Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:45:49.995694Z
Paper Citation Record · LEDGER
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation
As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2505.23612.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
14 of 14 outbound references displayed
- verified exact0
- verified fuzzy3
- unresolved11
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 4633c0b5-4630-4f1d-b4f7-7593ad033ba8 · outbound
This paper cites GPT-4 Technical Report.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation GPT-4 Technical Report
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:48.690108Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation da863ee5-03be-4c98-b566-27b5ca3b4007 · outbound
This paper cites UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:48.950184Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d74758c9-ffb7-4396-a06a-0f66af8ef916 · outbound
This paper cites SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:49.200980Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f5b4e1ca-042a-4c0d-b898-59a36eb9d121 · outbound
This paper cites DRoPE: Directional Rotary Position Embedding for Efficient Agent Interaction Modeling.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation DRoPE: Directional Rotary Position Embedding for Efficient Agent Interaction Modeling
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:49.270432Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1709b3da-f5f3-4d8a-a446-5f4c3644a96e · outbound
This paper cites an unresolved cited work.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T12:45:51.193120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c3b4e7e8-11fa-4b3b-b147-ab15956bcb17 · outbound
This paper cites This significantly reduces the memory complexity by a factor of N, the number of agents in the scene, thereby accelerating training while maintaining strong performance.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation This significantly reduces the memory complexity by a factor of N, the number of agents in the scene, thereby accelerating training while maintaining strong performance
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:45:50.934455Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1fcbda9e-6872-4c7d-917c-5966a2ecc17d · outbound
This paper cites This adjustment ensures that the embedding retains the inherent2π-periodicity of directional angles.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation This adjustment ensures that the embedding retains the inherent2π-periodicity of directional angles
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:45:50.668570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 93671052-dedf-41a6-9c8b-63ce97ff2aad · outbound
This paper cites Both the action prediction module and the meta-action prediction module consist of three transformer layers for temporal aggregation.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation Both the action prediction module and the meta-action prediction module consist of three transformer layers for temporal aggregation
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:45:50.411180Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 18b42b33-ce04-46c0-8244-7d63b25bcdfb · outbound
This paper cites OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:49.132849Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 98a226a5-c546-4b57-973a-f71d66953428 · outbound
This paper cites MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:48.781737Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b8d40546-da2f-49f0-afb5-52d6040ccebb · outbound
This paper cites Large Trajectory Models are Scalable Motion Predictors and Planners.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation Large Trajectory Models are Scalable Motion Predictors and Planners
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:49.069135Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1664f1b8-9a79-46ab-8d2f-bc27a15d5c26 · outbound
This paper cites CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:49.004620Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e537f5a7-12df-478e-b541-889395048913 · outbound
This paper cites Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-tuning.
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-tuning
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:45:48.866794Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0bb50f07-48cf-4bc5-9269-215e999d15d9 · outbound
This paper cites QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction.
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.
Pith citing papers
No inbound Pith citation observations are available.