Paper Citation Record · LEDGER

QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2306.10508.

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

pith.paper-citation-record.v1
2306.10508 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:36:24.324168Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-11T03:27:45.540736Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c8dfab90-75bb-4159-9550-591ea2f571b4 · inbound

RetroMotion: Retrocausal Motion Forecasting Models are Instructable cites this paper.

RetroMotion: Retrocausal Motion Forecasting Models are Instructable QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-19T12:47:18.047570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0bb50f07-48cf-4bc5-9269-215e999d15d9 · inbound

Autoregressive Meta-Actions for Unified Controllable Trajectory Generation cites this paper.

Autoregressive Meta-Actions for Unified Controllable Trajectory Generation QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:49.396232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b33d1342-74e0-4490-8cb0-a4a4ede95cdc · inbound

AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning cites this paper.

AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:46:44.224232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aa698c47-cdb6-4bce-8dcd-67f4f8db31eb · inbound

CooperRisk: A Driving Risk Quantification Pipeline with Multi-Agent Cooperative Perception and Prediction cites this paper.

CooperRisk: A Driving Risk Quantification Pipeline with Multi-Agent Cooperative Perception and Prediction QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T19:36:24.324168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d9a1188-8f30-44c5-9927-54d5dd6348fd · inbound

Improving Consistency in Vehicle Trajectory Prediction Through Preference Optimization cites this paper.

Improving Consistency in Vehicle Trajectory Prediction Through Preference Optimization QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T20:34:37.304363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a44ca707-a0fb-4e2d-92e7-e2f7933709d2 · inbound

What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies cites this paper.

What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 261

Resolution: unresolved; no resolver link, observed 2026-08-06T19:06:09.188971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a63491e-278c-4a52-97a6-f7158c89d7c6 · inbound

ILNet: Trajectory Prediction with Inverse Learning Attention for Enhancing Intention Capture cites this paper.

ILNet: Trajectory Prediction with Inverse Learning Attention for Enhancing Intention Capture QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T19:07:16.865039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aad221af-c232-4b93-9f29-5f000436d5c9 · inbound

JAM: Keypoint-Guided Joint Prediction after Classification-Aware Marginal Proposal for Multi-Agent Interaction cites this paper.

JAM: Keypoint-Guided Joint Prediction after Classification-Aware Marginal Proposal for Multi-Agent Interaction QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:00:19.221981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9271fba4-fe3f-4bbf-b106-93c43c52a7e3 · inbound

DeMo++: Motion Decoupling for Autonomous Driving cites this paper.

DeMo++: Motion Decoupling for Autonomous Driving QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T14:55:02.805329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f349349-2524-47d3-9b57-7f9927d270c6 · inbound

Do LLM Modules Generalize? A Study on Motion Generation for Autonomous Driving cites this paper.

Do LLM Modules Generalize? A Study on Motion Generation for Autonomous Driving QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T11:30:39.671835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ed7e4bf-8471-48da-9823-dd8233b318b0 · inbound

Super Agents and Confounders: Influence of surrounding agents on vehicle trajectory prediction cites this paper.

Super Agents and Confounders: Influence of surrounding agents on vehicle trajectory prediction QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-13T19:48:11.702276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a824f512-6221-4722-88f6-cd322a4b0ad7 · inbound

SCORP: Scene-Consistent Multi-agent Diffusion Planning with Stable Online Reinforcement Post-Training for Cooperative Driving cites this paper.

SCORP: Scene-Consistent Multi-agent Diffusion Planning with Stable Online Reinforcement Post-Training for Cooperative Driving QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:21:04.638698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b6024a6e-213a-4461-8729-3fe2400de3ef · inbound

SCORP: Scene-Consistent Multi-agent Diffusion Planning with Stable Online Reinforcement Post-Training for Cooperative Driving cites this paper.

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:21:25.671298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3dd84281-1a18-42fa-8971-6a85aa6797f6 · inbound

Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Traffic cites this paper.

Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Traffic QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 132

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:26:02.616459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9872ad1b-8862-4868-ad37-65578abfbc57 · inbound

DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving cites this paper.

DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 73

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:31:26.345389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4ea3e96b-1a27-4667-9014-dd26c5ca189f · inbound

MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems cites this paper.

MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:51:27.397166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 98d8ac11-ef38-425d-9380-0a978c03beeb · inbound

Teaching Vision-Language-Action Models What to See and Where to Look cites this paper.

Teaching Vision-Language-Action Models What to See and Where to Look QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:48:39.550408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ff7ccd53-7a2f-4d1a-9c72-33edd9c1f354 · inbound

IMR: Iterative Mode-World Weighted Regression for Multi-Agent Trajectory Prediction cites this paper.

IMR: Iterative Mode-World Weighted Regression for Multi-Agent Trajectory Prediction QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-11T03:27:45.562012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 95b88649-ab76-4c1e-9276-74fddf5862a2 · inbound

Long-term Traffic Scene Prediction via Polynomial Representations in Autonomous Driving cites this paper.

Long-term Traffic Scene Prediction via Polynomial Representations in Autonomous Driving QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

Reference 107

Resolution: unresolved; no resolver link, observed 2026-08-05T20:54:21.841372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.