Paper Citation Record · LEDGER

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.23128.

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

pith.paper-citation-record.v1
2506.23128 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:52:53.361587Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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 exact0
verified fuzzy18
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d1f53289-5778-4dea-9a20-109edb928886 · outbound

This paper cites Can LLMs Understand Time Series Anomalies?.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Can LLMs Understand Time Series Anomalies?

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:49.656206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7975255f-7e6b-4e78-8932-7e4a6d3b4c54 · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:49.708889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b95299b-207f-41a4-8e36-f5ce10cc7cc1 · outbound

This paper cites Ai for education (ai4edu): Advancing personalized education with llm and adaptive learning,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Ai for education (ai4edu): Advancing personalized education with llm and adaptive learning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:56.942159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fe42046e-6dfb-44d8-b160-f40120b91f5a · outbound

This paper cites Software engineering education must adapt and evolve for an llm environment,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Software engineering education must adapt and evolve for an llm environment,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:56.792680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 80bda44c-ca1e-4b02-83d9-74cabbfc0b44 · outbound

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

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:49.907084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c109a60c-35f4-4498-8206-d91418ebabd6 · outbound

This paper cites How Far Are We From AGI: Are LLMs All We Need?.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons How Far Are We From AGI: Are LLMs All We Need?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:50.000709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ada5798a-386a-4439-86be-a0d10eb93d7b · outbound

This paper cites Llm/gpt generative ai and artificial general intelligence (agi): The next frontier,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Llm/gpt generative ai and artificial general intelligence (agi): The next frontier,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:56.623668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eaa1e2b9-109e-4539-9e06-d948c0c055f4 · outbound

This paper cites A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:50.011424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fddc03b-c5a5-45a7-92f0-7713d61c9e47 · outbound

This paper cites MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:50.075683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c6955fe-5e2f-4772-93fb-cddf08be402c · outbound

This paper cites LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:50.183141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39cdaae2-8420-4d39-b37f-166f700b5415 · outbound

This paper cites LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:50.296981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34213d3b-7975-4c07-9a81-d4bd4953bd30 · outbound

This paper cites Scaling Relationship on Learning Mathematical Reasoning with Large Language Models.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Scaling Relationship on Learning Mathematical Reasoning with Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:50.387120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09809818-7808-456f-a145-b492002d2ebe · outbound

This paper cites Solving math word problems con- cerning systems of equations with gpt models,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Solving math word problems con- cerning systems of equations with gpt models,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:56.439080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fadbb9a9-656e-4799-8064-817476b8558d · outbound

This paper cites The mathematics of deepseek-r1: Theoretical foundations and comparative analysis,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons The mathematics of deepseek-r1: Theoretical foundations and comparative analysis,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:56.282901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 23a0e61b-5557-4fe5-a519-3851bc4a4c88 · outbound

This paper cites Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:56.075027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8e393966-c146-4cf0-ad6c-862c5afce9fe · outbound

This paper cites Neurocognitive development of rela- tional reasoning,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Neurocognitive development of rela- tional reasoning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:55.905548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ee122da3-25e7-433d-96ff-d8f2e9b79bd3 · outbound

This paper cites Processing capacity defined by relational complexity: Implications for comparative, devel- opmental, and cognitive psychology,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Processing capacity defined by relational complexity: Implications for comparative, devel- opmental, and cognitive psychology,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:55.722086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 006d5740-023e-480f-bd1a-656348055bed · outbound

This paper cites Llms for relational reasoning: How far are we?.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Llms for relational reasoning: How far are we?

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:55.540805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a6e3f251-1ffb-4d9f-adb1-5fd8e2ad0803 · outbound

This paper cites How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:51.306115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d728047-ee83-440c-9434-6753f7ace73f · outbound

This paper cites ChatMusician: Understanding and Generating Music Intrinsically with LLM.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons ChatMusician: Understanding and Generating Music Intrinsically with LLM

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:51.473082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a339490b-291e-4fb7-b8e2-3d305e3b67b6 · outbound

This paper cites Attention is all you need,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Attention is all you need,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:51.593691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed62c14a-13ff-4d8c-b63c-6a4fb6bfcd34 · outbound

This paper cites Multimodal prompt- ing with missing modalities for visual recognition,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Multimodal prompt- ing with missing modalities for visual recognition,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:55.305579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fca669d8-40af-47da-b15a-debff66471a4 · outbound

This paper cites Next-gpt: Any-to-any multimodal llm,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Next-gpt: Any-to-any multimodal llm,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:54.994316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bc9aa145-bf89-46d3-bc23-a3097a2e8f5a · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Learning transferable visual models from natural language supervision,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:52.083541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cac18a67-0fc2-44a6-9d79-09768fcfcd93 · outbound

This paper cites Language mod- els are few-shot learners,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Language mod- els are few-shot learners,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:52.193113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4e3dd82-696f-4acd-bea5-40c51fdcaba7 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Chain-of-thought prompting elicits reasoning in large language models,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:52.318467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9755c05d-090a-46aa-a185-ae4dbff6bd20 · outbound

This paper cites Chain-of-Verification Reduces Hallucination in Large Language Models.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Chain-of-Verification Reduces Hallucination in Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:52.407048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9d6db86-42cf-4aeb-9e40-6bdf44cfdee2 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Tree of thoughts: Deliberate problem solving with large language models,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:52.515163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d20e3f8-27e2-43cb-a2cf-7b08de95ca59 · outbound

This paper cites Large lan- guage models are zero-shot reasoners,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Large lan- guage models are zero-shot reasoners,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:52.596521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 705fc5a1-7c7b-4a4a-9cea-15086e065a72 · outbound

This paper cites Prompt engineering for zero- shot and few-shot defect detection and classification using a visual- language pretrained model,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Prompt engineering for zero- shot and few-shot defect detection and classification using a visual- language pretrained model,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:54.721079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a44b8a5c-b8e5-4a4e-baa7-3b51bd6c7ea0 · outbound

This paper cites Vita-clip: Video and text adaptive clip via multimodal prompting,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Vita-clip: Video and text adaptive clip via multimodal prompting,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:54.565967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 491ab124-09e4-4215-8f3f-28ad101a830c · outbound

This paper cites Worldgpt: Empowering llm as multimodal world model,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Worldgpt: Empowering llm as multimodal world model,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:54.422242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 17e43a17-bc5c-43e1-a396-9827688bf028 · outbound

This paper cites Neural logic machines,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Neural logic machines,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:54.255326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0e4bd2c4-b816-40ab-8537-45bcf1e8aa2d · outbound

This paper cites Differentiable logic machines,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Differentiable logic machines,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:54.045409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b8ae5958-4be8-4ba4-84c6-7464158ce8b2 · outbound

This paper cites Learning explanatory rules from noisy data,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Learning explanatory rules from noisy data,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:53.902311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ff210251-0fcc-4622-8c9e-a8af3595f06f · outbound

This paper cites Neural probabilistic logic programming in deepproblog,.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Neural probabilistic logic programming in deepproblog,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:52:53.748829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bf096a3d-ac9d-45e2-9be7-52d992820e24 · outbound

This paper cites Logical Reasoning in Large Language Models: A Survey.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Logical Reasoning in Large Language Models: A Survey

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:53.280834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eafdb9c7-b658-4d84-8848-f1c98f16410d · outbound

This paper cites Neural Logic Machines.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons Neural Logic Machines

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:53.361587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.