu, Stefano Ermon, Atri Rudra, and Christopher R´ e

Reference 24

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Observation 95083fe9-3a01-456c-8ee2-2ff1c1df0d3d · outbound

This paper cites Universal transformers, 2019.

Advances in Transformers for Robotic Applications: A Review Universal transformers, 2019

Reference 25

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This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Advances in Transformers for Robotic Applications: A Review Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 26

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This paper cites DiPietro and Gregory Hager.

Advances in Transformers for Robotic Applications: A Review DiPietro and Gregory Hager

Reference 27

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This paper cites Scaling cross- embodied learning: One policy for manipulation, navigation, locomotion and aviation, 2024.

Advances in Transformers for Robotic Applications: A Review Scaling cross- embodied learning: One policy for manipulation, navigation, locomotion and aviation, 2024

Reference 28

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale, 2021.

Advances in Transformers for Robotic Applications: A Review An image is worth 16x16 words: Transformers for image recognition at scale, 2021

Reference 29

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This paper cites Addressing some limitations of transformers with feedback memory, 2021.

Advances in Transformers for Robotic Applications: A Review Addressing some limitations of transformers with feedback memory, 2021

Reference 30

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Observation 5835b735-987d-4e7b-8eea-102fd1b6a687 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks, 2017.

Advances in Transformers for Robotic Applications: A Review Model-agnostic meta-learning for fast adaptation of deep networks, 2017

Reference 31

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Observation 50197225-7da3-4b2b-98eb-59c3db3b8fd2 · outbound

This paper cites Foundation models in robotics: Ap- plications, challenges, and the future.

Advances in Transformers for Robotic Applications: A Review Foundation models in robotics: Ap- plications, challenges, and the future

Reference 32

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 33

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This paper cites Generalized decision transformer for offline hindsight information matching, 2022.

Advances in Transformers for Robotic Applications: A Review Generalized decision transformer for offline hindsight information matching, 2022

Reference 34

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This paper cites Physically grounded vision-language models for robotic ma- nipulation, 2024.

Advances in Transformers for Robotic Applications: A Review Physically grounded vision-language models for robotic ma- nipulation, 2024

Reference 35

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This paper cites Learning in reality: A case study of stanley, the robot that won the darpa challenge.

Advances in Transformers for Robotic Applications: A Review Learning in reality: A case study of stanley, the robot that won the darpa challenge

Reference 36

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Advances in Transformers for Robotic Applications: A Review RVT: Robotic View Transformer for 3D Object Manipulation

Reference 37

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Advances in Transformers for Robotic Applications: A Review Metamorph: Learning universal controllers with transformers, 2022

Reference 38

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This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor, 2018.

Advances in Transformers for Robotic Applications: A Review Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor, 2018

Reference 39

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This paper cites Transformers in Medical Image Analysis: A Review.

Advances in Transformers for Robotic Applications: A Review Transformers in Medical Image Analysis: A Review

Reference 40

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Advances in Transformers for Robotic Applications: A Review Vision Transformers in Medical Imaging: A Review

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This paper cites Convolutional vision transformer as a path following controller for omnidirectional robots.

Advances in Transformers for Robotic Applications: A Review Convolutional vision transformer as a path following controller for omnidirectional robots

Reference 42

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This paper cites Long short-term memory.Neural Computation, 9:1735–1780, 1997.

Advances in Transformers for Robotic Applications: A Review Long short-term memory.Neural Computation, 9:1735–1780, 1997

Reference 43

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Advances in Transformers for Robotic Applications: A Review On transforming re- inforcement learning with transformers: The development trajectory

Reference 44

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Advances in Transformers for Robotic Applications: A Review Toward general-purpose robots via foundation models: A survey and meta-analysis, 2024

Reference 45

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This paper cites Language models as zero-shot planners: Extracting actionable knowledge for embodied agents, 2022.

Advances in Transformers for Robotic Applications: A Review Language models as zero-shot planners: Extracting actionable knowledge for embodied agents, 2022

Reference 46

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This paper cites Hpcneu- ronet: Advancing neuromorphic audio signal processing with transformer-enhanced spik- ing neural networks.

Advances in Transformers for Robotic Applications: A Review Hpcneu- ronet: Advancing neuromorphic audio signal processing with transformer-enhanced spik- ing neural networks

Reference 47

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This paper cites A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks.

Advances in Transformers for Robotic Applications: A Review A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks

Reference 48

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This paper cites Perceiver: General perception with iterative attention, 2021.

Advances in Transformers for Robotic Applications: A Review Perceiver: General perception with iterative attention, 2021

Reference 49

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Advances in Transformers for Robotic Applications: A Review Bc-z: Zero-shot task generalization with robotic imita- tion learning, 2022

Reference 50

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Advances in Transformers for Robotic Applications: A Review When to trust your model: Model-based policy optimization, 2021

Reference 51

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Advances in Transformers for Robotic Applications: A Review Offline reinforcement learning as one big sequence modeling problem

Reference 52

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Advances in Transformers for Robotic Applications: A Review Flair: Feeding via long-horizon acquisition of realistic dishes, 2024

Reference 53

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Advances in Transformers for Robotic Applications: A Review A survey of robot intelligence with large language models

Reference 54

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Advances in Transformers for Robotic Applications: A Review Le, Yunhsuan Sung, Zhen Li, and Tom Duerig

Reference 55

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Advances in Transformers for Robotic Applications: A Review Highly accurate protein structure prediction with alphafold

Reference 56

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This paper cites Trans- formers are rnns: Fast autoregressive transformers with linear attention, 2020.

Advances in Transformers for Robotic Applications: A Review Trans- formers are rnns: Fast autoregressive transformers with linear attention, 2020

Reference 57

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Advances in Transformers for Robotic Applications: A Review Segment anything in high quality, 2023

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This paper cites Real-world robot applications of foundation models: a review.

Advances in Transformers for Robotic Applications: A Review Real-world robot applications of foundation models: a review

Reference 59

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

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This paper cites What and when to explain? on-road evaluation of explanations in highly automated vehicles.

Advances in Transformers for Robotic Applications: A Review What and when to explain? on-road evaluation of explanations in highly automated vehicles

Reference 61

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Advances in Transformers for Robotic Applications: A Review Openvla: An open-source vision-language-action model, 2024

Reference 62

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Observation 65590f33-b7de-484f-9077-2274ef5259ff · outbound

This paper cites A survey on integration of large language models with intelligent robots.

Advances in Transformers for Robotic Applications: A Review A survey on integration of large language models with intelligent robots

Reference 63

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Observation 4dd86bd2-16d7-466d-b505-54394fbd8417 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Doll´ ar, and Ross Girshick.

Advances in Transformers for Robotic Applications: A Review Berg, Wan-Yen Lo, Piotr Doll´ ar, and Ross Girshick

Reference 64

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Observation b7c8b314-980e-4cae-8391-dfe108868cf0 · outbound

This paper cites Reformer: The efficient transformer, 2020.

Advances in Transformers for Robotic Applications: A Review Reformer: The efficient transformer, 2020

Reference 65

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Observation e32d1040-c44f-4578-84a2-9fac83b7ecd1 · outbound

This paper cites Reinforcement learning in robotics: A survey.

Advances in Transformers for Robotic Applications: A Review Reinforcement learning in robotics: A survey

Reference 66

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Observation ea68521c-ba06-4eb0-a1d7-86dbd11f050c · outbound

This paper cites Image augmentation is all you need: Regularizing deep reinforcement learning from pixels, 2021.

Advances in Transformers for Robotic Applications: A Review Image augmentation is all you need: Regularizing deep reinforcement learning from pixels, 2021

Reference 67

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Observation cc440378-6720-4137-9334-ea6694603d5d · outbound

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 68

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Observation 5f1e6f57-e3e6-4314-bafe-15316239d032 · outbound

This paper cites Conservative q-learning for offline reinforcement learning, 2020.

Advances in Transformers for Robotic Applications: A Review Conservative q-learning for offline reinforcement learning, 2020

Reference 69

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Observation dace7474-c442-4234-b060-769b6262f685 · outbound

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 70

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Observation ccbe1bd0-643f-4407-b131-eb894cefb871 · outbound

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Advances in Transformers for Robotic Applications: A Review Fnet: Mixing tokens with fourier transforms, 2022

Reference 71

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Observation b9d19e9f-1d8a-440f-adcc-3439213fe574 · outbound

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Advances in Transformers for Robotic Applications: A Review End-to-end training of deep visuomotor policies

Reference 72

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Observation 3787e8bf-ce5e-4d58-8af9-8cb48430e219 · outbound

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Advances in Transformers for Robotic Applications: A Review Landman, and S

Reference 73

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Observation 58166518-dc6e-456e-b7fb-fd9e7994db47 · outbound

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Advances in Transformers for Robotic Applications: A Review Visualbert: A simple and performant baseline for vision and language, 2019

Reference 74

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Observation 72c57650-defe-480f-a328-c5106f44c298 · outbound

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Advances in Transformers for Robotic Applications: A Review Grounded language-image pre-training, 2022

Reference 75

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Observation ec89855c-3002-412e-a282-ab39ae3ab9c1 · outbound

This paper cites Shapegrasp: Zero-shot task-oriented grasping with large language models through geometric decomposition, 2024.

Advances in Transformers for Robotic Applications: A Review Shapegrasp: Zero-shot task-oriented grasping with large language models through geometric decomposition, 2024

Reference 76

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Observation 574630ac-b98e-4b8a-bd9e-188a29dd4b99 · outbound

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Advances in Transformers for Robotic Applications: A Review A survey on transformers in reinforcement learning, 2023

Reference 77

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Observation eddf6977-9fa6-4a3c-a29e-06219d399c18 · outbound

This paper cites Oscar: Object-semantics aligned pre-training for vision-language tasks, 2020.

Advances in Transformers for Robotic Applications: A Review Oscar: Object-semantics aligned pre-training for vision-language tasks, 2020

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.049112Z

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Observation 3e33f286-184f-49b0-9049-4742bba19c72 · outbound

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Advances in Transformers for Robotic Applications: A Review Lillicrap, Jonathan J

Reference 79

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Observation 3c514e00-bd6e-4387-9f4b-fe17b92cbfe9 · outbound

This paper cites A survey of transformers.

Advances in Transformers for Robotic Applications: A Review A survey of transformers

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.059920Z

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Observation e14c4edc-1c41-41d8-ad47-485de727a9d2 · outbound

This paper cites Instruction-following agents with multimodal transformer, 2023.

Advances in Transformers for Robotic Applications: A Review Instruction-following agents with multimodal transformer, 2023

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.066302Z

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Observation 90fc2aa4-0727-4eac-b70a-b4484fa8ed7a · outbound

This paper cites Constrained decision transformer for offline safe reinforcement learning.

Advances in Transformers for Robotic Applications: A Review Constrained decision transformer for offline safe reinforcement learning

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.071990Z

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Observation 01e4af26-e26d-4a21-9652-7df82070617a · outbound

This paper cites Few-shot subgoal plan- ning with language models, 2022.

Advances in Transformers for Robotic Applications: A Review Few-shot subgoal plan- ning with language models, 2022

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.076621Z

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Observation 103eacd7-f094-42ce-a000-964473fdf683 · outbound

This paper cites Uncertainty-aware hybrid paradigm of nonlinear mpc and model- based rl for offroad navigation: Exploration of transformers in the predictive model.

Advances in Transformers for Robotic Applications: A Review Uncertainty-aware hybrid paradigm of nonlinear mpc and model- based rl for offroad navigation: Exploration of transformers in the predictive model

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.081761Z

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Unavailable: canonical work link unavailable.

Observation 6956afc8-a227-43b3-a4f4-38330a0a33e5 · outbound

This paper cites Multi- agent actor-critic for mixed cooperative-competitive environments, 2020.

Advances in Transformers for Robotic Applications: A Review Multi- agent actor-critic for mixed cooperative-competitive environments, 2020

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.087615Z

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Observation 20adec2e-6a83-47e3-a3f1-f00e74592de6 · outbound

This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks, 2019.

Advances in Transformers for Robotic Applications: A Review Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks, 2019

Reference 86

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Unavailable: canonical work link unavailable.

Observation 947886c1-95ed-4c09-8782-cc7bdbe5ac03 · outbound

This paper cites Mega: Moving average equipped gated attention, 2023.

Advances in Transformers for Robotic Applications: A Review Mega: Moving average equipped gated attention, 2023

Reference 87

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Unavailable: canonical work link unavailable.

Observation c77cfc62-adb1-4550-beef-8dbd6f4347a8 · outbound

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Advances in Transformers for Robotic Applications: A Review Transformers are Sample-Efficient World Models

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.103476Z

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Unavailable: canonical work link unavailable.

Observation e1cda4f7-60eb-45dd-8aa4-bb398062a4bd · outbound

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Advances in Transformers for Robotic Applications: A Review Human-level control through deep reinforcement learning

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.108885Z

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Unavailable: canonical work link unavailable.

Observation ed978f4b-a345-4b33-b5e8-7c653a03550b · outbound

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Advances in Transformers for Robotic Applications: A Review Integrating reinforcement learning with foundation models for autonomous robotics: Methods and perspectives, 2024

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.113817Z

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Observation aced0f37-ee74-4671-b05c-57783a540311 · outbound

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.120590Z

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Unavailable: canonical work link unavailable.

Observation f04305bd-cb7d-4d87-a8e5-e73142e93f88 · outbound

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Advances in Transformers for Robotic Applications: A Review Data-efficient hierarchical reinforcement learning, 2018

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.126417Z

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Observation 81f1d93b-077b-48af-b804-58ddd9f858cc · outbound

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.131528Z

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Unavailable: canonical work link unavailable.

Observation e8e87aa1-26d6-4924-95c7-23b22a5e1a82 · outbound

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Advances in Transformers for Robotic Applications: A Review Newman, Pranay Gupta, Kris Kitani, Yonatan Bisk, Henny Admoni, and Chris Paxton

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.136761Z

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Unavailable: canonical work link unavailable.

Observation 0788c0e7-825c-4942-a93e-27ad821f2e5b · outbound

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Advances in Transformers for Robotic Applications: A Review Policy invariance under reward transformations: Theory and application to reward shaping

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.141833Z

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Unavailable: canonical work link unavailable.

Observation 4a378527-fecd-490c-bdd2-38bc3797ebdf · outbound

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Advances in Transformers for Robotic Applications: A Review Unresolved cited work

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.146524Z

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Unavailable: canonical work link unavailable.

Observation be243340-24c8-4404-b93d-682a06eb2fae · outbound

This paper cites Deep explo- ration via bootstrapped dqn, 2016.

Advances in Transformers for Robotic Applications: A Review Deep explo- ration via bootstrapped dqn, 2016

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.151497Z

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Observation 15a98a9c-8f8b-4590-a403-3a37c004936d · outbound

This paper cites Voicepilot: Harnessing llms as speech interfaces for physically assistive robots.

Advances in Transformers for Robotic Applications: A Review Voicepilot: Harnessing llms as speech interfaces for physically assistive robots

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.156321Z

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Unavailable: canonical work link unavailable.

Observation d34ea9cd-ed45-435f-9e67-ace30beeebbf · outbound

This paper cites Lifelong robot learning with human assisted language planners, 2023.

Advances in Transformers for Robotic Applications: A Review Lifelong robot learning with human assisted language planners, 2023

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-11T15:50:38.161104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cb0d70f-3de1-4f58-bc57-3c5af6245730 · outbound

This paper cites Lifelong robot learning with human assisted language planners.

Advances in Transformers for Robotic Applications: A Review Lifelong robot learning with human assisted language planners

Reference 100

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Outbound references

Pith citing papers