DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models | Paper Citation Record

Observation 46b64b86-d5e1-43e5-94b0-7b51ac3b73d4 · outbound

This paper cites A holistic robust motion control framework for autonomous platooning,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models A holistic robust motion control framework for autonomous platooning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.328863Z

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Observation 7cc2ee29-394f-40d7-b4b9-6e5e3edb318f · outbound

This paper cites A survey on an emerging safety challenge for autonomous vehicles: Safety of the intended functionality,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models A survey on an emerging safety challenge for autonomous vehicles: Safety of the intended functionality,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.319248Z

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Observation d4b8a711-22db-4e15-b3e6-fd2dfe32d7ea · outbound

This paper cites Sotif entropy: Online sotif risk quantification and mitigation for autonomous driving,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Sotif entropy: Online sotif risk quantification and mitigation for autonomous driving,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.309427Z

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Observation 0cc07648-4951-4ff0-bb73-9781a85c92b5 · outbound

This paper cites Pesotif: A challenging visual dataset for perception sotif problems in long-tail traffic scenarios,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Pesotif: A challenging visual dataset for perception sotif problems in long-tail traffic scenarios,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.299979Z

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Observation 96f132e6-bfe6-43e2-b5fb-baa52b4601ff · outbound

This paper cites Multi-modal answer validation for knowledge-based vqa,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Multi-modal answer validation for knowledge-based vqa,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.289494Z

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Observation 5c50d009-e0c0-4f99-9bb8-7ce3852b80d5 · outbound

This paper cites Context-vqa: Towards context- aware and purposeful visual question answering,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Context-vqa: Towards context- aware and purposeful visual question answering,

Reference 6

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Observation 73245253-0d0d-44d8-9e8c-07e3d677d042 · outbound

This paper cites CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving

Reference 7

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Observation 852d2156-8d11-4cd0-8905-5566c6d68739 · outbound

This paper cites Simulation-based performance evaluation of 3d object detection methods with deep learning for a lidar point cloud dataset in a sotif-related use case,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Simulation-based performance evaluation of 3d object detection methods with deep learning for a lidar point cloud dataset in a sotif-related use case,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.269004Z

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Observation f88aa260-008f-4e0b-9ee8-99087bfb7a06 · outbound

This paper cites Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.671697Z

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Observation a924ca6b-d498-4d65-938a-59aa82a2395d · outbound

This paper cites Enhancing autonomous vehicle safety based on operational design domain defi- nition, monitoring, and functional degradation: A case study on lane keeping system,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Enhancing autonomous vehicle safety based on operational design domain defi- nition, monitoring, and functional degradation: A case study on lane keeping system,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.260103Z

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Observation e3b557f6-f83f-43f0-9521-eb9712307c92 · outbound

This paper cites Sotif-oriented percep- tion evaluation method for forward obstacle detection of autonomous vehicles,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Sotif-oriented percep- tion evaluation method for forward obstacle detection of autonomous vehicles,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.250743Z

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Observation 05235559-8731-4a8c-9456-f672812c62ca · outbound

This paper cites The sotif meta-algorithm: Quantitative analyses of the safety of autonomous behaviors,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models The sotif meta-algorithm: Quantitative analyses of the safety of autonomous behaviors,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.241685Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 00407ee8-a828-44bf-9e15-14a62d08664f · outbound

This paper cites A hazard analysis approach for the sotif in intelligent railway driving assistance systems using stpa and complex network,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models A hazard analysis approach for the sotif in intelligent railway driving assistance systems using stpa and complex network,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.231610Z

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Observation 19804e08-fff1-4471-8ace-f86518bc4018 · outbound

This paper cites Safety of the intended functionality (sotif) based on system theoretic process analysis (stpa): Study for specific control action in blind spot detection (bsd),.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Safety of the intended functionality (sotif) based on system theoretic process analysis (stpa): Study for specific control action in blind spot detection (bsd),

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.222175Z

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Observation 71aab8f8-35b1-499f-95fa-c5f944899136 · outbound

This paper cites Formal cer- tification methods for automated vehicle safety assessment,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Formal cer- tification methods for automated vehicle safety assessment,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.212108Z

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Observation 8a562cba-ab94-49f0-9a37-e6317d4be6a6 · outbound

This paper cites Systematic modeling ap- proach for environmental perception limitations in automated driving,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Systematic modeling ap- proach for environmental perception limitations in automated driving,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.201684Z

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Observation c8a783b0-c624-4284-a950-697bfb4d9e07 · outbound

This paper cites Decomposition and quan- tification of sotif requirements for perception systems of autonomous vehicles,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Decomposition and quan- tification of sotif requirements for perception systems of autonomous vehicles,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.192369Z

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Observation 76c3cb82-d18d-42af-a172-2380f7f728fd · outbound

This paper cites Online quantitative analysis of perception uncertainty based on high- definition map,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Online quantitative analysis of perception uncertainty based on high- definition map,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.182003Z

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Observation 4219b357-3f28-4387-a7a4-672ddf0ed6c1 · outbound

This paper cites Towards causal vqa: Revealing and reducing spurious correlations by invariant and covariant semantic editing,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Towards causal vqa: Revealing and reducing spurious correlations by invariant and covariant semantic editing,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.171141Z

Source-reported events for the cited work

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Observation 3c0229bb-9ef0-484d-a319-f94e6d8c4689 · outbound

This paper cites Drivellm: Charting the path toward full autonomous driving with large language models,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Drivellm: Charting the path toward full autonomous driving with large language models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.160212Z

Source-reported events for the cited work

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Observation c9f1ba13-06d1-4dc6-832e-89847479b820 · outbound

This paper cites Driving with llms: Fusing object- level vector modality for explainable autonomous driving,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Driving with llms: Fusing object- level vector modality for explainable autonomous driving,

Reference 21

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Observation a0e3d80c-b9ed-4c79-90c7-fc6be35d14cc · outbound

This paper cites VLM-MPC: Vision Language Foundation Model (VLM)-Guided Model Predictive Controller (MPC) for Autonomous Driving.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models VLM-MPC: Vision Language Foundation Model (VLM)-Guided Model Predictive Controller (MPC) for Autonomous Driving

Reference 22

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Observation 63bca8eb-f201-4ec8-8110-aea7246f8399 · outbound

This paper cites Scene understanding for autonomous driving using visual question answering,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Scene understanding for autonomous driving using visual question answering,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.144045Z

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Observation ee408494-4133-4f7c-8f51-c8ece088a1d1 · outbound

This paper cites Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario,

Reference 24

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Observation 77deb080-5531-476b-a481-9c0a3fd65c76 · outbound

This paper cites Explaining autonomous driving actions with visual question answering,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Explaining autonomous driving actions with visual question answering,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.126937Z

Source-reported events for the cited work

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Observation 82ff2c98-48a3-4da4-935d-06f6c562cf89 · outbound

This paper cites GPT-4V(ision) is a Generalist Web Agent, if Grounded.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models GPT-4V(ision) is a Generalist Web Agent, if Grounded

Reference 26

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Observation e4ea5224-34b7-485b-bf84-20fb8a0f16e0 · outbound

This paper cites Multi-Frame, Lightweight & Efficient Vision-Language Models for Question Answering in Autonomous Driving.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Multi-Frame, Lightweight & Efficient Vision-Language Models for Question Answering in Autonomous Driving

Reference 27

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Observation 451be2cc-3810-430e-a1df-cd1b4f64d60a · outbound

This paper cites Drama: Joint risk localization and captioning in driving,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Drama: Joint risk localization and captioning in driving,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.115916Z

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Observation 3723ccbd-3c21-457a-8421-c908c6fae8d0 · outbound

This paper cites Referring multi-object tracking,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Referring multi-object tracking,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.106127Z

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Observation 2088789f-d601-4812-857e-17ad26a5502d · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.741051Z

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Observation e580f922-9d48-4390-81ef-de0b8f662e33 · outbound

This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answering,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Making the v in vqa matter: Elevating the role of image understanding in visual question answering,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.096080Z

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Observation 00262dd7-76b9-4726-831d-df780c21d896 · outbound

This paper cites Cider: Consensus- based image description evaluation,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Cider: Consensus- based image description evaluation,

Reference 32

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Observation e25fa1a8-aa61-42b0-a797-2018c82bbc48 · outbound

This paper cites Spice: Semantic propositional image caption evaluation,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Spice: Semantic propositional image caption evaluation,

Reference 33

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Observation 01237a3f-619e-40df-8396-a0b309e4bfc6 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 34

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Observation 9e3e05d4-7447-44bb-84dd-44b438aad7c3 · outbound

This paper cites Judge Anything: MLLM as a Judge Across Any Modality.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Judge Anything: MLLM as a Judge Across Any Modality

Reference 35

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Observation 1792280e-73aa-4912-a9af-55f00774f848 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.760786Z

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Observation f63bb5fa-8cf4-49b2-a13a-9885ec1cc7c7 · outbound

This paper cites Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,

Reference 37

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Observation 79343155-fe7a-4cdb-8231-6f28bf60a842 · outbound

This paper cites Visual instruction tuning,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Visual instruction tuning,

Reference 38

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Observation 49174d0a-cfd0-465f-b4bd-94e858efdc42 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 39

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Observation 0bc66d7f-f9e9-4a12-920b-7d3bc587a902 · outbound

This paper cites Qwen2.5-VL Technical Report.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Qwen2.5-VL Technical Report

Reference 40

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Observation 01893d7a-a86d-4c02-bd13-f0c42186a738 · outbound

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

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 41

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Observation 06ef0d92-e2ae-44f7-b28e-7cfa5e9d2e12 · outbound

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

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.779436Z

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Observation c7397c6c-1fb6-4475-a94f-57ad15c34ca9 · outbound

This paper cites LA VIS: A one-stop library for language-vision intelligence,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models LA VIS: A one-stop library for language-vision intelligence,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.054754Z

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Observation 12b0af8c-3221-4f41-867e-6e4052e0bfa6 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 44

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Source-reported events for the cited work

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Observation 7ef106db-afe3-4eca-b312-f51ccc38a32a · outbound

This paper cites TensorRT-LLM,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models TensorRT-LLM,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.044107Z

Source-reported events for the cited work

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Observation b4220204-30f7-4b63-b043-700143b1478a · outbound

This paper cites Efficient memory management for large language model serving with pagedattention,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Efficient memory management for large language model serving with pagedattention,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.792756Z

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Observation bbd5893c-327a-4e9a-9797-d751232f4e45 · outbound

This paper cites Towards Human-Centric Autonomous Driving: A Fast-Slow Architecture Integrating Large Language Model Guidance with Reinforcement Learning.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Towards Human-Centric Autonomous Driving: A Fast-Slow Architecture Integrating Large Language Model Guidance with Reinforcement Learning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.795961Z

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Observation 430ff2b3-3d49-4c12-9e90-9f78dc6224ac · outbound

This paper cites VLMPlanner: Integrating Visual Language Models with Motion Planning.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models VLMPlanner: Integrating Visual Language Models with Motion Planning

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.799574Z

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Observation 0fd600ec-0e51-427f-a690-266130e510a2 · outbound

This paper cites Canadian adverse driving conditions dataset,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Canadian adverse driving conditions dataset,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.028217Z

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Observation 9822037e-2cb3-41c5-bdf7-b701dac82b8e · outbound

This paper cites Safe RLHF: Safe Reinforcement Learning from Human Feedback.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Safe RLHF: Safe Reinforcement Learning from Human Feedback

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.807314Z

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Observation 47041eae-e0ac-474b-a444-8aa83f236321 · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 51

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Observation 4f88fff4-c8b0-4fb3-bf11-6c00db24f296 · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.814475Z

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Observation 0bca7d1b-2853-42e1-9ace-42286c56d3d6 · outbound

This paper cites Rlaif vs. rlhf: Scaling reinforcement learning from human feedback with ai feedback,.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Rlaif vs. rlhf: Scaling reinforcement learning from human feedback with ai feedback,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:29:55.013397Z

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Observation 55fb241e-8f23-4ed5-86ef-d71ce61e03de · outbound

This paper cites Reducing Hallucinations in Vision-Language Models via Latent Space Steering.

DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models Reducing Hallucinations in Vision-Language Models via Latent Space Steering

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T22:29:54.820604Z

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