Paper Citation Record · LEDGER

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

As of 20 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

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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

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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

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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

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

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

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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,

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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

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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,

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

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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

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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,

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

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

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

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

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

Reference 34

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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

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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

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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

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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

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Pith citing papers

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