Standard Neural Computation Alone Is Insufficient for Logical Intelligence | Paper Citation Record

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This paper cites write newline.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence write newline

Reference 1

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This paper cites Organon, 4th century BCE.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Organon, 4th century BCE

Reference 2

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This paper cites and Hitzler, P.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Hitzler, P

Reference 3

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This paper cites Explaining neural scaling laws.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Explaining neural scaling laws

Reference 4

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 5

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This paper cites Neural-Symbolic Learning and Reasoning: A Survey and Interpretation.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Neural-Symbolic Learning and Reasoning: A Survey and Interpretation

Reference 6

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

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 7

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This paper cites Large language models can be easily distracted by irrelevant context.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Large language models can be easily distracted by irrelevant context

Reference 8

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 9

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 10

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This paper cites Algebraic Foundations of Many-Valued Reasoning.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Algebraic Foundations of Many-Valued Reasoning

Reference 11

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This paper cites Selection-inference: Exploiting large language models for interpretable logical reasoning.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Selection-inference: Exploiting large language models for interpretable logical reasoning

Reference 12

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This paper cites Approximation by superpositions of a sigmoidal function.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Approximation by superpositions of a sigmoidal function

Reference 13

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This paper cites Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning

Reference 14

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 15

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This paper cites Neural Logic Machines.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Neural Logic Machines

Reference 16

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Prade, H

Reference 17

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Lamb, L

Reference 18

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This paper cites and Halpern, J.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Halpern, J

Reference 19

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 20

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This paper cites and Taskar, B.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Taskar, B

Reference 21

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This paper cites Metamathematics of Fuzzy Logic.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Metamathematics of Fuzzy Logic

Reference 22

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This paper cites The symbol grounding problem.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence The symbol grounding problem

Reference 23

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Prentzas, J

Reference 24

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This paper cites Artificial Intelligence: The Very Idea.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Artificial Intelligence: The Very Idea

Reference 25

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This paper cites An overview of strategies for neurosymbolic integration.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence An overview of strategies for neurosymbolic integration

Reference 26

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This paper cites Multilayer feedforward networks are universal approximators.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Multilayer feedforward networks are universal approximators

Reference 27

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Kalinke, Y

Reference 28

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This paper cites Thinking, Fast and Slow.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Thinking, Fast and Slow

Reference 29

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence P., and B Murthy, A

Reference 30

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This paper cites Scaling Laws for Neural Language Models.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Scaling Laws for Neural Language Models

Reference 31

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This paper cites The third ai summer: Aaai robert s.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence The third ai summer: Aaai robert s

Reference 32

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 33

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence P., Mesiar, R., and Pap, E

Reference 34

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 35

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This paper cites From statistical relational to neurosymbolic artificial intelligence: A survey.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence From statistical relational to neurosymbolic artificial intelligence: A survey

Reference 36

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Hayes, P

Reference 37

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 38

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 39

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This paper cites Statistical metrics.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Statistical metrics

Reference 40

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This paper cites Steps toward artificial intelligence.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Steps toward artificial intelligence

Reference 41

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This paper cites Learning from positive data.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Learning from positive data

Reference 42

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This paper cites Limitations of the current stock of ideas about problem solving.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Limitations of the current stock of ideas about problem solving

Reference 43

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Simon, H

Reference 44

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Simon, H

Reference 45

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 46

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 47

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This paper cites Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Reference 48

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This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 49

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This paper cites D., Dumančić, S., Manhaeve, R., and Marra, G.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence D., Dumančić, S., Manhaeve, R., and Marra, G

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.620232Z

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Observation 03348013-1640-4ddf-b1bf-8fc865f7a922 · outbound

This paper cites Many-Valued Logic.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Many-Valued Logic

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.605230Z

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This paper cites Logical Neural Networks.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Logical Neural Networks

Reference 52

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Riedel, S

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.590425Z

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Observation 78c6714b-b1eb-4844-a922-cab6436a9998 · outbound

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 54

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Observation 12c4009b-7344-413a-97bf-fea3d1bb9f6b · outbound

This paper cites and Norvig, P.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Norvig, P

Reference 55

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Observation 84dd0a80-3d55-47f9-a66b-a8b7234eddf4 · outbound

This paper cites K., Zhou, L., Eberhart, A., and Hitzler, P.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence K., Zhou, L., Eberhart, A., and Hitzler, P

Reference 56

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Observation 7d098cab-af21-4161-9899-e94e48fa2fbb · outbound

This paper cites and Sklar, A.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Sklar, A

Reference 57

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Observation 81dfeb9c-e8d3-470f-9508-926cef0e7fc9 · outbound

This paper cites and Sklar, A.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Sklar, A

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.512847Z

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Reference 59

Resolution: verified exact; doi, observed 2026-08-09T13:19:51.712833Z

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-09T13:19:52.497454Z

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This paper cites and Garcez, A.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence and Garcez, A

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.482982Z

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-09T13:19:52.468381Z

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This paper cites D eterm LR : Augmenting LLM -based logical reasoning from indeterminacy to determinacy.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence D eterm LR : Augmenting LLM -based logical reasoning from indeterminacy to determinacy

Reference 63

Resolution: verified exact; doi, observed 2026-08-09T13:19:51.696272Z

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This paper cites The semantic conception of truth.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence The semantic conception of truth

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.453421Z

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This paper cites Diagnosing the first-order logical reasoning ability through L ogic NLI.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Diagnosing the first-order logical reasoning ability through L ogic NLI

Reference 65

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This paper cites Analyzing differentiable fuzzy logic operators.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Analyzing differentiable fuzzy logic operators

Reference 66

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T13:19:52.019198Z

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Observation 0df321d4-7182-4c7c-a482-bb192d97f4e3 · outbound

This paper cites Satnet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Satnet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.438267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 63806f18-7dd6-4a49-be29-be48e6f02134 · outbound

This paper cites Towards data-and knowledge-driven ai: A survey on neuro-symbolic computing.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Towards data-and knowledge-driven ai: A survey on neuro-symbolic computing

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.422436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9c43d86a-ce60-4384-ad2d-ee486c3ea6f0 · outbound

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

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-09T13:19:51.613278Z

Source-reported events for the cited work

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Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-09T13:19:52.404534Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d10215e9-29b6-4fa0-9175-e730bfdd78ad · outbound

This paper cites Learning Algorithms via Neural Logic Networks.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Learning Algorithms via Neural Logic Networks

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-09T13:19:51.624026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbae8e03-c108-4a73-980d-91a65e1aeec2 · outbound

This paper cites Neurasp: Embracing neural networks into answer set programming.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Neurasp: Embracing neural networks into answer set programming

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.388396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 003f7081-5bc7-454c-b1fd-263167d22668 · outbound

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

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Tree of thoughts: Deliberate problem solving with large language models

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.371649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5b33271d-8d5e-42d5-993e-755e7aefb829 · outbound

This paper cites an unresolved cited work.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-09T13:19:52.355377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0d307c2f-4bf7-4e78-911f-b2287529bc33 · outbound

This paper cites O logice trójwartościowej.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence O logice trójwartościowej

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:19:52.339597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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