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Paper Citation Record · LEDGER

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs

As of 19 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.10527.

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

pith.paper-citation-record.v1
2506.10527 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:28:47.872578Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

38 of 38 outbound references displayed

  • verified exact1
  • verified fuzzy13
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 13daddeb-bf98-4bd7-9a13-2efcb2f7d51f · outbound

This paper cites How far can transformers reason? the globality barrier and inductive scratchpad.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs How far can transformers reason? the globality barrier and inductive scratchpad

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:51.870479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:37.631385Z digest=sha256:f3511d5625bf3a9b7c538e5db72b9fefca3a7928aa04dbf710968be4f11abd1d

Observation 4a180558-2c7b-4523-96ac-45160c5a1113 · outbound

This paper cites Graph of logic: Enhancing llm reasoning with graphs and symbolic logic.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Graph of logic: Enhancing llm reasoning with graphs and symbolic logic

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-07T04:28:51.648962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:39.992525Z digest=sha256:c078fbc7670355f6c356ab4b65aedeb36886ed551bdbec5cd156710328218f24

Observation 5d0623af-db05-4bc4-9540-25aa8c057937 · outbound

This paper cites Claude 3.7 sonnet.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Claude 3.7 sonnet

Reference 3

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raw_fallback, observed 2026-08-07T04:28:51.345069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:40.109199Z digest=sha256:1141ece5ffee1627b6e377bc60f07c30ce2a995a7a491a4cfe34b08d4029007e

Observation 333256f3-6047-47a1-ae20-4dd8f38e1ec4 · outbound

This paper cites Eureka: Evaluating and Understanding Large Foundation Models.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Eureka: Evaluating and Understanding Large Foundation Models

Reference 4

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no resolver link, observed 2026-08-07T04:28:40.218979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:40.218979Z digest=sha256:31e3f9c62687584b82bc191d82485b4cce7afeb2f9bb3acf96bb2e570e250310

Observation cffd9cab-db11-42e7-ada0-fde6f9ff23c5 · outbound

This paper cites The Llama 3 Herd of Models.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs The Llama 3 Herd of Models

Reference 5

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T04:28:40.339630Z digest=sha256:2059c05335179335a25467ce0b27fa853ad61f7fef67244592f6674fc10a762d

Observation ab83d070-3c04-44dc-b9e6-6c70cba195da · outbound

This paper cites NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 6

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no resolver link, observed 2026-08-07T04:28:40.881171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:40.881171Z digest=sha256:b67911f7e49dab76049cba8a51f72c84f1db50bcf4614a08f536c70f0a3d0c90

Observation 52e18b69-3525-43f3-9d0c-641f6da8c5a4 · outbound

This paper cites Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks

Reference 7

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source=arxiv_source observed=2026-08-07T04:28:43.800298Z digest=sha256:e3c2f96d52e5f4028e8765c906f2c166cde566a50cd37961a18dc35feb2c817c

Observation e381ab0e-bd16-476e-afba-2cea2d894a18 · outbound

This paper cites Gemini 2.0 pro experimental.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Gemini 2.0 pro experimental

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-07T04:28:51.060732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:43.913151Z digest=sha256:54b164cbc41f21c8066aa7e3c0ce018486fba419b067ae0050545a0cf95198a0

Observation 6a919f3c-4495-4f5c-a3f8-3db8f25737dd · outbound

This paper cites Gemini 2.0 flash thinking.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Gemini 2.0 flash thinking

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:50.806928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:44.022394Z digest=sha256:e3508b134ca09c2eb40dbd494e6e4d54d9a3c87c1060884dd8ac6e8bead457cd

Observation cdfb6979-b996-405f-b957-0f4421b6c7fe · outbound

This paper cites Reinforced Self-Training (ReST) for Language Modeling.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Reinforced Self-Training (ReST) for Language Modeling

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:44.141478Z digest=sha256:1dae57639da2e344ab6d6e81a8b11767ba32591bf7eb2ef09c06a5847f4c5a52

Observation 1d341136-a6eb-4881-b45a-183389793d9e · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

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source=arxiv_source observed=2026-08-07T04:28:44.268329Z digest=sha256:ad4fba445aa284dfcbd5a6e70b27fad05325adcb0f14bea3db0212574124ed9a

Observation 34041c10-3514-41ee-8637-d2c7787ecfc9 · outbound

This paper cites GPT-4o System Card.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs GPT-4o System Card

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:44.369152Z digest=sha256:5a9f15adcb883f26efd230ad261e52f01348378bab0aeb92c41fa7e8c89cc78d

Observation e0e8ec66-628e-48b0-ab30-204a7afcd6f8 · outbound

This paper cites OpenAI o1 System Card.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs OpenAI o1 System Card

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:44.472582Z digest=sha256:c568ea5f688f1fb9322831d9db0787d16d99a0d2c76fb44f7c7d834eddc2b489

Observation e6c594e3-5fc4-4736-a8c4-6c679e502ebf · outbound

This paper cites Finding all the elementary circuits of a directed graph.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Finding all the elementary circuits of a directed graph

Reference 14

Resolution
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raw_fallback, observed 2026-08-07T04:28:50.551608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:44.662847Z digest=sha256:b66cb6b8c61b46b18d00f636d447439f690a36b85920531f294c0d1ce1aa6716

Observation ee54dd7e-7624-49af-8097-9be19ed5a087 · outbound

This paper cites Same task, more tokens: the impact of input length on the reasoning performance of large language models.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Same task, more tokens: the impact of input length on the reasoning performance of large language models

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:50.304512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:44.779665Z digest=sha256:038a448b07ce7b031d6eadf9b1e82ba53ef764eef5c6f084cb7724c307531f65

Observation 40a4ecee-aee7-46c8-9ade-57a6469fbfae · outbound

This paper cites Large Language Models for Supply Chain Optimization.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Large Language Models for Supply Chain Optimization

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:44.907012Z digest=sha256:f49a4e8eee94b79d29e2bb1b06a63cb73578afccc94fe1266e5393011c79250e

Observation 859e10bb-1161-4366-bb42-3df6f0a3b072 · outbound

This paper cites Llms for relational reasoning: How far are we? In Proceedings of the 1st International Workshop on Large Language Models for Code, pp.\ 119--126, 2024.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Llms for relational reasoning: How far are we? In Proceedings of the 1st International Workshop on Large Language Models for Code, pp.\ 119--126, 2024

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:45.061476Z digest=sha256:1a39ec4f3f097cea5aedb047838a2f30f1074393a4934ac486db68a799e613fa

Observation 75549691-995f-42ec-85b7-bf025908a967 · outbound

This paper cites Let's verify step by step.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Let's verify step by step

Reference 18

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source=arxiv_source observed=2026-08-07T04:28:45.169542Z digest=sha256:b171bebd5f762e9a21603480e6b9eefb310addc2b62932cba2be6b39233ff0cc

Observation 0585ec8d-bfb5-4b8b-8c30-03a8a3682e69 · outbound

This paper cites ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning

Reference 19

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source=arxiv_source observed=2026-08-07T04:28:45.311682Z digest=sha256:54a6db117a63497928d83db640bfb6cf1af080cb4ea42ee93cf9291f8e7b04fa

Observation 1198c1e5-a59f-4cd8-a408-54ed93a49fad · outbound

This paper cites Evaluating cognitive maps and planning in large language models with cogeval.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Evaluating cognitive maps and planning in large language models with cogeval

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:28:49.777154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:45.438885Z digest=sha256:67ba92bcaa6a73259aeb06690fea9349ad34ce633ce8d9e78e0a21409e716750

Observation 71007d16-5174-49f2-af57-cf863ebb13bb · outbound

This paper cites Foster, and Michael W.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Foster, and Michael W

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-07T04:28:49.524885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:45.587781Z digest=sha256:ca05fb78c4d8af8871593e71d423eaf3e2c0c19f564df869f2ab18f8e61b44b2

Observation 8d9ed02d-68bb-4d41-9b87-63c757460c4f · outbound

This paper cites Openai o3-mini system card.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Openai o3-mini system card

Reference 22

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source=arxiv_source observed=2026-08-07T04:28:45.681138Z digest=sha256:14992e308b8aed6f85562c6c72873ae9cc662721a4cbdc49d1369291e7be6f9d

Observation e493e0fb-5ddf-4608-b0c2-eb598dbf49d3 · outbound

This paper cites Logicbench: Towards systematic evaluation of logical reasoning ability of large language models.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Logicbench: Towards systematic evaluation of logical reasoning ability of large language models

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-07T04:28:49.303330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:45.808086Z digest=sha256:d99cf7b90c25b471775e947651b730ee2d15376bfc1c2811673c71becdacca02

Observation eec52d23-b3ff-4bc4-a8f0-e17870037a28 · outbound

This paper cites Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models

Reference 24

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source=arxiv_source observed=2026-08-07T04:28:45.947400Z digest=sha256:b752e1733bd0dc893fc258059fc2e14c93b2b6d86e6c1b4ccb4ee0ca4fdd8f35

Observation 9571dae9-3f7e-403e-a0e1-e884514fadfb · outbound

This paper cites Divide and translate: Compositional first-order logic translation and verification for complex logical reasoning.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Divide and translate: Compositional first-order logic translation and verification for complex logical reasoning

Reference 25

Resolution
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raw_fallback, observed 2026-08-07T04:28:49.020000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:46.143857Z digest=sha256:b14160604523a97633e477c27984cfd06a96a4ade3f799327bdf1deccb8f5921

Observation da054956-7561-4149-95b1-ce862f3536ca · outbound

This paper cites MoreHopQA: More Than Multi-hop Reasoning.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs MoreHopQA: More Than Multi-hop Reasoning

Reference 26

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source=arxiv_source observed=2026-08-07T04:28:46.289978Z digest=sha256:47ee9e664ca44f49dfdc600f799fb798696624eae1b436d637a929d893caee74

Observation 7cfadf7a-1629-496a-aadb-5c31cfd83f56 · outbound

This paper cites Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles

Reference 27

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source=arxiv_source observed=2026-08-07T04:28:46.408842Z digest=sha256:8c1475ccd54a46c2771253a5bfd9249339493fb6cfd515679bf20c55a3576492

Observation d708a61d-0097-4c7d-8de8-c0b73add71d0 · outbound

This paper cites Musique: Multihop questions via single-hop question composition.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Musique: Multihop questions via single-hop question composition

Reference 28

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no resolver link, observed 2026-08-07T04:28:46.557922Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:46.557922Z digest=sha256:97c3b7a52b083c48c5309214dc51b31a4f576d74d62b96118d2d31f74b6cf821

Observation b8a51838-5ab7-44b6-bc01-16188e1fbe78 · outbound

This paper cites Holy Grail 2.0: From Natural Language to Constraint Models.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Holy Grail 2.0: From Natural Language to Constraint Models

Reference 29

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verified exact
local_arxiv, observed 2026-08-07T04:28:48.259984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:46.653749Z digest=sha256:8b1e4e7cae539265d6bd96b845bf4519458c150ae5a405b20dfb1d7484c5430a

Observation 21847219-af4a-477b-958a-87aa8001bb95 · outbound

This paper cites On the planning abilities of large language models-a critical investigation.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs On the planning abilities of large language models-a critical investigation

Reference 30

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no resolver link, observed 2026-08-07T04:28:46.787264Z

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source=arxiv_source observed=2026-08-07T04:28:46.787264Z digest=sha256:2b7a0b9ebdfe990eace37fe013c213e922447286f268e85f424179fc8f3acc30

Observation 16a779d1-6d61-4191-9907-fea88806053e · outbound

This paper cites LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBench.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBench

Reference 31

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:46.939636Z digest=sha256:a5a8724082803330307d474f8ea19a5d23d47249620b620f66ab7efae34cf236

Observation 0a527187-c70f-4ec1-b20d-88839e383437 · outbound

This paper cites Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models

Reference 32

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no resolver link, observed 2026-08-07T04:28:47.081061Z

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source=arxiv_source observed=2026-08-07T04:28:47.081061Z digest=sha256:d6bc4c38738e1ad840fa9eb3fb745e5544b04342376f85a9548d88d5362f6349

Observation eba4517b-6b66-496a-b150-5b5060f6f192 · outbound

This paper cites On The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs On The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability

Reference 33

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no resolver link, observed 2026-08-07T04:28:47.210808Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:47.210808Z digest=sha256:92a749dee5979078cfc82154f71bb9a3cb3639ee4fd46748593ff7f57dadd00a

Observation d6923359-51ac-47db-a56c-e6e919cba353 · outbound

This paper cites Math-shepherd: Verify and reinforce llms step-by-step without human annotations.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Math-shepherd: Verify and reinforce llms step-by-step without human annotations

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-07T04:28:48.740642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T04:28:47.330230Z digest=sha256:4481b9ff9bd2c939a3e76217d238d4c4b75b01b37596dd5637167f6c07083399

Observation 2f3f4aa8-d39d-4e1d-832d-41bd705e4542 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:47.511050Z digest=sha256:8ba4648c24a09b73cd3e4abdb8cbf57a552c7932eb28d2e1a053f2ab7e1b9b93

Observation 4979fd67-1488-487f-acdc-b9661780569c · outbound

This paper cites Faithful Logical Reasoning via Symbolic Chain-of-Thought.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs Faithful Logical Reasoning via Symbolic Chain-of-Thought

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T04:28:47.609701Z

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source=arxiv_source observed=2026-08-07T04:28:47.609701Z digest=sha256:41e2a33f925ada45f7bcaf00256a1e24eb57ff35c4f6dc4463045b741e5bbf95

Observation 5bae4fd2-961f-4349-bb38-18dbad1a73e3 · outbound

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

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T04:28:47.750383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:47.750383Z digest=sha256:3f9ed934d3443da4e03c80e3191f7da90f72dcd7124c7bba8219d10b8fd68496

Observation 3f1b9139-7109-4809-907e-8bb7be6e5fb6 · outbound

This paper cites NATURAL PLAN: Benchmarking LLMs on Natural Language Planning.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs NATURAL PLAN: Benchmarking LLMs on Natural Language Planning

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T04:28:47.872578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:47.872578Z digest=sha256:de9830a50c391adebf38a4608b4efbcf72a34c8a3195e6b361dbac0118199b46

Pith citing papers

No inbound Pith citation observations are available.