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Paper Citation Record · LEDGER

ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2312.16217.

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

pith.paper-citation-record.v1
2312.16217 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:06:12.937669Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T12:53:28.505415Z

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 a685c2e8-4bec-4994-8324-a3659bab9d0a · inbound

Lift3D Foundation Policy: Lifting 2D Large-Scale Pretrained Models for Robust 3D Robotic Manipulation cites this paper.

Lift3D Foundation Policy: Lifting 2D Large-Scale Pretrained Models for Robust 3D Robotic Manipulation ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T11:06:12.937669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:06:12.937669Z digest=sha256:1500fe92e13f5d5bb9a6bd7f21ffb5d1dd4726bab79743b6b9e806600ce421c6

Observation c4633b1a-269c-466f-9b52-d77707814ff3 · inbound

Diving into Self-Evolving Training for Multimodal Reasoning cites this paper.

Diving into Self-Evolving Training for Multimodal Reasoning ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-11T05:32:38.888290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:32:38.888290Z digest=sha256:a6d04363d98f5a204f2677dfa5259f16f9e0ee9045a5555a3708598713e3f972

Observation ba4fc7b3-3a7d-44fe-8dc4-10e1c3400390 · inbound

Integrating LMM Planners and 3D Skill Policies for Generalizable Manipulation cites this paper.

Integrating LMM Planners and 3D Skill Policies for Generalizable Manipulation ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T22:44:50.771636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T22:44:50.771636Z digest=sha256:c0d7c2749fb82dfc17aaaddec404cb00c98dbf80349476145e154e421921cf30

Observation 6023ceb1-fe25-4dd7-9265-2df50acdd989 · inbound

Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture cites this paper.

Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T11:40:22.609304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:40:22.609304Z digest=sha256:bb00656b2b0b85387f2fd233c57780216f78427af6eda9c8e3cb80eefa7237f1

Observation 92d5ce73-d317-42ef-adb4-eee7d5f571a0 · inbound

MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation cites this paper.

MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-20T12:53:28.507983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T12:53:20.761872Z digest=sha256:c330f8476236b0b3902d3f5b6bc44d4eddfbe5bd4967e42f077541f0c4c133e5

Observation 656ed2b0-9084-4aaf-a6b0-6183f1bceebb · 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 ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation

Reference 141

Resolution
unresolved
no resolver link, observed 2026-08-04T19:45:34.909786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:45:34.909786Z digest=sha256:23a9031d182064acba95fd2a451a17edbde7b7ef208a92416e915b97c6219736