Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Prompt a Robot to Walk with Large Language Models
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2309.09969.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T11:29:20.749487Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T02:33:47.691459Z
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 f62ce691-77ac-468d-867e-59c18b492c48 · inbound
Agent AI: Surveying the Horizons of Multimodal Interaction cites this paper.
Agent AI: Surveying the Horizons of Multimodal Interaction Prompt a Robot to Walk with Large Language Models
Reference 156
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T14:25:59.517253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 18fcf33b-0d00-4f19-b6f3-94c6784c863d · inbound
Chat Modeling: Interaction-Enhanced Agent Framework for Visualizing Literature-Grounded Biological Structures cites this paper.
Chat Modeling: Interaction-Enhanced Agent Framework for Visualizing Literature-Grounded Biological Structures Prompt a Robot to Walk with Large Language Models
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T02:33:47.695536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4e81c6ea-fd47-40e0-a278-1aa75d290ea0 · inbound
Prediction with Action: Visual Policy Learning via Joint Denoising Process cites this paper.
Prediction with Action: Visual Policy Learning via Joint Denoising Process Prompt a Robot to Walk with Large Language Models
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T11:29:20.749487Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 536d1117-54c1-4237-9863-69941a92b0cb · inbound
Using Large Language Models for Parametric Shape Optimization cites this paper.
Using Large Language Models for Parametric Shape Optimization Prompt a Robot to Walk with Large Language Models
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T18:19:53.951988Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ec3def7f-3dfb-469e-b933-b7fb45cf9005 · inbound
Improving Vision-Language-Action Model with Online Reinforcement Learning cites this paper.
Improving Vision-Language-Action Model with Online Reinforcement Learning Prompt a Robot to Walk with Large Language Models
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T11:39:56.147898Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2d464b53-e88e-47cb-9843-f6611725bd91 · inbound
UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent cites this paper.
UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent Prompt a Robot to Walk with Large Language Models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T22:13:14.928657Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c5988630-96d3-471f-b8af-6e0eb73b10e9 · inbound
DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning cites this paper.
DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Prompt a Robot to Walk with Large Language Models
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:42:29.396155Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc08d25c-595f-40e3-b7cf-5bc770ad4372 · inbound
PRISM-XR: Empowering Privacy-Aware XR Collaboration with Multimodal Large Language Models cites this paper.
PRISM-XR: Empowering Privacy-Aware XR Collaboration with Multimodal Large Language Models Prompt a Robot to Walk with Large Language Models
Reference 55
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T05:07:20.522328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation ecea71a7-34c5-4bc6-9c65-6aaface69d98 · inbound
Hierarchical Prompting with Dual LLM Modules for Robotic Task and Motion Planning cites this paper.
Hierarchical Prompting with Dual LLM Modules for Robotic Task and Motion Planning Prompt a Robot to Walk with Large Language Models
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T08:06:26.443353Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 71b16e61-ac28-4b99-87a5-3fc4386cf035 · inbound
Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills cites this paper.
Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills Prompt a Robot to Walk with Large Language Models
Reference 257
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:45:35.313533Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.