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Paper Citation Record · LEDGER

Relational Programming with Foundation Models

As of 12 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2412.14515.

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

pith.paper-citation-record.v1
2412.14515 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:13:21.639033Z

measured 57 of 57 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 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

57 of 57 outbound references displayed

  • verified exact3
  • verified fuzzy5
  • unresolved49
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ce10464-e296-47a5-b64f-b42f2dd563f7 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Relational Programming with Foundation Models , " * write output.state after.block = add.period write newline

Reference 1

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.355643Z digest=sha256:eea9d15c54cabe5d78de63c78f2dff94b98a0d6a1cee629548a12bec00020484

Observation cc0eebda-da3f-4ddd-9b25-edd2aea768e9 · outbound

This paper cites write newline.

Relational Programming with Foundation Models write newline

Reference 2

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source=arxiv_source observed=2026-08-11T12:13:21.360474Z digest=sha256:0d2eb8a6efba0b31e32d23ff7c2f334076231aa79b8547933d4c317f58abfd56

Observation c79d777c-9596-477e-bafb-d5339ca4ded0 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 3

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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=arxiv_source observed=2026-08-11T12:13:21.364083Z digest=sha256:57bc24c29e1867c0ebe96e9475d1d8cf08f412fe76ff7fd902ce00e30d0df46e

Observation 08497700-5624-442f-ba54-5208905eda97 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 4

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

source=arxiv_source observed=2026-08-11T12:13:21.367393Z digest=sha256:04314b0117930f762db7b026ad3d0b4812ede2b8d7102e04a1270502dbd84a09

Observation 5bac6d8a-be7b-4044-9ced-3e125614416f · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 5

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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=arxiv_source observed=2026-08-11T12:13:21.370767Z digest=sha256:59d05902d7b4c361252c2b916b26e552bb775ee3fecffe637a5a0619df87cf9e

Observation 08f93329-b04b-4fa9-85f0-a625b4f173f8 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Relational Programming with Foundation Models On the Opportunities and Risks of Foundation Models

Reference 6

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source=arxiv_source observed=2026-08-11T12:13:21.373876Z digest=sha256:d22d77ff2d30114e774d2405a04edbf9b9216c6a4e9500ae3022afaf80aaed57

Observation 17b58c6a-19b7-46cb-bbd7-041225f24725 · outbound

This paper cites InstructPix2Pix: Learning to Follow Image Editing Instructions.

Relational Programming with Foundation Models InstructPix2Pix: Learning to Follow Image Editing Instructions

Reference 7

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source=arxiv_source observed=2026-08-11T12:13:21.378477Z digest=sha256:441e25ff6e005c3f45b693c71b3fd32c5310c6ac75a051e97b2295ffdde12a3b

Observation cdd4a418-f2e1-42e4-9233-786587029ab9 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Relational Programming with Foundation Models Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 8

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source=arxiv_source observed=2026-08-11T12:13:21.382502Z digest=sha256:95136b601fe5e53f784d067c2af1680e4925f59ad09a15f34fb0eccd79fcff3e

Observation 709b4c5c-38fb-4733-b762-3401970e8cdd · outbound

This paper cites W.; Zhou, D.; Song, D.; and Le, Q.

Relational Programming with Foundation Models W.; Zhou, D.; Song, D.; and Le, Q

Reference 9

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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=arxiv_source observed=2026-08-11T12:13:21.386612Z digest=sha256:18bbc61d80237e4bdcd88b648e78d36bad5ca06950d71a0ff2a720bc54e21875

Observation d0b6d193-ef15-4753-b488-795d27d47ca8 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Relational Programming with Foundation Models Training Verifiers to Solve Math Word Problems

Reference 10

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source=arxiv_source observed=2026-08-11T12:13:21.389533Z digest=sha256:496bfada0d60d8e376f16c33d4ecc693b3d69a580b5351adea888de21baa0fd5

Observation 4b93e877-ac11-4e70-8cbb-61543273a64e · outbound

This paper cites Testing GPT-4 with Wolfram Alpha and Code Interpreter plug-ins on math and science problems.

Relational Programming with Foundation Models Testing GPT-4 with Wolfram Alpha and Code Interpreter plug-ins on math and science problems

Reference 11

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source=arxiv_source observed=2026-08-11T12:13:21.393829Z digest=sha256:47edaf27435a87c07e296e771b44bd4d1d8853288ef2a818d0ea089392b39774

Observation 5ec4143d-486b-4195-b4c9-c53a409f439c · outbound

This paper cites PAL: Program-aided Language Models.

Relational Programming with Foundation Models PAL: Program-aided Language Models

Reference 12

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source=arxiv_source observed=2026-08-11T12:13:21.397400Z digest=sha256:48bdc66647ab1cc2252b60b0061e3a27ddaf3d02bbfc9f7535475f68a55e3174

Observation 28e812d9-a7f9-409e-9fad-6f9edc821321 · outbound

This paper cites Visual Programming: Compositional visual reasoning without training.

Relational Programming with Foundation Models Visual Programming: Compositional visual reasoning without training

Reference 13

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source=arxiv_source observed=2026-08-11T12:13:21.402018Z digest=sha256:c9f120094b4e5ccb14b0093369a7a7e8f7394e35899c337fd335556d3927a74e

Observation 0746855f-33eb-448f-830f-6387eee294e9 · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

Relational Programming with Foundation Models Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 14

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.406492Z digest=sha256:50379f855cb250860ebc970692d4ebe7a5374996540653b9b04934db87687670

Observation d53c3146-8c69-41b6-85f5-3bd2afbab6fb · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 15

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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=arxiv_source observed=2026-08-11T12:13:21.410842Z digest=sha256:3cffe36e7381f4de519c8a72da5b545b1aaa867e4e73bfba5c0903edea12fa34

Observation b7e567a3-46ff-4dfc-bac5-c7bad6e1c15a · outbound

This paper cites GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering.

Relational Programming with Foundation Models GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering

Reference 16

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source=arxiv_source observed=2026-08-11T12:13:21.413671Z digest=sha256:abd97f83becd6ba0a1b3b4aa196ac549ac541ad2c80452795eeaa800e5e268f9

Observation be93e67d-896d-4d26-a556-1b5eb0f96548 · outbound

This paper cites CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning.

Relational Programming with Foundation Models CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

Reference 17

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source=arxiv_source observed=2026-08-11T12:13:21.418101Z digest=sha256:1bbe49d6fd912beadee0f6163801a794daac50379cee657e099cb091847e2b44

Observation d7ca3a37-f02d-4ec6-99e1-38073ef829e2 · outbound

This paper cites ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision.

Relational Programming with Foundation Models ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision

Reference 18

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source=arxiv_source observed=2026-08-11T12:13:21.422734Z digest=sha256:bd0eace48718d9e93836f07f499a84a80390c692abbf3c09b9276d5c19a7ff6b

Observation 2036e379-188b-4926-96a0-c464f3d53094 · outbound

This paper cites Segment Anything.

Relational Programming with Foundation Models Segment Anything

Reference 19

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source=arxiv_source observed=2026-08-11T12:13:21.426483Z digest=sha256:846401a8df4866a146813ef0e1bdc19f68debebe8ee3ee0885449a014a458d38

Observation 6409240f-1afd-4d61-bde7-0c5687678646 · outbound

This paper cites S.; Reid, M.; Matsuo, Y.; and Iwasawa, Y.

Relational Programming with Foundation Models S.; Reid, M.; Matsuo, Y.; and Iwasawa, Y

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-11T12:13:22.424504Z

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=arxiv_source observed=2026-08-11T12:13:21.429894Z digest=sha256:f330a39d3b6721c4eb31124ebb1ef727b09f3026365da3b50a569b529102e055

Observation bc34e9f3-e422-4c69-b963-87f3e09ae614 · outbound

This paper cites DSFD: Dual Shot Face Detector.

Relational Programming with Foundation Models DSFD: Dual Shot Face Detector

Reference 21

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local_arxiv, observed 2026-08-11T12:13:21.898573Z

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=arxiv_source observed=2026-08-11T12:13:21.435637Z digest=sha256:48974ddde121559be682bfef463a918dc2038a77bda3b01fea00c8c243f0b9ca

Observation c834dbe1-46a3-4d8f-8ece-5b3e76ef0821 · outbound

This paper cites N.; and Zhu, S.-C.

Relational Programming with Foundation Models N.; and Zhu, S.-C

Reference 22

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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=arxiv_source observed=2026-08-11T12:13:21.442854Z digest=sha256:65d8fb56a73d9080fa6a3e4c739624259ecedb6e5bf867ee9cd5d6800610959d

Observation 5423c0b2-e0e4-46a8-83d5-c917321effd5 · outbound

This paper cites From Easy to Hard: Two-stage Selector and Reader for Multi-hop Question Answering.

Relational Programming with Foundation Models From Easy to Hard: Two-stage Selector and Reader for Multi-hop Question Answering

Reference 23

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local_arxiv, observed 2026-08-11T12:13:21.885060Z

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

source=arxiv_source observed=2026-08-11T12:13:21.451052Z digest=sha256:f6141f09b15a160e8d261eef8b01ccbb59dd0568265a8b73120d5a8466b24da0

Observation f0e10005-0ee4-4b23-9299-513c36e75f76 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 24

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

source=arxiv_source observed=2026-08-11T12:13:21.461944Z digest=sha256:6384e4ae30d9d4c7cb1f46f0515d0f1755541ac1df5b1e4a2f85381d9db8cbe7

Observation 88af961c-ff46-44d7-9106-02e501644a66 · outbound

This paper cites TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs.

Relational Programming with Foundation Models TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs

Reference 25

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source=arxiv_source observed=2026-08-11T12:13:21.466544Z digest=sha256:c56651d465ba9cbc85e3958eff12d3581f6e619918ede216789854c3ecb5de8d

Observation 8fb6ee43-5748-4347-934b-0184b99fb278 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Relational Programming with Foundation Models RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 26

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source=arxiv_source observed=2026-08-11T12:13:21.470746Z digest=sha256:8db74a7a37d9be029be6f4b77b305113db742e0d793dbcb9d819c9be1f04aef0

Observation 2cc8d93f-a1e4-4cea-a860-00edcdcd7325 · outbound

This paper cites Faithful Chain-of-Thought Reasoning.

Relational Programming with Foundation Models Faithful Chain-of-Thought Reasoning

Reference 27

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source=arxiv_source observed=2026-08-11T12:13:21.474093Z digest=sha256:8398d230cb759e1af17374a880ceb8f0a47d5daf3b58efd3bf85b4915c244684

Observation d067b25a-35e6-4945-9e0e-7be5be86b9af · outbound

This paper cites DeepProbLog: Neural Probabilistic Logic Programming.

Relational Programming with Foundation Models DeepProbLog: Neural Probabilistic Logic Programming

Reference 28

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source=arxiv_source observed=2026-08-11T12:13:21.477796Z digest=sha256:a87f742032a611316b5b25edd03284c1cd1b353460fda9beeb4e814e9c37e02e

Observation f966759a-fbfe-4224-aba6-912c2650d979 · outbound

This paper cites The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision.

Relational Programming with Foundation Models The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

Reference 29

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source=arxiv_source observed=2026-08-11T12:13:21.481602Z digest=sha256:b0a3928382319e3beff55f69743051c19f13f1b6a057d2163003d8fb5445b840

Observation 4367ff7d-7ac0-46a7-b027-e912aa5c1843 · outbound

This paper cites Sources of Hallucination by Large Language Models on Inference Tasks.

Relational Programming with Foundation Models Sources of Hallucination by Large Language Models on Inference Tasks

Reference 30

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source=arxiv_source observed=2026-08-11T12:13:21.484582Z digest=sha256:42b244727bf8c6ed8513dc0a379a374221d8f956a0d386ab255b933e5a2c3a6d

Observation c7af9a74-44ad-4fff-85d0-3dc25e574b62 · outbound

This paper cites Simple Open-Vocabulary Object Detection with Vision Transformers.

Relational Programming with Foundation Models Simple Open-Vocabulary Object Detection with Vision Transformers

Reference 31

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source=arxiv_source observed=2026-08-11T12:13:21.488083Z digest=sha256:e3b20404b5703dcdc1f80005641b3e7e917aa308a2c2681df28d5a5ff4d9b229

Observation 134bb0c7-29e0-45b6-bdda-1310e98978f1 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-11T12:13:22.292850Z

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=arxiv_source observed=2026-08-11T12:13:21.492256Z digest=sha256:da1e46e7f766d2a983d9f6e9986999103d55b8f0a2b79638b3df4806af4c58bf

Observation 6c6a49de-9dca-4e7d-b5a9-6c8c636ca927 · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

Relational Programming with Foundation Models WebGPT: Browser-assisted question-answering with human feedback

Reference 33

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.495507Z digest=sha256:e1cf1e89493592f49fb02156a1c599249fecbb298103cc05fc2b8ba512829881

Observation b52e6a14-2792-46ef-a395-50cad963b93e · outbound

This paper cites Passage Re-ranking with BERT.

Relational Programming with Foundation Models Passage Re-ranking with BERT

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.499709Z digest=sha256:63d0f327469cc961fa5b1cde8d19531fd1a49c9531e3fbc9b9596c729f7db111

Observation 0914caae-6b5a-4977-8e54-2369cfb86c1d · outbound

This paper cites GPT-4 Technical Report.

Relational Programming with Foundation Models GPT-4 Technical Report

Reference 35

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source=arxiv_source observed=2026-08-11T12:13:21.503781Z digest=sha256:1346b9d659fa0be5d0ba51c5e44690a639502eec50e6673166c79771a8962d42

Observation 5e03ea82-2bdd-4dd6-8769-bab7832b808d · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Relational Programming with Foundation Models Learning Transferable Visual Models From Natural Language Supervision

Reference 36

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.506917Z digest=sha256:09268e2a89ec9fb01020a9dbf857f2832dca5c3c9e8d0816e7ac9ae81ac56180

Observation 172bc153-6bd5-4791-b312-8388a78ec8bb · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-11T12:13:22.244291Z

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=arxiv_source observed=2026-08-11T12:13:21.510606Z digest=sha256:c3afb21c225744bc40a3c2f8c75c0c604386635ec434606bf5f927b2fd650794

Observation 1741b791-aeeb-4082-9914-bd6893c03286 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 38

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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=arxiv_source observed=2026-08-11T12:13:21.513633Z digest=sha256:bd17b61e481f8d94bb139e05e11cfc764795c38fe92bdb66b61913bd98a66f77

Observation 42b14909-3154-4ee0-976a-0651d53d4367 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 39

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raw_fallback, observed 2026-08-11T12:13:22.106649Z

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=arxiv_source observed=2026-08-11T12:13:21.533257Z digest=sha256:80036ba12d884b25f3e4b3e041a697d2cfda5a181603de20e2aa232fabdcf092

Observation bcece366-1d33-4f7e-a3ef-faaf8bbb7391 · outbound

This paper cites Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search.

Relational Programming with Foundation Models Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.557499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.557499Z digest=sha256:29615fc8f80f2ea71569ee45faa64f2b8939b8bd94c2f7e33068cdf6d302ef8e

Observation dc5e4221-54a5-4719-a637-1414e0c0faa0 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:13:22.066829Z

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=arxiv_source observed=2026-08-11T12:13:21.581269Z digest=sha256:1f93e4723c18db71892f701d65d7802ab1fb4c9e75e68231fd0f1dd5d52880a9

Observation cb14ae2c-d526-4ef5-bfa1-0cfcaeb39b43 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:13:22.055718Z

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=arxiv_source observed=2026-08-11T12:13:21.585094Z digest=sha256:7eaec925cfb74fce13d3e42518cd88e9635cb21da476e9222673d06c70c0f4a7

Observation 148500d2-75f5-4ccb-a90c-39fa97f022b3 · outbound

This paper cites Toolformer: Language Models Can Teach Themselves to Use Tools.

Relational Programming with Foundation Models Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.588772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.588772Z digest=sha256:c3e2ad45d441094bf5154eea769912f0ce7b64dd5b74e4a9d05741e6d8453c1e

Observation c7f542a9-6e2d-468c-9171-3ce6fbc184a2 · outbound

This paper cites CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text.

Relational Programming with Foundation Models CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.593237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.593237Z digest=sha256:4ec91c1352823d2487047307417932435323b28e20f33c8b41a9df95178864c1

Observation eda2b044-acef-4450-a236-a22d506104be · outbound

This paper cites MPNet: Masked and Permuted Pre-training for Language Understanding.

Relational Programming with Foundation Models MPNet: Masked and Permuted Pre-training for Language Understanding

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.597025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.597025Z digest=sha256:efe6349ecc5c6642d322c4090ced349fd5105fd23ea20d77cd428653df26f906

Observation 39feccbe-0adc-43cf-ab58-bfbf00ab087e · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Relational Programming with Foundation Models Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.600201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.600201Z digest=sha256:d4904c47aef3ac26f25a231b5a829881400c4e2607387070a8e06148b9bf9871

Observation ba1785ff-41e8-4d65-8ba3-d87df5c95696 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:13:22.042518Z

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=arxiv_source observed=2026-08-11T12:13:21.603727Z digest=sha256:ee43d8a785889d3747dbf623be4ff1f6962968e54a673ae39f67b22e8d637223

Observation 36692e5f-11b3-4a7b-bf2e-3738f3c632cc · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Relational Programming with Foundation Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.607916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.607916Z digest=sha256:25b304be16aceec0a2bbc23195795d5ef9edb6b8d94bc4f0a67a3dcbaec5e3e1

Observation 4b87f03b-a405-4bae-9f3a-e048d9734c2f · outbound

This paper cites L.; Wilder, B.; and Kolter, Z.

Relational Programming with Foundation Models L.; Wilder, B.; and Kolter, Z

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:13:22.030106Z

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=arxiv_source observed=2026-08-11T12:13:21.612473Z digest=sha256:cfb372f440abd93f6ceb4a152d7a8ba6f211dac33ce41343c9d6121c7cd7d030

Observation c194d445-f459-46d8-85a2-d53a94d9ae59 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Relational Programming with Foundation Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.615946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.615946Z digest=sha256:a01ac9a1c093dcf240577d717df32ed53523dee2f81b9586550f730ce961d990

Observation c7244a59-e7b2-4711-a202-0bd804b6d27e · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Relational Programming with Foundation Models Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.620307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.620307Z digest=sha256:d8fb06a9a67cd31da47c21eea640d9e34f971c0f71a2481324e31c515b12eeaf

Observation d09b7782-95d8-4ee5-bf59-b151972182b9 · outbound

This paper cites S.; Wong, Y.; Kankanhalli, M.; and Shah, M.

Relational Programming with Foundation Models S.; Wong, Y.; Kankanhalli, M.; and Shah, M

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:13:22.018678Z

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=arxiv_source observed=2026-08-11T12:13:21.623267Z digest=sha256:5887a828924d33cf1655c03a53693a79164b50baa651251f6140d9cd677fd6fe

Observation ef997bb0-abd5-468e-afa0-558849bbcb86 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

Relational Programming with Foundation Models HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.626991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.626991Z digest=sha256:e39522b6a3441a32c1cf86af9c8424fc4f9fea32ad7ba9de286ec5b78f585bda

Observation d8849403-63f6-48be-bf73-4d0990b96446 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Relational Programming with Foundation Models ReAct: Synergizing Reasoning and Acting in Language Models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.630337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.630337Z digest=sha256:ca253fd8dcbd5c5a77cc31a5f784476af9fc3b2e0922bba1b5ff94457e7027b5

Observation d6a853d7-af05-4220-8bcd-f979075c73d6 · outbound

This paper cites an unresolved cited work.

Relational Programming with Foundation Models Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:13:22.007764Z

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=arxiv_source observed=2026-08-11T12:13:21.633439Z digest=sha256:27320920773e02d4870467d05377076e6a9eb025f92965103b291fa0d9ba98f3

Observation 1c75e611-0cc1-4caf-988e-b179392c3feb · outbound

This paper cites Rethinking Label Smoothing on Multi-hop Question Answering.

Relational Programming with Foundation Models Rethinking Label Smoothing on Multi-hop Question Answering

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-08-11T12:13:21.677079Z

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=arxiv_source observed=2026-08-11T12:13:21.636196Z digest=sha256:fc9b8d14ea68b54a6f1385b6d35f40cbf3e63381e9b4cd93cc957b7f24f5cca5

Observation 74c48a4d-dcd7-413f-a54f-96cb5201f698 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Relational Programming with Foundation Models Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.639033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.639033Z digest=sha256:c149c42b98b7a39faebfbdf746281ebd4714fa20dca84b3c76aa16282088a760

Pith citing papers

No inbound Pith citation observations are available.