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Paper Citation Record · LEDGER

Foundation Models for Decision Making: Problems, Methods, and Opportunities

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:2303.04129.

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

pith.paper-citation-record.v1
2303.04129 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 29 of 29 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:57:44.066130Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:39:58.451883Z

Reference resolution

0 of 0 outbound references displayed

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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 2590c633-2cc6-493d-a207-2148573d7810 · inbound

Language Models can Solve Computer Tasks cites this paper.

Language Models can Solve Computer Tasks Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 76

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arxiv_id, observed 2026-05-17T12:17:26.682394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-17T12:17:26.602361Z digest=sha256:0798ccef107d04a56d6d5c1b59696272d347ccd32cf9642fd14e95428a3b271c

Observation c26a2d5b-75c0-48f5-ac27-cd8c6f487c2f · inbound

Understanding the planning of LLM agents: A survey cites this paper.

Understanding the planning of LLM agents: A survey Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 52

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arxiv_id, observed 2026-05-13T18:12:57.629823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-13T18:12:57.568144Z digest=sha256:df07e4c88bf03ebdb746f9bf13f99adde845d44b129cfdd323c5efdde1553b1c

Observation 14c7ac0d-212a-4d92-82a4-463589143ecf · inbound

Learning to Ask: When LLM Agents Meet Unclear Instruction cites this paper.

Learning to Ask: When LLM Agents Meet Unclear Instruction Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 31

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arxiv_id, observed 2026-05-23T21:13:28.121286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-23T21:08:42.276002Z digest=sha256:394dc657e9d76d1c5d727e388aca3b2cf02878d99b57937cfc85fcc663f58bc1

Observation 39c8aaca-5a43-4013-80eb-213b9b8df4aa · inbound

ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation cites this paper.

ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 93

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arxiv_id, observed 2026-05-16T08:25:18.166864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T08:25:17.847571Z digest=sha256:d738ce9d38edb6510dd4483e19a14e00b914a2208550b501fd16e0c0d41f2540

Observation a2a14654-2623-4e22-a15b-95ead8ce24a2 · inbound

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning cites this paper.

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 67

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no resolver link, observed 2026-08-12T19:57:44.066130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:57:44.066130Z digest=sha256:0b7946eddbbc4958ac68a292093e35c0192f9cab58d9abca54690a2945060a3c

Observation f240a42b-c672-45d7-bc57-3cc091ada8ee · inbound

Preference Goal Tuning: Post-Training as Latent Control for Frozen Policies cites this paper.

Preference Goal Tuning: Post-Training as Latent Control for Frozen Policies Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 52

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arxiv_id, observed 2026-05-23T08:22:44.254983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-23T08:20:05.898025Z digest=sha256:0788edbd32199b06d93821ddbc08c19d9ecdc66932c115e2024579a7785578d4

Observation d6cf7dc1-2b37-4583-80c2-127c8ccf48d1 · inbound

The Role of Task Complexity in Reducing AI Plagiarism: A Study of Generative AI Tools cites this paper.

The Role of Task Complexity in Reducing AI Plagiarism: A Study of Generative AI Tools Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 53

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no resolver link, observed 2026-08-11T13:12:29.538375Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:12:29.538375Z digest=sha256:0deffc013a3cec1073b82fd4c5302679a8cd013823c6f18fc4af820bcd09c956

Observation 51842706-d741-4bef-bb3a-df6e446fffcb · inbound

Humanlike Cognitive Patterns as Emergent Phenomena in Large Language Models cites this paper.

Humanlike Cognitive Patterns as Emergent Phenomena in Large Language Models Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 45

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no resolver link, observed 2026-08-11T11:24:53.119576Z

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source=pdf_text observed=2026-08-11T11:24:53.119576Z digest=sha256:b979c3797031a686c822f6c846500693d9e1822587703e06e664e96dbfacadac

Observation 4186d085-3db1-4fd2-82ae-74118f533459 · inbound

Beyond Text: Implementing Multimodal Large Language Model-Powered Multi-Agent Systems Using a No-Code Platform cites this paper.

Beyond Text: Implementing Multimodal Large Language Model-Powered Multi-Agent Systems Using a No-Code Platform Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 19

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no resolver link, observed 2026-08-10T22:46:05.702757Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:46:05.702757Z digest=sha256:6a8b9bf73b2280bcbec170e64bb9b1e43cc2bc5323111ad04ddd0a0c2be2f702

Observation 76c26c9d-96bb-4daa-a346-f4f40bcf93fc · inbound

OmniManip: Towards General Robotic Manipulation via Object-Centric Interaction Primitives as Spatial Constraints cites this paper.

OmniManip: Towards General Robotic Manipulation via Object-Centric Interaction Primitives as Spatial Constraints Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 51

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source=pdf_text observed=2026-08-10T21:50:41.387944Z digest=sha256:dbfab9f86ee029baf13563948b2a93e4f1e852d1eb3b49bbebd61eb86023497f

Observation 6650efd3-ad27-4f96-909c-044640feb55f · inbound

Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning cites this paper.

Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 134

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no resolver link, observed 2026-08-09T17:58:36.313478Z

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source=pdf_text observed=2026-08-09T17:58:36.313478Z digest=sha256:ace1c4fe550b106d056cdba483c8cb021407f052409af12200b5e5bf201b29ff

Observation 91bf319a-ecd2-4254-aeb7-df7068cf1e9f · inbound

Robot Operation of Home Appliances by Reading User Manuals cites this paper.

Robot Operation of Home Appliances by Reading User Manuals Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 16

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no resolver link, observed 2026-08-07T13:59:19.086308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:59:19.086308Z digest=sha256:9eabec4b1fedb366cee0752064034b2ab92c9ae5571826bc88b814575b4f38e3

Observation c3cd9246-9068-4d15-94b0-811c1f89e145 · inbound

PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations cites this paper.

PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 91

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no resolver link, observed 2026-08-07T12:35:43.148867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:43.148867Z digest=sha256:cdaa4fd0aee2bf9af12085df520229bfae3864213d6beedc6148256e7b9b6a98

Observation e93e8ece-734e-48d8-ac24-14f4972fb4fd · inbound

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation cites this paper.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 90

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no resolver link, observed 2026-08-07T04:58:53.629901Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:53.629901Z digest=sha256:c821455bd89c1af8193baa2d2004c40d1cbafbd715e0dec80aba09acbfd72bbb

Observation 7bce264b-f0c1-4ebf-b544-77f7ab8cfd8c · inbound

Towards Efficient and Effective Alignment of Large Language Models cites this paper.

Towards Efficient and Effective Alignment of Large Language Models Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 197

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no resolver link, observed 2026-08-07T04:55:43.138807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:55:43.138807Z digest=sha256:c13f1c205d4bbe42501d877a1a5b415eb7fb9657d7e495c8b63df66678582f4f

Observation 8c29bd59-3681-4b3b-a308-f23a2617ccc8 · inbound

CodeDiffuser: Attention-Enhanced Diffusion Policy via VLM-Generated Code for Instruction Ambiguity cites this paper.

CodeDiffuser: Attention-Enhanced Diffusion Policy via VLM-Generated Code for Instruction Ambiguity Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 81

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no resolver link, observed 2026-08-06T23:43:17.295896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:43:17.295896Z digest=sha256:dd6b15d34caade4a0ae09e0744b9c740869ba8ad697ec51e62aa3a5cd69755ca

Observation 87235990-9198-4b19-b7ab-7f4b8e95b113 · inbound

Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning cites this paper.

Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 37

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no resolver link, observed 2026-08-06T21:35:36.966715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:35:36.966715Z digest=sha256:4784f9d3378a7f65a616e8d6a78c8afcd245535b34c492f186b431714be0c891

Observation 8307a745-9dcb-4c56-8e5b-943ebc6b5929 · inbound

A Review of Generative AI in Aquaculture: Foundations, Applications, and Future Directions for Smart and Sustainable Farming cites this paper.

A Review of Generative AI in Aquaculture: Foundations, Applications, and Future Directions for Smart and Sustainable Farming Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 102

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no resolver link, observed 2026-08-06T17:00:25.862823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:00:25.862823Z digest=sha256:77dd45b36c6a34df24863715ed3b21e3cec4e78c2bee8582f239e92a62366593

Observation b1546250-12ad-4db4-a0df-added7ae678e · inbound

A Study on the Framework for Evaluating the Ethics and Trustworthiness of Generative AI cites this paper.

A Study on the Framework for Evaluating the Ethics and Trustworthiness of Generative AI Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 12

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verified exact
arxiv_id, observed 2026-05-18T19:56:49.528132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T19:53:17.049961Z digest=sha256:7d6c62ef6ee55b295abbdf5b5b4333fcac5f20d91c11d3ff46405c023828a5ce

Observation 255de7a6-6cc6-4652-9f1b-8e55059c3b44 · inbound

Embodied Spatial Intelligence: from Implicit Scene Modeling to Spatial Reasoning cites this paper.

Embodied Spatial Intelligence: from Implicit Scene Modeling to Spatial Reasoning Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 192

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:38:11.959304Z digest=sha256:4a985734c408ae1ccae08e7dfbf3273fa02d47a32111e70486911d2204b459f8

Observation 6ebddc39-80ae-4a45-9016-65412c7343d6 · inbound

CLaRE-ty Amid Chaos: Quantifying Representational Entanglement to Predict Ripple Effects in LLM Editing cites this paper.

CLaRE-ty Amid Chaos: Quantifying Representational Entanglement to Predict Ripple Effects in LLM Editing Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 5

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arxiv_id, observed 2026-05-15T12:55:37.973876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-15T12:52:00.086156Z digest=sha256:45076cf9b51400e5916ce88bd2621997f1c9d840531a5bcf44ec4cbb8d3a6829

Observation 93bcd15d-8ec7-41a1-9a75-629df635eac9 · inbound

MARL-GPT: Foundation Model for Multi-Agent Reinforcement Learning cites this paper.

MARL-GPT: Foundation Model for Multi-Agent Reinforcement Learning Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 48

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arxiv_id, observed 2026-05-10T22:30:51.942993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T19:47:26.815228Z digest=sha256:549669505e5a62fe293aeba7d58d6fcb07a137e4ca03e8aeca2542241fcecff1

Observation 3c0d286e-6097-4695-a03d-cf5631603fcc · inbound

Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding cites this paper.

Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 15

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arxiv_id, observed 2026-05-11T03:45:56.211230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-11T02:21:23.325806Z digest=sha256:c80faf1bd67221b106d91059c2363224e8219566c122a2ed7fbf4d92b0259cad

Observation 76f55fee-1cd5-4204-bd54-538e6bb76ddf · inbound

Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding cites this paper.

Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 15

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arxiv_id, observed 2026-05-13T07:42:30.541902Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-13T07:41:12.038619Z digest=sha256:caecfa4b7e1be07d3292ecbea22b82dc2a8452146c5b012601fba762be49ffba

Observation ce7f0e15-a724-4706-8a9c-60d8247d348d · inbound

GOAL: Graph-based Objective-Aligned Diffusion Solvers for Dynamic Multi-Objective Optimization cites this paper.

GOAL: Graph-based Objective-Aligned Diffusion Solvers for Dynamic Multi-Objective Optimization Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 48

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arxiv_id, observed 2026-05-20T07:18:07.098935Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T07:14:39.757279Z digest=sha256:0d03957e127bdca6f3ed073704ebc0cdfcc1ebc2c622dff890eb5e0d69f8f7e5

Observation 42f411df-a892-4349-99e0-85aaedfa56ca · inbound

QMFOL: Benchmarking Large Language Model Reasoning via Quantifiable Monadic First-Order Logic Test Case Generation cites this paper.

QMFOL: Benchmarking Large Language Model Reasoning via Quantifiable Monadic First-Order Logic Test Case Generation Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 38

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arxiv_id, observed 2026-07-04T03:59:33.517709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T17:24:52.879065Z digest=sha256:3fb6d039141a8285f1cbf39466e9617046261f6bb0ec251ab8967f5ebd68b17d

Observation 5564bfd7-63bc-4150-ba56-a04cdb6a8d66 · inbound

RoBoSR: Structured Scene Representations for Embodied Robotic Reasoning cites this paper.

RoBoSR: Structured Scene Representations for Embodied Robotic Reasoning Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 10

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arxiv_id, observed 2026-07-04T16:39:58.453389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T00:18:58.206705Z digest=sha256:fb0f1b705626964457be5b80879531f2cee308b92fbe99f64f4e4983beb7cc46

Observation b2429258-3301-4cdd-9920-10d958868af3 · inbound

Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Execution cites this paper.

Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Execution Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 25

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no resolver link, observed 2026-08-02T02:06:26.321553Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T02:06:26.321553Z digest=sha256:24951ab89759c03a67433f7f99a668fd074782a01e70f75ad2a766999ed7638e

Observation 37c164a4-f77a-43b2-8b47-22559c25b6f3 · inbound

SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information cites this paper.

SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 117

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no resolver link, observed 2026-08-12T19:21:59.376147Z

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source=arxiv_source observed=2026-08-12T19:21:59.376147Z digest=sha256:a3cd61352fb1ed22f4f88afd75f34b5b81a0ec3f15f45e8d88981e8f90bfd6c1