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Paper Citation Record · LEDGER

Ego-centric Learning of Communicative World Models for Autonomous Driving

As of 10 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 2 inbound Pith citation observations for arXiv:2506.08149.

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

pith.paper-citation-record.v1
2506.08149 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:27:42.446479Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:57:08.704505Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:57:08.967016Z

Reference resolution

35 of 35 outbound references displayed

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  • verified fuzzy16
  • unresolved19
  • parse uncertain0
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Outbound references

Observation 4519568a-4a0b-4ff3-bc25-694804e0d8f0 · outbound

This paper cites Deep Learning using Rectified Linear Units (ReLU).

Ego-centric Learning of Communicative World Models for Autonomous Driving Deep Learning using Rectified Linear Units (ReLU)

Reference 1

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Observation fdcb6ef0-eda9-4bb8-8b14-74d365d3fb33 · outbound

This paper cites With Assumption Assumption 3 holds, we obtain the following bound, rl − ˆrl ≤Lr(1 + Lπ)ϵt+l Qt+L − ˆQt+L ≤LQ(1 + Lπ)ϵt+L, where LQ := Lr 1−γ.

Ego-centric Learning of Communicative World Models for Autonomous Driving With Assumption Assumption 3 holds, we obtain the following bound, rl − ˆrl ≤Lr(1 + Lπ)ϵt+l Qt+L − ˆQt+L ≤LQ(1 + Lπ)ϵt+L, where LQ := Lr 1−γ

Reference 3

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Observation 166c3fc5-cc58-46b5-affc-1085bc8ddf65 · outbound

This paper cites Model-free deep reinforcement learning for urban autonomous driving.

Ego-centric Learning of Communicative World Models for Autonomous Driving Model-free deep reinforcement learning for urban autonomous driving

Reference 4

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Observation 77736695-5a54-49f0-af4b-0a3b7b042b35 · outbound

This paper cites The BEV representation can be learnt by using algorithms such as BevFusion Liu et al.

Ego-centric Learning of Communicative World Models for Autonomous Driving The BEV representation can be learnt by using algorithms such as BevFusion Liu et al

Reference 5

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Observation 976ab7c1-8086-4c34-9f96-c412bb17a252 · outbound

This paper cites We provide the detailed demo videos and images in the supplementary materials.

Ego-centric Learning of Communicative World Models for Autonomous Driving We provide the detailed demo videos and images in the supplementary materials

Reference 7

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Observation 825c701a-4fa1-4d10-b570-1395fb7dc130 · outbound

This paper cites E.2 W ORLD MODEL TRAINING We use Dreamer v3 Hafner et al.

Ego-centric Learning of Communicative World Models for Autonomous Driving E.2 W ORLD MODEL TRAINING We use Dreamer v3 Hafner et al

Reference 8

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Observation 8a156622-9757-49d9-bfde-b0d969bbe435 · outbound

This paper cites Mastering Diverse Domains through World Models.

Ego-centric Learning of Communicative World Models for Autonomous Driving Mastering Diverse Domains through World Models

Reference 11

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Observation 6dcef7f7-d4e3-4509-9746-e9a20592d7ac · outbound

This paper cites Auto-Encoding Variational Bayes.

Ego-centric Learning of Communicative World Models for Autonomous Driving Auto-Encoding Variational Bayes

Reference 12

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source=pdf_text observed=2026-08-07T05:27:42.341973Z digest=sha256:18a6a008d6f091e42b6e6dac37c5f259116a39b86897009e9cf161885b368f3e

Observation 2b043b30-1369-4b43-ba87-af8846c95ed9 · outbound

This paper cites Think2Drive: Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving (in CARLA-v2).

Ego-centric Learning of Communicative World Models for Autonomous Driving Think2Drive: Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving (in CARLA-v2)

Reference 13

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Observation f9e674f8-ae03-4629-b107-98b46ec008ec · outbound

This paper cites Efficient Multi-agent Reinforcement Learning by Planning.

Ego-centric Learning of Communicative World Models for Autonomous Driving Efficient Multi-agent Reinforcement Learning by Planning

Reference 14

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Observation 8a64483b-e6ca-4d42-9e57-8fd409c9ef7b · outbound

This paper cites Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation.

Ego-centric Learning of Communicative World Models for Autonomous Driving Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation

Reference 15

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Observation 090bb2d2-8a78-4098-a48b-78150a2781a3 · outbound

This paper cites Trajectory planning for autonomous vehicles using hierarchical reinforcement learning.

Ego-centric Learning of Communicative World Models for Autonomous Driving Trajectory planning for autonomous vehicles using hierarchical reinforcement learning

Reference 16

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Observation b60b2404-00ac-40b1-b2f0-9e23b2a5a72e · outbound

This paper cites Scalable multi-agent reinforcement learning for networked systems with average reward.

Ego-centric Learning of Communicative World Models for Autonomous Driving Scalable multi-agent reinforcement learning for networked systems with average reward

Reference 18

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Observation 192592f0-6623-4d2b-9d2c-07f79208d854 · outbound

This paper cites Car2x-based perception in a high-level fusion architecture for cooperative perception systems.

Ego-centric Learning of Communicative World Models for Autonomous Driving Car2x-based perception in a high-level fusion architecture for cooperative perception systems

Reference 19

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Observation cbf56137-3d0c-420a-9de9-c808b3ea71b5 · outbound

This paper cites Benchmarking Model-Based Reinforcement Learning.

Ego-centric Learning of Communicative World Models for Autonomous Driving Benchmarking Model-Based Reinforcement Learning

Reference 20

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Observation 425358e9-156b-4134-a29b-08cde05a659a · outbound

This paper cites Leveraging world model disentanglement in value-based multi-agent reinforcement learning.

Ego-centric Learning of Communicative World Models for Autonomous Driving Leveraging world model disentanglement in value-based multi-agent reinforcement learning

Reference 21

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Observation 92410a65-a7cb-4089-bc99-77beebe6ff3a · outbound

This paper cites Statistical machine learning in model predictive control of nonlinear processes.

Ego-centric Learning of Communicative World Models for Autonomous Driving Statistical machine learning in model predictive control of nonlinear processes

Reference 22

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Observation 7cf94762-5dcd-43ea-b174-e0f7a9998755 · outbound

This paper cites Game-Theoretic Multiagent Reinforcement Learning.

Ego-centric Learning of Communicative World Models for Autonomous Driving Game-Theoretic Multiagent Reinforcement Learning

Reference 23

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Observation b6aca387-30be-4020-ba9a-e5d70699e37a · outbound

This paper cites COMBO: Compositional World Models for Embodied Multi-Agent Cooperation.

Ego-centric Learning of Communicative World Models for Autonomous Driving COMBO: Compositional World Models for Embodied Multi-Agent Cooperation

Reference 24

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Observation c8647893-fbb8-4c88-9dc1-9f2d0cdcd987 · outbound

This paper cites Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts.

Ego-centric Learning of Communicative World Models for Autonomous Driving Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts

Reference 25

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Observation b7f6cf23-3d09-4eea-ac69-dd07f3f8e23c · outbound

This paper cites Chen et al.

Ego-centric Learning of Communicative World Models for Autonomous Driving Chen et al

Reference 27

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Observation 93c19c4f-fbd3-4d2a-91cc-ce9b83de26c8 · outbound

This paper cites • ¯zt+k: the prediction generated by RNN if the Locally Sufficient Information (LSI) is employed as input.

Ego-centric Learning of Communicative World Models for Autonomous Driving • ¯zt+k: the prediction generated by RNN if the Locally Sufficient Information (LSI) is employed as input

Reference 28

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Observation 99dffc48-7a61-4ff6-94ed-4b7f18b65095 · outbound

This paper cites L−1X l=0 γlr(st+l, at+l, a′ t+l) + γLQt−1(st+L, at+L, a′ t+L) # − Ea∼π.

Ego-centric Learning of Communicative World Models for Autonomous Driving L−1X l=0 γlr(st+l, at+l, a′ t+l) + γLQt−1(st+L, at+L, a′ t+L) # − Ea∼π

Reference 29

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Observation 7022376e-307c-4f9e-92a4-98de59f008d5 · outbound

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Ego-centric Learning of Communicative World Models for Autonomous Driving Unresolved cited work

Reference 34

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Observation 49d798db-1df2-4b38-a192-1d18c4d854b4 · outbound

This paper cites an unresolved cited work.

Ego-centric Learning of Communicative World Models for Autonomous Driving Unresolved cited work

Reference 35

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Observation 4bf25575-178b-4d53-9843-f0fcd0c6d37a · outbound

This paper cites The dynamics of reinforcement learning in cooperative multiagent systems.

Ego-centric Learning of Communicative World Models for Autonomous Driving The dynamics of reinforcement learning in cooperative multiagent systems

Reference 1991

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raw_fallback, observed 2026-08-07T05:27:43.021520Z

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Observation 6e5443c4-d6eb-4464-925e-856ca8e0bb24 · outbound

This paper cites A R ELATED WORK Model-based MARL.

Ego-centric Learning of Communicative World Models for Autonomous Driving A R ELATED WORK Model-based MARL

Reference 2007

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Observation 7cf56b39-9c9b-4e02-9f09-3a0db625f727 · outbound

This paper cites Independent Learning in Stochastic Games.

Ego-centric Learning of Communicative World Models for Autonomous Driving Independent Learning in Stochastic Games

Reference 2008

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source=pdf_text observed=2026-08-07T05:27:42.366330Z digest=sha256:3672b0bc7f1424b3dd6fa86c9422a1bc919d29fd39fef47cecf2e587cfb4ceaf

Observation cc8230f2-a2e1-424a-b004-9d4ea9a10a05 · outbound

This paper cites Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?.

Ego-centric Learning of Communicative World Models for Autonomous Driving Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?

Reference 2009

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Observation cbe75793-b654-4310-8edf-329d09554f2d · outbound

This paper cites World Models.

Ego-centric Learning of Communicative World Models for Autonomous Driving World Models

Reference 2016

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Observation 62ab6c11-700d-45d1-af5d-368112e29621 · outbound

This paper cites DeepMind Lab.

Ego-centric Learning of Communicative World Models for Autonomous Driving DeepMind Lab

Reference 2018

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source=pdf_text observed=2026-08-07T05:27:42.299064Z digest=sha256:530c0a992739bb73e9a45e8599fff108ff2b8ef291a88f1497e9f72aa182b920

Observation e1447e90-3857-4337-b1d0-38025a1dba9f · outbound

This paper cites Mastering Atari with Discrete World Models.

Ego-centric Learning of Communicative World Models for Autonomous Driving Mastering Atari with Discrete World Models

Reference 2019

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source=pdf_text observed=2026-08-07T05:27:42.332120Z digest=sha256:b1ad736d9e4d10f7ec7d636c602d996cf23e223fa05c7eed0aa6a972f40edf72

Observation fbd843cd-f849-4f81-8232-530cd96838c5 · outbound

This paper cites ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst.

Ego-centric Learning of Communicative World Models for Autonomous Driving ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst

Reference 2020

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source=pdf_text observed=2026-08-07T05:27:42.293624Z digest=sha256:9f4b1e6321e16f036288bf540591262593e6cf7e36455becfdd90343f6dabc52

Observation dda29755-7e15-401e-9a48-198f680542ef · outbound

This paper cites End-to-end Autonomous Driving: Challenges and Frontiers.

Ego-centric Learning of Communicative World Models for Autonomous Driving End-to-end Autonomous Driving: Challenges and Frontiers

Reference 2021

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source=pdf_text observed=2026-08-07T05:27:42.308408Z digest=sha256:0e60c91d8129559a166732fdd584d1ab73fe396be87de34b8ffbb577501b0499

Observation 67378425-818e-4a13-9001-627de2901a38 · outbound

This paper cites Cooper: Cooperative perception for connected autonomous vehicles based on 3d point clouds.

Ego-centric Learning of Communicative World Models for Autonomous Driving Cooper: Cooperative perception for connected autonomous vehicles based on 3d point clouds

Reference 2023

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raw_fallback, observed 2026-08-07T05:27:43.035865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:27:42.313315Z digest=sha256:6ad1f376f38bebd596ebfc41a83ff35f06409e609d5197456d87b1808e1ab5bf

Pith citing papers

Observation 38edc3df-b89a-44bf-b657-695124a0be6c · inbound

GenAI-based Multi-Agent Reinforcement Learning towards Distributed Agent Intelligence: A Generative-RL Agent Perspective cites this paper.

GenAI-based Multi-Agent Reinforcement Learning towards Distributed Agent Intelligence: A Generative-RL Agent Perspective Ego-centric Learning of Communicative World Models for Autonomous Driving

Reference 154

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:57:08.972558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T17:57:08.704505Z digest=sha256:94e3f54057e513c4204386d2c34817e3cee3a93ba9f60a0ba8d6c02c08d4b29f

Observation bb22ac97-3db9-4297-a6cf-278f63e0db2e · inbound

A Comprehensive Survey on World Models for Embodied AI cites this paper.

A Comprehensive Survey on World Models for Embodied AI Ego-centric Learning of Communicative World Models for Autonomous Driving

Reference 123

Resolution
unresolved
no resolver link, observed 2026-08-04T09:12:43.953225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:12:43.953225Z digest=sha256:b979a4b5ee04611d4f4193192359e24cd5e1f304be45df14e8377694a3ac3cd1