Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MotionRL: Align Text-to-Motion Generation to Human Preferences with Multi-Reward Reinforcement Learning
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.06513.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T10:13:40.580329Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T02:40:14.746588Z
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 635a1e0d-0bcc-49a2-9b29-6856134bbbd9 · inbound
Fleximo: Towards Flexible Text-to-Human Motion Video Generation cites this paper.
Fleximo: Towards Flexible Text-to-Human Motion Video Generation MotionRL: Align Text-to-Motion Generation to Human Preferences with Multi-Reward Reinforcement Learning
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T10:13:40.580329Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d56ceb1a-d05e-4cb3-99b8-a1149bfa99d5 · inbound
IRG-MotionLLM: Interleaving Motion Generation, Assessment and Refinement for Text-to-Motion Generation cites this paper.
IRG-MotionLLM: Interleaving Motion Generation, Assessment and Refinement for Text-to-Motion Generation MotionRL: Align Text-to-Motion Generation to Human Preferences with Multi-Reward Reinforcement Learning
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:06:56.393617Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f1497c4-cead-4477-bb3f-36d54360a337 · inbound
MotionMERGE: A Multi-granular Framework for Human Motion Editing, Reasoning, Generation, and Explanation cites this paper.
MotionMERGE: A Multi-granular Framework for Human Motion Editing, Reasoning, Generation, and Explanation MotionRL: Align Text-to-Motion Generation to Human Preferences with Multi-Reward Reinforcement Learning
Reference 75
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T10:38:12.356758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c809c625-af8b-4bd2-b532-e536442f504a · inbound
SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-based Humanoid Control cites this paper.
SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-based Humanoid Control MotionRL: Align Text-to-Motion Generation to Human Preferences with Multi-Reward Reinforcement Learning
Reference 75
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T02:40:14.749926Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.