Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning | Paper Citation Record

Observation 11acef8e-95cf-45d8-902e-82bee4dbd63d · outbound

This paper cites Envisioning the Future of Transportation: Inspiration of ChatGPT and Large Models.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Envisioning the Future of Transportation: Inspiration of ChatGPT and Large Models

Reference 1

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Observation 1c4a99ce-fad1-4abe-8246-101d8bd42623 · outbound

This paper cites HarnessingMultimodal Large Language Models for Traffic Knowledge Graph Generation and Decision-Making.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning HarnessingMultimodal Large Language Models for Traffic Knowledge Graph Generation and Decision-Making

Reference 2

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Observation 38aaa4e9-ed1f-4260-9fde-7404adf71e4e · outbound

This paper cites Multimodal Large-Language Model Empowering Next-Generation Autonomous Driving Systems.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Multimodal Large-Language Model Empowering Next-Generation Autonomous Driving Systems

Reference 3

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Observation cb48fe3a-3039-406d-989d-8e1acc93b8af · outbound

This paper cites IEEE Transactions on Intelligent Vehicles doi:10.1109/TIV.2024.3402136.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning IEEE Transactions on Intelligent Vehicles doi:10.1109/TIV.2024.3402136

Reference 4

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Observation 7ca8632a-f8eb-48c5-a29c-fc6725dc4036 · outbound

This paper cites DriveVLM: The convergence of autonomous driving and largevision–languagemodels.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning DriveVLM: The convergence of autonomous driving and largevision–languagemodels

Reference 5

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Observation af8ca416-67b5-4b98-a473-f3ac61861703 · outbound

This paper cites Mon-Williams, G.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Mon-Williams, G

Reference 6

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Observation 5c19d9a5-74d1-4f82-8f75-e53ecebe2fc2 · outbound

This paper cites GRAPE: Generalizing Robot Policy via Preference Alignment.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning GRAPE: Generalizing Robot Policy via Preference Alignment

Reference 7

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Observation 3fa98b85-9d0c-4fda-81d8-517625619533 · outbound

This paper cites VLM-AD:End-to-endautonomousdriving through vision–language model supervision.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning VLM-AD:End-to-endautonomousdriving through vision–language model supervision

Reference 8

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Observation c72543de-eee2-403f-8a6e-8be439308a63 · outbound

This paper cites AEFusion: An Attention-Based EnsembleLearningApproachforBEVFusionPerceptioninAutonomous Modular Buses.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning AEFusion: An Attention-Based EnsembleLearningApproachforBEVFusionPerceptioninAutonomous Modular Buses

Reference 9

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This paper cites A High-Precision Calibration and Evaluation Method Based on Binocular Cameras and LiDAR for Intelligent Vehicles.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning A High-Precision Calibration and Evaluation Method Based on Binocular Cameras and LiDAR for Intelligent Vehicles

Reference 10

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Observation 96de4ec0-8e86-4234-a6d0-44ba26a8cfba · outbound

This paper cites Few- Shot Learning for Novel Object Detection in Autonomous Driving.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Few- Shot Learning for Novel Object Detection in Autonomous Driving

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-01T06:45:28.795795Z

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Observation f770fbdf-6f5e-4ae2-8cdb-2b4a633994bc · outbound

This paper cites Use of cumulants to quantify uncertainties in the HBT measurements of the homogeneity regions.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Use of cumulants to quantify uncertainties in the HBT measurements of the homogeneity regions

Reference 12

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This paper cites The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision).

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

Reference 13

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Observation 3d86ddbd-c0ee-4d93-b5bc-fcc33f30cf43 · outbound

This paper cites Qwen2.5-VL Technical Report.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Qwen2.5-VL Technical Report

Reference 14

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Observation 0f99fb59-4f49-444b-aa81-3e504a3578fe · outbound

This paper cites Grounding DINO: Marrying DINO with grounded pre- training for open-set object detection.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Grounding DINO: Marrying DINO with grounded pre- training for open-set object detection

Reference 15

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Observation cf6bd4ea-7bd7-40c1-9793-4655bdee3484 · outbound

This paper cites In: European Conference on Computer Vision.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning In: European Conference on Computer Vision

Reference 16

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Observation f2682d51-eca3-4a8c-ab9f-fd15c87bfbb5 · outbound

This paper cites Pix2Seq: A Language Modeling Framework for Object Detection.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Pix2Seq: A Language Modeling Framework for Object Detection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.898229Z

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Observation 166e5233-75dd-437f-a2a0-273507b5181f · outbound

This paper cites LISA: ReasoningSegmentationviaLargeLanguageModel.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning LISA: ReasoningSegmentationviaLargeLanguageModel

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.896276Z

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Observation 11285bcf-20ac-4f92-b057-a6361c18603d · outbound

This paper cites MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.875898Z

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Observation 136a6da1-5974-41dd-8b33-b09817997e7c · outbound

This paper cites CoverNet: Multimodal Behavior Prediction Using Trajectory Sets.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning CoverNet: Multimodal Behavior Prediction Using Trajectory Sets

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.869743Z

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Observation a352434e-3d99-4f87-95b8-8724685ba95f · outbound

This paper cites HPNet: Dynamic trajectory forecasting with historical prediction attention.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning HPNet: Dynamic trajectory forecasting with historical prediction attention

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.888834Z

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This paper cites HowGenerativeAdversarialNetworks Promote the Development of Intelligent Transportation Systems: A Survey.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning HowGenerativeAdversarialNetworks Promote the Development of Intelligent Transportation Systems: A Survey

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-01T06:45:28.791847Z

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This paper cites A Dynamic Prompting and Scenario Generation Method for Autonomous Driving Perception via Large-Model Optimization.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning A Dynamic Prompting and Scenario Generation Method for Autonomous Driving Perception via Large-Model Optimization

Reference 23

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Observation ab47b0ee-ed28-44e7-aae5-d55e8d18821e · outbound

This paper cites Risk-Controllable Multi-View Diffusion for Driving Scenario Generation.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Risk-Controllable Multi-View Diffusion for Driving Scenario Generation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.874013Z

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Observation 59142d4c-bbc9-4995-80b0-e884a527ad0a · outbound

This paper cites Training language models to follow instructions with human feedback.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Training language models to follow instructions with human feedback

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.872229Z

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Observation 94d045e9-d1ee-4b3d-86d1-ec7a921faa74 · outbound

This paper cites A meta- analysis on the reliability of comparative judgement.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning A meta- analysis on the reliability of comparative judgement

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-01T06:45:28.785324Z

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Observation a47ba181-da55-4b45-84f8-f0fd6afb4759 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning LoRA: Low-Rank Adaptation of Large Language Models

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.881743Z

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Observation 178978c1-3b8f-476d-b1c5-6e326916c01f · outbound

This paper cites DETRs beat YOLOs on real-time object detection.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning DETRs beat YOLOs on real-time object detection

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.890516Z

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Observation b658ea2f-71b1-40a5-9242-62ab525a777f · outbound

This paper cites 3D-MOOD: Lifting 2D to 3D for monocular open- set object detection.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning 3D-MOOD: Lifting 2D to 3D for monocular open- set object detection

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.880068Z

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Observation 2ea305ce-93b1-4e88-8928-e345c928c438 · outbound

This paper cites Masked- attention mask transformer for universal image segmentation.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Masked- attention mask transformer for universal image segmentation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.892524Z

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Observation 610b5631-3eae-42a2-bf0d-a908de40fb8a · outbound

This paper cites Fast Segment Anything.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Fast Segment Anything

Reference 31

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Observation 1338e5cb-4141-4b8c-9132-93af72db455b · outbound

This paper cites In: Proc.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning In: Proc

Reference 32

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This paper cites Vision meets robotics: The KITTI dataset.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Vision meets robotics: The KITTI dataset

Reference 33

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Observation 136a14b8-5d30-4732-b7ec-e592685ac1b9 · outbound

This paper cites Argoverse: 3D tracking and forecasting with rich maps.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Argoverse: 3D tracking and forecasting with rich maps

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.885194Z

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This paper cites The Cityscapes dataset for semantic urban scene understanding.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning The Cityscapes dataset for semantic urban scene understanding

Reference 35

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Observation f7235fad-6713-42c2-99e8-9679d5f925a2 · outbound

This paper cites Toward Human-in-the-Loop AI: Enhancing Deep Reinforcement Learning via Real-Time Human GuidanceforAutonomousDriving.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Toward Human-in-the-Loop AI: Enhancing Deep Reinforcement Learning via Real-Time Human GuidanceforAutonomousDriving

Reference 36

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 37

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 38

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 39

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Observation a1bb6aa3-2f53-46ec-b7d9-d3178090595e · outbound

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 40

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 41

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 42

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 43

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 44

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Observation 9b9416a4-eeec-439f-a31c-c676292b846f · outbound

This paper cites 11 Trajectory prediction – selection prompt You are analyzing a trajectory prediction scenario.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning 11 Trajectory prediction – selection prompt You are analyzing a trajectory prediction scenario

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.911277Z

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Observation 65d014b6-c776-4511-a04d-74ff57f42dc8 · outbound

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 46

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Observation 131d480d-7189-48fc-ab6d-96f7392858b9 · outbound

This paper cites an unresolved cited work.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 47

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Observation f3f3aabd-a95d-4a6e-913e-ed6bf9b910f3 · outbound

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Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Unresolved cited work

Reference 48

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Observation 8f9c69ab-531f-488d-9596-b3ee70d4e225 · outbound

This paper cites Candidate 3.

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning Candidate 3

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:42:43.917038Z

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