ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI | Paper Citation Record

Observation 141927ee-73c4-4369-bbef-f41d36144431 · outbound

This paper cites A survey of embodied ai: From simulators to research tasks.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI A survey of embodied ai: From simulators to research tasks

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Observation 9c1edee8-2682-463f-a42f-df7bb3e171f7 · outbound

This paper cites A Survey on Robotics with Foundation Models: toward Embodied AI.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI A Survey on Robotics with Foundation Models: toward Embodied AI

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This paper cites RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation

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This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

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Observation 28cf012f-3d06-4319-b46c-5ef29d0e95ec · outbound

This paper cites Qwen3-VL Technical Report.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Qwen3-VL Technical Report

Reference 5

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Observation 5533c13a-09e7-414d-89d0-1ff840ab15ab · outbound

This paper cites Qwen3 Technical Report.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Qwen3 Technical Report

Reference 6

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This paper cites Gemini: A Family of Highly Capable Multimodal Models.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Gemini: A Family of Highly Capable Multimodal Models

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Observation bda8b1a1-daa3-4a73-9f9d-525f9dd8159b · outbound

This paper cites Qwen-RobotNav Technical Report: A Scalable Navigation Model Designed for an Agentic Navigation System.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Qwen-RobotNav Technical Report: A Scalable Navigation Model Designed for an Agentic Navigation System

Reference 8

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Observation 6ba5691b-b952-4833-bc33-a6304beed28a · outbound

This paper cites Embodied navigation foundation model.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Embodied navigation foundation model

Reference 9

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Observation 53966804-dddf-43d0-bed7-fdefd305dd56 · outbound

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

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 10

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Observation a9fa1942-49dc-429a-bcd5-2b4629eb556d · outbound

This paper cites World Action Models are Zero-shot Policies.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI World Action Models are Zero-shot Policies

Reference 11

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Observation 1c4aa590-11c8-4afe-b1f8-4c74f3172d39 · outbound

This paper cites RoboReward: General-purpose vision-language reward models for robotics.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RoboReward: General-purpose vision-language reward models for robotics

Reference 12

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Observation 59ebd359-cb5b-44bd-a2ae-eacdf6469054 · outbound

This paper cites Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons

Reference 13

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ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Unresolved cited work

Reference 14

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ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Unresolved cited work

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ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Unresolved cited work

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Observation a11f0199-c5a2-48cd-8264-5b744e947274 · outbound

This paper cites $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

Reference 17

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Observation d8024768-a443-4f5e-8af0-e68f88e5c6cd · outbound

This paper cites Interleave-vla: Enhancing robot manipulation with interleaved image-text instructions, 2025.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Interleave-vla: Enhancing robot manipulation with interleaved image-text instructions, 2025

Reference 18

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Observation 9b4a8d58-da77-4c2d-9b77-64e09f539bfa · outbound

This paper cites Do as i can, not as i say: Grounding language in robotic affordances.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Do as i can, not as i say: Grounding language in robotic affordances

Reference 19

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Observation f70ceaa5-d7ca-4acb-8659-72802253413f · outbound

This paper cites PaLM-E: An embodied multimodal language model.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI PaLM-E: An embodied multimodal language model

Reference 20

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Observation b058d83b-7b2b-4987-b783-11ed6293f832 · outbound

This paper cites Code as policies: Language model programs for embodied control.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Code as policies: Language model programs for embodied control

Reference 21

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Observation 648bb15a-ea49-4431-8936-94d9c26d43f5 · outbound

This paper cites Voxposer: Composable 3d value maps for robotic manipulation with language models.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Voxposer: Composable 3d value maps for robotic manipulation with language models

Reference 22

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Observation 2cc9a582-2bab-45f3-9454-e90d5452ef79 · outbound

This paper cites RoboCodeX: Multimodal code generation for robotic behavior synthesis.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RoboCodeX: Multimodal code generation for robotic behavior synthesis

Reference 23

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Observation 5e62c089-d830-47c1-8049-ff8edd7b22ab · outbound

This paper cites RoboAgent: Chaining Basic Capabilities for Embodied Task Planning.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RoboAgent: Chaining Basic Capabilities for Embodied Task Planning

Reference 24

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Observation 4a918928-a2f2-482a-b288-595ea9092593 · outbound

This paper cites GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 25

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Observation ada86e16-2b55-4088-a0a5-0fe7598a8668 · outbound

This paper cites Gr00t n1.5: An improved open foundation model for generalist humanoid robots.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Gr00t n1.5: An improved open foundation model for generalist humanoid robots

Reference 26

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Observation 9766699a-0bce-4b34-b608-09ec4ea3ec5a · outbound

This paper cites Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Reference 27

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Observation d342d7b5-fe9e-46dd-997f-5ec135fef29f · outbound

This paper cites Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation

Reference 28

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Observation 56ec2478-6d79-44df-9007-85ba28ba5160 · outbound

This paper cites ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning

Reference 29

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Observation 8bb52d65-6ea9-4646-81c9-beee96f73e00 · outbound

This paper cites Rynnbrain: Open embodied foundation models.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Rynnbrain: Open embodied foundation models

Reference 30

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Observation 2e3ebbcd-57e3-4dbe-8636-e49b96634871 · outbound

This paper cites Cosmos 3: Omnimodal World Models for Physical AI.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Cosmos 3: Omnimodal World Models for Physical AI

Reference 31

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Observation ff92efcc-6e25-4e7c-a4aa-2ecb99a70e42 · outbound

This paper cites Ace-brain-0: Spatial intelligence as a shared scaffold for universal embodiments.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Ace-brain-0: Spatial intelligence as a shared scaffold for universal embodiments

Reference 32

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Observation d107ad8e-e58f-4504-99cf-7b901ab047d2 · outbound

This paper cites Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action

Reference 33

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Observation 52869e84-c7ed-44fc-8db0-d9ee91b7629b · outbound

This paper cites HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents

Reference 34

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Observation 77f5b74a-e87a-4d66-98ab-3129af903266 · outbound

This paper cites ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

Reference 35

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Observation ceda9816-273d-4627-b6d5-b6722cf28e35 · outbound

This paper cites $\pi^{*}_{0.6}$: a VLA That Learns From Experience.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI $\pi^{*}_{0.6}$: a VLA That Learns From Experience

Reference 36

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Observation 40513af3-cfa8-4723-8f19-3c1572883530 · outbound

This paper cites Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models

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Observation 7093daec-0540-48bc-a710-2b00f05698e1 · outbound

This paper cites MolmoAct2: Action Reasoning Models for Real-world Deployment.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI MolmoAct2: Action Reasoning Models for Real-world Deployment

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Observation a1a78ed6-52c2-4e16-9127-fcb0dc4d66a5 · outbound

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ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Qwen-RobotManip Technical Report: Alignment Unlocks Scale for Robotic Manipulation Foundation Models

Reference 39

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Observation 5af40899-3c4d-49ba-83e9-a1d7e7a60108 · outbound

This paper cites Abot-n0: Technical report on the vla foundation model for versatile embodied navigation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Abot-n0: Technical report on the vla foundation model for versatile embodied navigation

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Observation faaff22f-dfa0-47c9-8ab1-15d592b83ca9 · outbound

This paper cites Gemini Robotics-ER 1.6: Powering real-world robotics tasks through enhanced em- bodied reasoning.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Gemini Robotics-ER 1.6: Powering real-world robotics tasks through enhanced em- bodied reasoning

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Observation fcf9ce38-f87e-4df2-a044-3f947ac31eaf · outbound

This paper cites Introducing helix 02: Full-body autonomy, 2026.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Introducing helix 02: Full-body autonomy, 2026

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Observation e8e959ef-3a8e-47aa-9716-2f0f78c9795c · outbound

This paper cites Model merging in llms, mllms, and beyond: Methods, theories, applications, and opportunities.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Model merging in llms, mllms, and beyond: Methods, theories, applications, and opportunities

Reference 43

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Observation c77a7c9f-8fed-43b9-914a-4b149fa1fc46 · outbound

This paper cites Qwen2.5-VL Technical Report.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Qwen2.5-VL Technical Report

Reference 44

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Observation c260d960-5da1-4142-80a2-d5343894d2a4 · outbound

This paper cites Improved baselines with visual instruction tuning.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Improved baselines with visual instruction tuning

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Observation f058b581-ad60-4015-b802-a7787c392e00 · outbound

This paper cites Gpt-4o system card.https://openai.com/index/gpt-4o-system-card/, 2025.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Gpt-4o system card.https://openai.com/index/gpt-4o-system-card/, 2025

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Observation c7c7f3ab-af64-4758-81aa-258786bb90f7 · outbound

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ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Claude sonnet 4

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Observation b8cdf4f8-057f-405f-a32c-8e1666e9c794 · outbound

This paper cites SpatialVLM: Endowing vision-language models with spatial reasoning capabilities.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI SpatialVLM: Endowing vision-language models with spatial reasoning capabilities

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Observation 151f5f20-ec80-4fa0-a285-f1b30583eee6 · outbound

This paper cites RoboPoint: A vision-language model for spatial affordance prediction for robotics.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RoboPoint: A vision-language model for spatial affordance prediction for robotics

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Observation 1932c905-de85-4bc3-bd57-fff28e24d2d1 · outbound

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ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RoboRefer: Towards spatial referring with reasoning in vision-language models for robotics

Reference 50

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Observation 74304a63-58e8-45f6-8b5c-011c187abc7a · outbound

This paper cites Robobrain: A unified brain model for robotic manipulation from abstract to concrete.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Robobrain: A unified brain model for robotic manipulation from abstract to concrete

Reference 51

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Observation ee474def-3ff1-4243-ac9b-1e9352afacc3 · outbound

This paper cites Robobrain 2.5: Depth in sight, time in mind.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Robobrain 2.5: Depth in sight, time in mind

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Observation ed0ca22f-7515-4283-99ad-b1a05dfdc1ec · outbound

This paper cites MiMo-Embodied: X-Embodied Foundation Model Technical Report.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI MiMo-Embodied: X-Embodied Foundation Model Technical Report

Reference 53

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Observation 5ca3a554-d397-484d-9748-597a412c8479 · outbound

This paper cites Visual Embodied Brain: Let Multimodal Large Language Models See, Think, and Control in Spaces.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Visual Embodied Brain: Let Multimodal Large Language Models See, Think, and Control in Spaces

Reference 54

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Observation eddaea49-160f-4f46-b2b9-b8d3487ef1b8 · outbound

This paper cites RoboBrain 2.0 Technical Report.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RoboBrain 2.0 Technical Report

Reference 55

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Observation d583d91a-6417-459d-9fa6-2ebbc8e914b1 · outbound

This paper cites Vlaser: Vision-language-action model with synergistic embodied reasoning.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Vlaser: Vision-language-action model with synergistic embodied reasoning

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Observation 54080e52-ce8c-4bf5-8b82-f3fd26ad96ca · outbound

This paper cites Pelican-vl 1.0: A foundation brain model for embodied intelligence.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Pelican-vl 1.0: A foundation brain model for embodied intelligence

Reference 57

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Observation 1e99e69a-0033-4827-92e4-02b8173ea7d9 · outbound

This paper cites RT-1: Robotics transformer for real-world control at scale.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RT-1: Robotics transformer for real-world control at scale

Reference 58

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Observation 04acb0ba-45d5-4c32-9959-c7cc41d7fe34 · outbound

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

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RT-2: Vision-language-action models transfer web knowledge to robotic control

Reference 59

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Observation 9f8adba5-4552-4e8f-ab10-8e7466f112e5 · outbound

This paper cites Octo: An open-source generalist robot policy.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Octo: An open-source generalist robot policy

Reference 60

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Observation 90fc8551-ae27-4c8b-9644-2bb77415fc4c · outbound

This paper cites OpenVLA: An open-source vision-language-action model.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI OpenVLA: An open-source vision-language-action model

Reference 61

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Observation 8ae275de-1280-41ce-b6aa-e200627afc7c · outbound

This paper cites Open X-Embodiment: Robotic learning datasets and RT-X models.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Open X-Embodiment: Robotic learning datasets and RT-X models

Reference 62

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Observation d418b3a4-033b-43db-bbc6-a9b3be2dc434 · outbound

This paper cites RT-H: Action Hierarchies Using Language.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RT-H: Action Hierarchies Using Language

Reference 63

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Observation 4a7f19e4-3639-49ab-bc9d-9727accbdbb9 · outbound

This paper cites Eo-1: Interleaved vision-text- action pretraining for general robot control.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Eo-1: Interleaved vision-text- action pretraining for general robot control

Reference 64

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Observation bd9eebd2-127e-4c50-a7ef-6a4a573ee6a4 · outbound

This paper cites CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation

Reference 65

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Observation 8f03d772-fc24-432a-adbe-9a25ee457fe9 · outbound

This paper cites GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation

Reference 66

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Observation 60b77533-9dca-4462-84ea-b589a9826d6f · outbound

This paper cites GR-3 Technical Report.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI GR-3 Technical Report

Reference 67

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Observation 64cc7f85-a32d-412a-8536-7999f23524a6 · outbound

This paper cites Gaze-Regularized Vision-Language-Action Models for Robotic Manipulation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Gaze-Regularized Vision-Language-Action Models for Robotic Manipulation

Reference 68

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Observation 00cda2d9-a497-42fa-bc7c-0f2268f891c9 · outbound

This paper cites Vla-jepa: Enhancing vision-language-action model with latent world model, 2026.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Vla-jepa: Enhancing vision-language-action model with latent world model, 2026

Reference 69

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Observation 28fb3364-9f6d-4b9c-bb42-b091c7ca314a · outbound

This paper cites Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Reference 70

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Observation e10d4955-22cc-4d6d-8715-a21740fe01b3 · outbound

This paper cites Gigaworld-policy: An efficient action-centered world–action model.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Gigaworld-policy: An efficient action-centered world–action model

Reference 71

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Observation 06d68dd9-aab4-4a75-ac01-3b64f32c5d02 · outbound

This paper cites Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

Reference 72

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Observation 7f27a67c-4155-423a-ad86-593274337c6b · outbound

This paper cites Fast-WAM: Do World Action Models Need Test-time Future Imagination?.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Fast-WAM: Do World Action Models Need Test-time Future Imagination?

Reference 73

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Observation dc0dd1f3-11d3-4dd1-a5cf-5e46182382d5 · outbound

This paper cites Dreamvla: a vision-language-action model dreamed with comprehensive world knowledge.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Dreamvla: a vision-language-action model dreamed with comprehensive world knowledge

Reference 74

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Observation 44eefec1-bbc7-475f-ba4b-1f4a4598dea3 · outbound

This paper cites Being-H0.7: A Latent World-Action Model from Egocentric Videos.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Being-H0.7: A Latent World-Action Model from Egocentric Videos

Reference 75

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Observation a247e9bc-0198-4fa9-bb9f-c4e5dc329c98 · outbound

This paper cites RynnVLA-002: A Unified Vision-Language-Action and World Model.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI RynnVLA-002: A Unified Vision-Language-Action and World Model

Reference 76

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Observation 17b0e8c8-93d0-4fd3-81e9-bb74d27b390a · outbound

This paper cites ABot-M0.5: Unified Mobility-and-Manipulation World Action Model.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI ABot-M0.5: Unified Mobility-and-Manipulation World Action Model

Reference 77

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Observation 864dbc8a-3285-493e-9047-ba9db8359042 · outbound

This paper cites Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments

Reference 78

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Observation 9afdb9af-1361-45b3-874b-699a4d12c1c2 · outbound

This paper cites Think global, act local: Dual-scale graph transformer for vision-and-language navigation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Think global, act local: Dual-scale graph transformer for vision-and-language navigation

Reference 79

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Observation 962e6fd2-29f4-4a41-83a8-5a31522491e1 · outbound

This paper cites Beyond the nav-graph: Vision- and-language navigation in continuous environments.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Beyond the nav-graph: Vision- and-language navigation in continuous environments

Reference 80

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Observation c34dd25f-b779-4a85-b762-077e359d9d4e · outbound

This paper cites Vision-and-language navigation with foundation models: A survey.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Vision-and-language navigation with foundation models: A survey

Reference 81

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Observation 3555cc1c-fdbb-4dee-bd49-a9e4733fe0df · outbound

This paper cites Navgpt: Explicit reasoning in vision-and-language navigation with large language models.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Navgpt: Explicit reasoning in vision-and-language navigation with large language models

Reference 82

Resolution: unresolved; no resolver link, observed 2026-07-11T19:16:57.396710Z

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Observation 96c27ba5-01f0-46d9-8c3d-54894c5a31b1 · outbound

This paper cites NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation

Reference 83

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Observation 60e3694c-c7e2-4522-8943-3ba9f774cccf · outbound

This paper cites NaVILA: Legged Robot Vision-Language-Action Model for Navigation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI NaVILA: Legged Robot Vision-Language-Action Model for Navigation

Reference 84

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Observation 761b0e6b-5041-4c56-a8a9-cded259122ca · outbound

This paper cites Uni-NaVid: A Video-based Vision-Language-Action Model for Unifying Embodied Navigation Tasks.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Uni-NaVid: A Video-based Vision-Language-Action Model for Unifying Embodied Navigation Tasks

Reference 85

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Observation eb84062f-aa1c-4a85-998a-0afa452ba9d4 · outbound

This paper cites StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling

Reference 86

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Observation 3dd353ec-0325-4b1e-a3be-8dbbf91a841d · outbound

This paper cites Octonav: Towards generalist embodied navigation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Octonav: Towards generalist embodied navigation

Reference 87

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Observation 4b54c8f8-097f-43fa-8587-5fb801c461e4 · outbound

This paper cites Agentvln: Towards agentic vision-and-language navigation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Agentvln: Towards agentic vision-and-language navigation

Reference 88

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Observation 56c67dc1-15b3-4d69-9282-3dd02bd454cf · outbound

This paper cites Learning goal-oriented language-guided navigation with self-improving demonstrations at scale.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Learning goal-oriented language-guided navigation with self-improving demonstrations at scale

Reference 89

Resolution: unresolved; no resolver link, observed 2026-07-11T19:16:57.396710Z

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Observation b095cb67-ab07-492c-a945-66d2ae287efe · outbound

This paper cites Endowing embodied agents with spatial reasoning capabilities for vision-and-language navigation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Endowing embodied agents with spatial reasoning capabilities for vision-and-language navigation

Reference 90

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Observation 78ec595b-d2f1-43c8-92c3-d324399c5d5c · outbound

This paper cites Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation

Reference 91

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Observation ef660308-8d90-414f-a3a0-d47002b0ef05 · outbound

This paper cites Sontakke, Jesse Zhang, S´ ebastien M.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Sontakke, Jesse Zhang, S´ ebastien M

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Observation 5210083a-0d52-47c4-8368-140dff9f04df · outbound

This paper cites VIP: Towards universal visual reward and representation via value-implicit pre-training.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI VIP: Towards universal visual reward and representation via value-implicit pre-training

Reference 93

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Observation 0da25528-39c7-47c1-8aec-daaa5b5ee79f · outbound

This paper cites Vision language models are in-context value learners.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Vision language models are in-context value learners

Reference 94

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Observation ffbd59dc-0b7b-4f66-98bd-2681944d382f · outbound

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ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Vision-language models are zero-shot reward models for reinforcement learning

Reference 95

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Observation 98b95458-49aa-49e0-901c-a1c5c83564b1 · outbound

This paper cites A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges

Reference 96

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Observation f6b3acb4-899d-4215-be04-9d528e4b7861 · outbound

This paper cites LIV: Language-image representations and rewards for robotic control.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI LIV: Language-image representations and rewards for robotic control

Reference 97

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Observation de4c356b-7ed9-4a73-838d-4f50e6e14b46 · outbound

This paper cites Rank2Reward: Learning shaped reward functions from passive video.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Rank2Reward: Learning shaped reward functions from passive video

Reference 98

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Observation 0e60e437-ce27-4d9d-be2a-21ebdd005052 · outbound

This paper cites Lim, Jesse Thomason, Erdem Biyik, and Jesse Zhang.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI Lim, Jesse Thomason, Erdem Biyik, and Jesse Zhang

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Observation b89c608b-c6f5-45a1-88db-14a7e3f1d15d · outbound

This paper cites SARM: Stage-aware reward modeling for long horizon robot manipulation.

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI SARM: Stage-aware reward modeling for long horizon robot manipulation

Reference 100

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