Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:36:24.324168Z
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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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.
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 2026-05-12T06:21:25.671298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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.