Pith. sign in

Paper Citation Record · LEDGER

Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2404.07353.

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

pith.paper-citation-record.v1
2404.07353 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:31:12.935446Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:09:50.031494Z

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 b7ff9c6a-a837-494a-853f-9091c40c2ed4 · inbound

Abductive Symbolic Solver on Abstraction and Reasoning Corpus cites this paper.

Abductive Symbolic Solver on Abstraction and Reasoning Corpus Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T11:31:12.935446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:31:12.935446Z digest=sha256:eb0be3e838f74275269eae1c638aa1254189db75a2d366011a36c74f9c646592

Observation 4d187335-4b3c-4224-aa04-64d8431bd3d3 · inbound

EcoSearch: A Constant-Delay Best-First Search Algorithm for Program Synthesis cites this paper.

EcoSearch: A Constant-Delay Best-First Search Algorithm for Program Synthesis Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T05:44:31.109648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:44:31.109648Z digest=sha256:9f141d360a72f6e5d1bde05c665b34362a8973f83c05c88ea5ab7c964c9f8981

Observation 3a34c39c-40b3-45fa-b69e-c5f9471dbeb5 · inbound

The role of positional encodings in the ARC benchmark cites this paper.

The role of positional encodings in the ARC benchmark Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T19:59:12.436611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:59:12.436611Z digest=sha256:cf02b90768e1de2c8ec231fc1031cd93d5a83e7983e05b6a4b68e86e78d10bee

Observation 00d65a84-0b6f-4410-a3f4-a1674f6b4720 · inbound

The role of positional encodings in the ARC benchmark cites this paper.

The role of positional encodings in the ARC benchmark Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-09T19:59:12.440764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:59:12.440764Z digest=sha256:ff0ab152fdc309f04803f5ad5a3be5518f0f7cb4cdc6d388f27f6b34ffbc326e

Observation c79aa9ea-5071-4214-a99b-faa88fc614d4 · inbound

From Reasoning to Generalization: Knowledge-Augmented LLMs for ARC Benchmark cites this paper.

From Reasoning to Generalization: Knowledge-Augmented LLMs for ARC Benchmark Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T14:50:53.144820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:50:53.144820Z digest=sha256:882bb4cbc5713a51b6687e2471046b76a820d505ca1d7e1f006bab3a2b6737dd

Observation a6dc8f4f-2e9a-4306-a004-505d356cc263 · inbound

GIFARC: Synthetic Dataset for Leveraging Human-Intuitive Analogies to Elevate AI Reasoning cites this paper.

GIFARC: Synthetic Dataset for Leveraging Human-Intuitive Analogies to Elevate AI Reasoning Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:53.534519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:53.534519Z digest=sha256:d75abd4fe5b3b60979e1033c46796c8773b269561e5f94b0abba464c847d5b02

Observation 108773d4-fbb1-4ee2-889b-4865f2505a0d · inbound

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks cites this paper.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:42.106854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:42.106854Z digest=sha256:180aa181caf13c9e982072be80c2dacf75142fa6ce1f0ef5324f0750d493e414

Observation fcbb218d-860d-41db-b9a5-96a9d3896751 · inbound

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models cites this paper.

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 164

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:05:09.093993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-10T04:56:35.796962Z digest=sha256:b998857e0961e0b1cfaa84f3515994b38fbda85501174208509d434e27e90952

Observation d1b58157-b5f7-4b4a-980c-e1c579511916 · inbound

Slots, Transitions, Loops: Learning Composable World Models for ARC cites this paper.

Slots, Transitions, Loops: Learning Composable World Models for ARC Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:37:56.821794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-27T09:55:40.978838Z digest=sha256:43a38595b38327f217887aba1d920f0f9574f2e01f75cd605c565163d94eb006

Observation 34753d3b-497c-4259-be34-2ff0be16c5f3 · inbound

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale cites this paper.

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:17:25.458601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-07-02T22:10:59.568675Z digest=sha256:38e03b4534d45a04aaba0604ca86524d3aab3ef371116860b2aa4683f45f2309

Observation 1f2d5690-f596-4361-a89d-f1233672292e · inbound

DiARC: Distinguishing Positive and Negative Samples Helps Improving ARC-like Reasoning Ability of Large Language Models cites this paper.

DiARC: Distinguishing Positive and Negative Samples Helps Improving ARC-like Reasoning Ability of Large Language Models Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:09:50.033638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-26T05:32:59.640335Z digest=sha256:de3e8b87573d09e81ff847629a41ea3519e0b6b27d6812a3b6e773c1f4f5e6d8

Observation 9d14954c-6451-4daf-855b-a8b4ce06d5fc · inbound

DiARC: Distinguishing Positive and Negative Samples Helps Improving ARC-like Reasoning Ability of Large Language Models cites this paper.

DiARC: Distinguishing Positive and Negative Samples Helps Improving ARC-like Reasoning Ability of Large Language Models Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-29T17:23:45.523947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-29T05:19:07.877346Z digest=sha256:80f8907d4fa77bc6ee1994b13c7f6b5cc97a50f3c2f724490ec1d44bee10e4cc

Observation aaf29b1e-ac5a-4427-8f27-ff5670152d15 · inbound

Modality-Driven Search with Holistic Trace Judging for ARC-AGI-2 cites this paper.

Modality-Driven Search with Holistic Trace Judging for ARC-AGI-2 Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T10:25:41.645971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-01T05:33:22.524746Z digest=sha256:f2f7eb75b7cfae8a6d3ee9fa4c39bdf2a51035fd2638f6f2c631d3d052bab068

Observation 3e7421be-3102-4dd4-94be-54240d829534 · inbound

From Global to Factor-Wise Expert Composition in Discrete Diffusion Models cites this paper.

From Global to Factor-Wise Expert Composition in Discrete Diffusion Models Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-07-14T03:24:09.456287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T03:24:09.456287Z digest=sha256:19d9827d853aa40db29129bd44e1df44eba0c2af970b45df2363a9b7336d9799

Observation bc71134f-ae03-41d1-898d-8a8b2cf267ae · inbound

TraceViT: Grounded Trace Supervision for Visual Abstract Reasoning cites this paper.

TraceViT: Grounded Trace Supervision for Visual Abstract Reasoning Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-03T04:06:55.828772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T04:06:55.828772Z digest=sha256:702b421897763176d0108c5d53fa7739cf5d1ab577f1c2e8c72369c5b9eeec36

Observation 165b4248-4d4d-41e8-ae31-4d301dd7c12c · inbound

Recursive Vision Language Models for General Symbolic Reasoning cites this paper.

Recursive Vision Language Models for General Symbolic Reasoning Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T00:11:25.481855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:11:25.481855Z digest=sha256:a757cb29a62b1dbca18b4d36872a0daf2c3fc0b407d741b1a490da3f177aa44f