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Paper Citation Record · LEDGER

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents

As of 11 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2510.18608.

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

pith.paper-citation-record.v1
2510.18608 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:53:11.182928Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e6e7244-374f-4c25-9aab-515769eaf786 · outbound

This paper cites Learning Interactive Real-World Simulators.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Learning Interactive Real-World Simulators

Reference 1

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no resolver link, observed 2026-08-04T08:53:09.453631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:53:09.453631Z digest=sha256:78da97d8c45114f9fa47e02d666584e1ea9a6ef67df4a1e7af293106f801f020

Observation 9be67eb2-9838-4646-af34-6aa643e428a5 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 2

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no resolver link, observed 2026-08-04T08:53:09.543262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:53:09.543262Z digest=sha256:c95329bbead1a4208d7d73b6f222ad055f90732d2c9a87bdd77a32c085bd381f

Observation 4e10dd79-8db7-4f54-b2a7-c6a6e04458d1 · outbound

This paper cites The Future of Continual Learning in the Era of Foundation Models: Three Key Directions.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents The Future of Continual Learning in the Era of Foundation Models: Three Key Directions

Reference 3

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no resolver link, observed 2026-08-04T08:53:09.702628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:53:09.702628Z digest=sha256:3cf1d86115e029cf883e7f93ce0ceaa5a8995a6e1105103519c56b9945e491d8

Observation 5bd4e0eb-bb52-4ce8-adfd-6a6af41f0ddb · outbound

This paper cites RT-1: robotics transformer for real-world control at scale.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents RT-1: robotics transformer for real-world control at scale

Reference 4

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no resolver link, observed 2026-08-04T08:53:09.866381Z

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source=pdf_text observed=2026-08-04T08:53:09.866381Z digest=sha256:2558b761a363aa869803a73868a037a842157ea7d17fb8b1ba3e5839795151fe

Observation c49bc2a5-14a2-45f1-8c99-bf5e34fee3f4 · outbound

This paper cites Ham: Hierarchical adapter merging for scalable continual learning.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Ham: Hierarchical adapter merging for scalable continual learning

Reference 5

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no resolver link, observed 2026-08-04T08:53:09.977577Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T08:53:09.977577Z digest=sha256:4d3a9ef74407002353db4678189f64098108126dfac02492dd6b3a001f7f6a88

Observation b1e2c2ac-14e6-47c2-b62f-17ace4eb6632 · outbound

This paper cites Instruction-driven history-aware policies for robotic manipulations.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Instruction-driven history-aware policies for robotic manipulations

Reference 6

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no resolver link, observed 2026-08-04T08:53:10.097813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:53:10.097813Z digest=sha256:b0cbc166667d47d6e3b00e8b04e5251f61e55ac7791e124f24e57bbc2e94a0b8

Observation 681e47b9-ea16-47b3-99c1-6342d5e408b0 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Lora: Low-rank adaptation of large language models

Reference 7

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T08:53:10.249411Z digest=sha256:c8ae2540f07d6f89db996839545303e17eb6815f93a222b199381925325f24cc

Observation 70eb54f7-2acf-45d7-aa92-c5deb405cecb · outbound

This paper cites $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

Reference 8

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source=pdf_text observed=2026-08-04T08:53:10.367470Z digest=sha256:2f080609e85324b1e31199e232d7f9e447e6630339ef7fcd1dc65c03cb387013

Observation 4df99196-dcb5-43a3-90cb-88bd95117333 · outbound

This paper cites Openvla: An open-source vision-language-action model.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Openvla: An open-source vision-language-action model

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:53:10.533946Z digest=sha256:50e080d5e1f755485c1250360d4a6ab76d365f1c5534b4eae14c780e64c6975d

Observation 4deea9d4-435b-439e-8e6f-63224e9b6267 · outbound

This paper cites Has LLM Reached the Scaling Ceiling Yet? Unified Insights into LLM Regularities and Constraints.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Has LLM Reached the Scaling Ceiling Yet? Unified Insights into LLM Regularities and Constraints

Reference 10

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source=pdf_text observed=2026-08-04T08:53:10.645620Z digest=sha256:ca2a549647524c731ae1483e72df0648ced06e2c0070fd478a3a271e87dec1a6

Observation 37f0fafc-d2b1-4320-ac0b-f1ba4739383d · outbound

This paper cites Open x-embodiment: Robotic learning datasets and RT-X models : Open x-embodiment collaboration.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Open x-embodiment: Robotic learning datasets and RT-X models : Open x-embodiment collaboration

Reference 11

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no resolver link, observed 2026-08-04T08:53:10.728454Z

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source=pdf_text observed=2026-08-04T08:53:10.728454Z digest=sha256:de841c553ece570112155b8c4d109c499f905594a340749b900c46883937846e

Observation 4901f82a-a57c-42de-b1c0-78ada133c982 · outbound

This paper cites Combining pre-trained models for enhanced feature representation in reinforcement learning.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Combining pre-trained models for enhanced feature representation in reinforcement learning

Reference 12

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no resolver link, observed 2026-08-04T08:53:10.781067Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:53:10.781067Z digest=sha256:ae4f7b3b844ceefd5fb20e18c9ed4097ce115d728f251e487e2a19dec105c471

Observation 15bc78ce-de7e-4fe1-b2dc-197a9f7e8d3f · outbound

This paper cites Cliport: What and where pathways for robotic manipulation.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Cliport: What and where pathways for robotic manipulation

Reference 13

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no resolver link, observed 2026-08-04T08:53:10.919202Z

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source=pdf_text observed=2026-08-04T08:53:10.919202Z digest=sha256:5045db50e452da4b865436e719e1f35c0b855fa371d76297f854e9d1676e00a7

Observation 1deccd9b-c616-4355-9c77-9d2336092ff6 · outbound

This paper cites ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI

Reference 14

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source=pdf_text observed=2026-08-04T08:53:11.030091Z digest=sha256:ad1adf44ba7acff56324802d6c2efc5ab41b3cdd0e9cc93e88329def921da2e2

Observation 21f2c5a5-5622-46f0-b327-d2fe3cf6b05a · outbound

This paper cites Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning

Reference 15

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source=pdf_text observed=2026-08-04T08:53:11.108898Z digest=sha256:51fd57d821a1058d332ce84fca6604acb36a78e97894ce5841906af6a8435bd7

Observation f8584bb6-6771-4b15-918e-7ed551f020d0 · outbound

This paper cites RT-2: vision-language-action models transfer web knowledge to robotic control.

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents RT-2: vision-language-action models transfer web knowledge to robotic control

Reference 16

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no resolver link, observed 2026-08-04T08:53:11.182928Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:53:11.182928Z digest=sha256:46fc83458ed11ccf8546261da7df80a46d35102a0c8af693a3b25ccf3145a0d1

Pith citing papers

No inbound Pith citation observations are available.