Paper Citation Record · LEDGER

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2411.10603.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.10603 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:34:35.005733Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

verified exact2
verified fuzzy17
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ba8d9f54-9cf3-453d-b7f8-0bfccca32b81 · outbound

This paper cites A survey on evaluation of large language models,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions A survey on evaluation of large language models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.897569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2f648c02-f363-4f41-8e88-6f418280b1dc · outbound

This paper cites XLM for Autonomous Driving Systems: A Comprehensive Review.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions XLM for Autonomous Driving Systems: A Comprehensive Review

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.694620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb769329-767d-4a5c-ab14-e622afe1e33a · outbound

This paper cites Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.703806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30f06fa5-b2f0-4c01-b86b-690538f68218 · outbound

This paper cites A survey on multimodal large language models for autonomous driving,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions A survey on multimodal large language models for autonomous driving,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.878795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0d995ad8-19d8-4def-bee1-117f9f63204d · outbound

This paper cites DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.715017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ce45ebf-ca24-4dbd-9750-a0d514315128 · outbound

This paper cites HiLM-D: Enhancing MLLMs with Multi-Scale High-Resolution Details for Autonomous Driving.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions HiLM-D: Enhancing MLLMs with Multi-Scale High-Resolution Details for Autonomous Driving

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.722115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 877b2f3e-bf52-473f-add5-161831b4c784 · outbound

This paper cites RAG-Driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions RAG-Driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.856033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 51646a8c-1a20-4a7b-919d-21380fb5255d · outbound

This paper cites DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.733534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e9e33ec-054a-4a1a-9e41-c70ddc04dfb7 · outbound

This paper cites DriveMLM: Aligning multi-modal large language models with behavioral planning states for autonomous driving,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions DriveMLM: Aligning multi-modal large language models with behavioral planning states for autonomous driving,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.740645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44ed7eec-afe6-4c45-86c4-211303a2e442 · outbound

This paper cites DriVLMe: Ex- ploring foundation models as autonomous driving agents that perceive, communicate, and navigate,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions DriVLMe: Ex- ploring foundation models as autonomous driving agents that perceive, communicate, and navigate,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.831405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1a0cc6b2-c173-40ff-ba33-08e6c923abe7 · outbound

This paper cites VLM2Scene: Self-supervised image-text- LiDAR learning with foundation models for autonomous driving scene understanding,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions VLM2Scene: Self-supervised image-text- LiDAR learning with foundation models for autonomous driving scene understanding,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.811880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 18826c63-a67b-4e33-8661-32cbb76b8d23 · outbound

This paper cites OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.759566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6838e69-14b0-421e-bb3c-c3b8ffa045a9 · outbound

This paper cites Enhancing Autonomous Vehicle Training with Language Model Integration and Critical Scenario Generation.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Enhancing Autonomous Vehicle Training with Language Model Integration and Critical Scenario Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.765424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc2bb731-72e5-45a3-b67c-38b58a3e448b · outbound

This paper cites A language agent for autonomous driving,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions A language agent for autonomous driving,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.792829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3f815be1-cda0-4131-aee6-93b0265b9e0a · outbound

This paper cites Feedback-guided autonomous driving,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Feedback-guided autonomous driving,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.773671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 95a88943-3df8-4767-af33-76fb3b2a43e6 · outbound

This paper cites Lever- aging multimodal large language models (MLLMs) for enhanced object detection and scene understanding in thermal images for autonomous driving systems,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Lever- aging multimodal large language models (MLLMs) for enhanced object detection and scene understanding in thermal images for autonomous driving systems,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.754701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a72f501c-0ce0-4409-9826-9339c80f0d25 · outbound

This paper cites Delving into multi-modal multi- task foundation models for road scene understanding: From learning paradigm perspectives,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Delving into multi-modal multi- task foundation models for road scene understanding: From learning paradigm perspectives,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.732674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d80ff3cb-324b-4552-8532-cca57acc3f35 · outbound

This paper cites Dense Multimodal Alignment for Open-Vocabulary 3D Scene Understanding.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Dense Multimodal Alignment for Open-Vocabulary 3D Scene Understanding

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:34:35.205821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fc35353e-b16c-42d9-b857-a71ab5f7cede · outbound

This paper cites DriveGPT4: Interpretable end-to-end autonomous driving via large language model,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions DriveGPT4: Interpretable end-to-end autonomous driving via large language model,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.711649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 38cb7aaf-96a6-4a9b-b384-f8f6d1e95806 · outbound

This paper cites Receive, reason, and react: Drive as you say, with large language models in autonomous vehicles,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Receive, reason, and react: Drive as you say, with large language models in autonomous vehicles,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.690521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 066b352f-3b2e-44b5-83c9-b5f6d447ac7b · outbound

This paper cites UnifiedMLLM: Enabling Unified Representation for Multi-modal Multi-tasks With Large Language Model.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions UnifiedMLLM: Enabling Unified Representation for Multi-modal Multi-tasks With Large Language Model

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.950153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58c3fdd8-65a2-4064-9136-57a08991f5e0 · outbound

This paper cites MLLM applied to autonomous driving across vari- ous weather conditions,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions MLLM applied to autonomous driving across vari- ous weather conditions,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.672453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation feccefee-b3d3-40ae-a830-770a9173c50b · outbound

This paper cites GPT-4o: The cutting-edge advancement in multimodal LLM,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions GPT-4o: The cutting-edge advancement in multimodal LLM,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.651990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 125ac687-c33d-413d-b43d-f02ac0165ed4 · outbound

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

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Driving with LLMs: Fusing object- level vector modality for explainable autonomous driving,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.631382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ec67be13-f14d-474d-ad5c-66471a19190a · outbound

This paper cites SurrealDriver: Designing LLM-powered Generative Driver Agent Framework based on Human Drivers' Driving-thinking Data.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions SurrealDriver: Designing LLM-powered Generative Driver Agent Framework based on Human Drivers' Driving-thinking Data

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.971796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea10bfd9-6571-4821-be7e-624d406106ba · outbound

This paper cites Driving Style Alignment for LLM-powered Driver Agent.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Driving Style Alignment for LLM-powered Driver Agent

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:34:35.125622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 37c4f505-c0b6-4b27-8a5f-d39878b0823b · outbound

This paper cites VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.982027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8717bb0d-5594-48d8-9073-c825f07f7dad · outbound

This paper cites Language Prompt for Autonomous Driving.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Language Prompt for Autonomous Driving

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T19:34:34.987372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d47fb7d-b49b-4556-bd20-18cead042941 · outbound

This paper cites CARLA: An open urban driving simulator,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions CARLA: An open urban driving simulator,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.612616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9bb551c3-dd57-4e2a-a11e-cc4a365019df · outbound

This paper cites Enhancing SUMO simulator for simulation based testing and validation of autonomous vehicles,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions Enhancing SUMO simulator for simulation based testing and validation of autonomous vehicles,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.593483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a2b314de-16f5-4dc0-b869-3262151a3c45 · outbound

This paper cites LimSim++: A closed-loop platform for deploying multimodal LLMs in autonomous driving,.

A Novel MLLM-based Approach for Autonomous Driving in Different Weather Conditions LimSim++: A closed-loop platform for deploying multimodal LLMs in autonomous driving,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:34:35.576721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.