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Paper Citation Record · LEDGER

Logical Reasoning in Large Language Models: A Survey

As of 10 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 13 inbound Pith citation observations for arXiv:2502.09100.

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

pith.paper-citation-record.v1
2502.09100 v1

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:39:45.639575Z

measured 84 of 84 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:35:58.452874Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:49:46.348394Z

Reference resolution

71 of 71 outbound references displayed

  • verified exact3
  • verified fuzzy53
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 263e00eb-1b10-4cdc-9195-58379b7e0ce2 · outbound

This paper cites LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low-Resource and Extinct Languages.

Logical Reasoning in Large Language Models: A Survey LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low-Resource and Extinct Languages

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.371286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 67c4afe8-b747-4e6f-aff0-d78216f11851 · outbound

This paper cites Formal semantics: an introduction.

Logical Reasoning in Large Language Models: A Survey Formal semantics: an introduction

Reference 3

Resolution
verified fuzzy
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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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Observation cd27212a-ead7-4f8e-9f51-8b293f2833fe · outbound

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

Logical Reasoning in Large Language Models: A Survey Selection-inference: Exploiting large language models for inter- pretable logical reasoning

Reference 7

Resolution
verified fuzzy
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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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Observation 0d7f26a6-a50f-41f3-98fc-1bc32db0080b · outbound

This paper cites Language models can be deductive solvers.

Logical Reasoning in Large Language Models: A Survey Language models can be deductive solvers

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.593893Z

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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Observation 503b4422-b51c-4cb2-a106-71726a53cd17 · outbound

This paper cites Inductive Learning of Logical Theories with LLMs: An Expressivity-Graded Analysis.

Logical Reasoning in Large Language Models: A Survey Inductive Learning of Logical Theories with LLMs: An Expressivity-Graded Analysis

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.411467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d70f79fc-558a-4632-a6bd-63e0a52ba96d · outbound

This paper cites Log- ical inferences with comparatives and generalized quantifiers.

Logical Reasoning in Large Language Models: A Survey Log- ical inferences with comparatives and generalized quantifiers

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.584224Z

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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Observation 04179be4-2a77-4151-b713-046c79b3aac2 · outbound

This paper cites Chen, and Shafiq Joty.

Logical Reasoning in Large Language Models: A Survey Chen, and Shafiq Joty

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.563722Z

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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Observation c8befcdd-5460-4a58-ad4f-a2afe861779a · outbound

This paper cites Maieutic prompting: Logically consistent rea- soning with recursive explanations.

Logical Reasoning in Large Language Models: A Survey Maieutic prompting: Logically consistent rea- soning with recursive explanations

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.553245Z

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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Observation 3aa4e378-ae64-491f-8f2a-a6aa42341137 · outbound

This paper cites Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought.

Logical Reasoning in Large Language Models: A Survey Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.434372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a2eac420-cb9b-4179-a345-2802c93bbf2b · outbound

This paper cites Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents.

Logical Reasoning in Large Language Models: A Survey Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents

Reference 18

Resolution
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no resolver link, observed 2026-08-07T22:39:45.438375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.438375Z digest=sha256:47f8734308cdeda7e9db46e7933b17ee1b8d20ac09f8c20e5e3a9d142f372586

Observation e8812be0-41bb-4229-9911-472ebb721813 · outbound

This paper cites Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models.

Logical Reasoning in Large Language Models: A Survey Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models

Reference 19

Resolution
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no resolver link, observed 2026-08-07T22:39:45.442603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e98d6f1c-6352-4f85-ae64-4dc84fb04066 · outbound

This paper cites NeuroLogic decoding: (un)supervised neural text generation with predicate logic constraints.

Logical Reasoning in Large Language Models: A Survey NeuroLogic decoding: (un)supervised neural text generation with predicate logic constraints

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.542905Z

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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Observation 9fbcc1dd-e9fb-4e81-9608-bae0ba1f049e · outbound

This paper cites Towards logiglue: A brief survey and a benchmark for analyzing logical reasoning capabilities of language models,.

Logical Reasoning in Large Language Models: A Survey Towards logiglue: A brief survey and a benchmark for analyzing logical reasoning capabilities of language models,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.532437Z

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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Observation b2eff5e0-81a4-4bca-980e-a2dfbba80a01 · outbound

This paper cites Knowra: Knowledge retrieval augmented method for document-level relation extraction with comprehensive reasoning abili- ties,.

Logical Reasoning in Large Language Models: A Survey Knowra: Knowledge retrieval augmented method for document-level relation extraction with comprehensive reasoning abili- ties,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.522029Z

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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Observation b3f7e866-e7b6-42b2-87b4-5e276d4bf376 · outbound

This paper cites Ex- ploring the role of reasoning structures for constructing proofs in multi- step natural language reasoning with large language models.

Logical Reasoning in Large Language Models: A Survey Ex- ploring the role of reasoning structures for constructing proofs in multi- step natural language reasoning with large language models

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.511150Z

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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Observation ef5075f7-cd4a-4501-aa6e-65ef633c6a7e · outbound

This paper cites McCarthy and P.J.

Logical Reasoning in Large Language Models: A Survey McCarthy and P.J

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.500308Z

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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Observation d33ba957-f801-4d21-a56d-ba2e063262f8 · outbound

This paper cites s1: Simple test-time scaling.

Logical Reasoning in Large Language Models: A Survey s1: Simple test-time scaling

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.476504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.476504Z digest=sha256:396ee12189873656502773c33a95f02f80f25568f907fa6184f59549e15a0ab0

Observation 0a5398e4-0a66-4b0a-8e5f-2e8c41e0f05a · outbound

This paper cites Newell and H.

Logical Reasoning in Large Language Models: A Survey Newell and H

Reference 29

Resolution
verified fuzzy
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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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Observation 2ce883d9-cce8-4f83-a4a3-e806293f3ae5 · outbound

This paper cites LINC: A neurosymbolic approach for logical reasoning by combining language models with first-order logic provers.

Logical Reasoning in Large Language Models: A Survey LINC: A neurosymbolic approach for logical reasoning by combining language models with first-order logic provers

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.433683Z

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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Observation a6373884-da4d-46ae-a8c5-affb50baef8f · outbound

This paper cites Learning to reason with LLMs.

Logical Reasoning in Large Language Models: A Survey Learning to reason with LLMs

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.422716Z

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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Observation 619163db-e7ac-49bb-a372-031516925097 · outbound

This paper cites Fact- driven logical reasoning for machine reading comprehension,.

Logical Reasoning in Large Language Models: A Survey Fact- driven logical reasoning for machine reading comprehension,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.412823Z

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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Observation bdf81193-45b7-406a-9fe7-3a8c551b0dec · outbound

This paper cites Logic-LM: Empowering large language models with symbolic solvers for faithful logical reasoning.

Logical Reasoning in Large Language Models: A Survey Logic-LM: Empowering large language models with symbolic solvers for faithful logical reasoning

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.403138Z

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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Observation ac76df87-0caa-4a96-86a5-a4d3388152dd · outbound

This paper cites Logicbench: A benchmark for evaluation of logical reasoning,.

Logical Reasoning in Large Language Models: A Survey Logicbench: A benchmark for evaluation of logical reasoning,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.392134Z

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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Observation 50c163f0-4371-456c-a249-c6ca76d8963d · outbound

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

Logical Reasoning in Large Language Models: A Survey Logicbench: Towards systematic evaluation of logical reasoning ability of large language models

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.381513Z

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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Observation e1609ede-2ae1-4774-9234-392fa3693b9f · outbound

This paper cites Logic for natural language analysis.

Logical Reasoning in Large Language Models: A Survey Logic for natural language analysis

Reference 37

Resolution
verified fuzzy
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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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Observation c528de9f-2221-453b-b951-331dcc7e3039 · outbound

This paper cites Reasoning with large language models, a survey.

Logical Reasoning in Large Language Models: A Survey Reasoning with large language models, a survey

Reference 39

Resolution
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no resolver link, observed 2026-08-07T22:39:45.520396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.520396Z digest=sha256:22c72ab3e0c0c4e49d7f62de661e528cc38c3aa89acde2aa679b2f1ad5fb2179

Observation e35ea3d6-629f-4abc-ac0a-1cd6e0189213 · outbound

This paper cites Relevant or random: Can llms truly perform analogi- cal reasoning?,.

Logical Reasoning in Large Language Models: A Survey Relevant or random: Can llms truly perform analogi- cal reasoning?,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.349534Z

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.

source=pdf_text observed=2026-08-07T22:39:45.524227Z digest=sha256:e50b270ca5874c79be95676eb6352fbd2ee1ae367100b9c3b08f65cc1a6d7e6c

Observation 58f03588-afb9-47b2-84b1-12a9369a9468 · outbound

This paper cites Investigating transformer-guided chaining for interpretable natural logic reasoning.

Logical Reasoning in Large Language Models: A Survey Investigating transformer-guided chaining for interpretable natural logic reasoning

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.338979Z

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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Observation 4e0a44f7-c076-405e-8248-3609621776a6 · outbound

This paper cites AnaLog: Testing analytical and deductive logic learn- ability in language models.

Logical Reasoning in Large Language Models: A Survey AnaLog: Testing analytical and deductive logic learn- ability in language models

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.328625Z

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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Observation 42fb3f60-1e88-4356-9701-7404e5a9fa5e · outbound

This paper cites Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning.

Logical Reasoning in Large Language Models: A Survey Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning

Reference 43

Resolution
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no resolver link, observed 2026-08-07T22:39:45.534039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.534039Z digest=sha256:947ef9bb5bf436e97c9d1ee55b288d681701b332fb7445473dbb01c8827450cb

Observation c73c6f46-03ec-4459-ae1e-f19bd88dcd56 · outbound

This paper cites Testing the general de- ductive reasoning capacity of large language models using ood examples.

Logical Reasoning in Large Language Models: A Survey Testing the general de- ductive reasoning capacity of large language models using ood examples

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.318080Z

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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Observation 60918c92-9fc9-4adf-a5a8-034a781fb672 · outbound

This paper cites Chain of logic: Rule-based reasoning with large language models.

Logical Reasoning in Large Language Models: A Survey Chain of logic: Rule-based reasoning with large language models

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.307292Z

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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Observation 1aef6bf8-215d-4a2a-b1ae-d898d2230656 · outbound

This paper cites Neural natural logic inference for interpretable question answering.

Logical Reasoning in Large Language Models: A Survey Neural natural logic inference for interpretable question answering

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.296422Z

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.

source=pdf_text observed=2026-08-07T22:39:45.544738Z digest=sha256:5cd9c5a82809b66a3d9bc5c3235b6afbc952b15af753ec45de7f331cc82ac79e

Observation 3ccfb1c9-6566-479c-a585-bae41164da62 · outbound

This paper cites Hamilton.

Logical Reasoning in Large Language Models: A Survey Hamilton

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.284216Z

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.

source=pdf_text observed=2026-08-07T22:39:45.547909Z digest=sha256:e2056665ea409b22d206733715fa0fdf412667480e0d98ba4d6b3fc0f81920c0

Observation 474f5133-124c-4e81-8d04-d9ae99dadc0f · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Logical Reasoning in Large Language Models: A Survey Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.551076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.551076Z digest=sha256:827807161970cc0cc9011263691fdc71d513d924f4fdd028017f0bc78df16352

Observation adfae405-30d8-4111-8f2d-2fae52ddef21 · outbound

This paper cites Logical reasoning with span-level predictions for interpretable and robust NLI models.

Logical Reasoning in Large Language Models: A Survey Logical reasoning with span-level predictions for interpretable and robust NLI models

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.272462Z

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.

source=pdf_text observed=2026-08-07T22:39:45.554856Z digest=sha256:8a0342b6fbb94986eccb39d9648ef70a72f3402e56b154812780ad6fc8697d1f

Observation 0af78712-56ec-4f4e-921c-c9b3b521e6e3 · outbound

This paper cites It is not true that transformers are inductive learners: Probing NLI models with external negation.

Logical Reasoning in Large Language Models: A Survey It is not true that transformers are inductive learners: Probing NLI models with external negation

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.261323Z

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.

source=pdf_text observed=2026-08-07T22:39:45.558462Z digest=sha256:6a7e6a7a1883ba123168bfe1ab32c65c71efc2d13064b33b9d92c3e427946d11

Observation 27556593-eb74-48ec-8618-5e7ebd21dd1c · outbound

This paper cites A Survey of Reasoning with Foundation Models.

Logical Reasoning in Large Language Models: A Survey A Survey of Reasoning with Foundation Models

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.561868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.561868Z digest=sha256:67f13c70e3796bd335b3ce83b6b3ce519959eab7d43cc6323dd5801ce49b1784

Observation 48e54707-2bdb-4187-af87-1e053d4be916 · outbound

This paper cites Determlr: Augmenting llm-based logical reasoning from indetermi- nacy to determinacy.

Logical Reasoning in Large Language Models: A Survey Determlr: Augmenting llm-based logical reasoning from indetermi- nacy to determinacy

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.250770Z

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.

source=pdf_text observed=2026-08-07T22:39:45.565778Z digest=sha256:cdc2099190881ae0ac7d39b5884e617f19422f37e15a9093f68efcfb97f0182c

Observation beb528b3-1927-4e53-8d69-de03b0165ab7 · outbound

This paper cites ProofWriter: Generating implications, proofs, and abductive statements over natural language.

Logical Reasoning in Large Language Models: A Survey ProofWriter: Generating implications, proofs, and abductive statements over natural language

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.241371Z

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.

source=pdf_text observed=2026-08-07T22:39:45.569958Z digest=sha256:be893c5d5bbf33d316a24ec568561b0cd09fdfa36ef28a68df19e360f0aafd06

Observation 45fa01d0-7d6e-413a-b412-a63fe8565b16 · outbound

This paper cites Assessing the Sensitivity and Alignment of FOL Closeness Metrics.

Logical Reasoning in Large Language Models: A Survey Assessing the Sensitivity and Alignment of FOL Closeness Metrics

Reference 54

Resolution
verified exact
local_arxiv, observed 2026-08-07T22:39:45.904004Z

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.

source=pdf_text observed=2026-08-07T22:39:45.573633Z digest=sha256:77055f76c46e9af2db2ee27d9d25e799170eaec9f63fbd88d1a17a84f4dc7868

Observation 29c7815d-471d-474f-a626-f941bff40086 · outbound

This paper cites Diagnosing the first-order logical reasoning ability through LogicNLI.

Logical Reasoning in Large Language Models: A Survey Diagnosing the first-order logical reasoning ability through LogicNLI

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.231328Z

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.

source=pdf_text observed=2026-08-07T22:39:45.577477Z digest=sha256:89169d43da5e3d0af662b49ab085b37c00fa263c23a430f998f6d6c4ab30bb39

Observation 3b5f4a82-64f5-4d7e-8a77-92968826f141 · outbound

This paper cites Verifiable, debuggable, and repairable commonsense logi- cal reasoning via llm-based theory resolution.

Logical Reasoning in Large Language Models: A Survey Verifiable, debuggable, and repairable commonsense logi- cal reasoning via llm-based theory resolution

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.219533Z

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.

source=pdf_text observed=2026-08-07T22:39:45.581013Z digest=sha256:7480269e6d2b9e9dbc29f97f7b84316d15eb8eb247d8286dc9a6d850a14b6f77

Observation a553b9a4-17de-43cb-b309-fb28e69edcfd · outbound

This paper cites Donti, Bryan Wilder, and Zico Kolter.

Logical Reasoning in Large Language Models: A Survey Donti, Bryan Wilder, and Zico Kolter

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.208542Z

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.

source=pdf_text observed=2026-08-07T22:39:45.584456Z digest=sha256:9c4a14ce6dff362cd037aedf58355392eb3d91a1f78a40d1f982f73a5369b187

Observation 7a7aa889-aa52-4893-952c-0f44ecb61be8 · outbound

This paper cites From lsat: The progress and challenges of com- plex reasoning.

Logical Reasoning in Large Language Models: A Survey From lsat: The progress and challenges of com- plex reasoning

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.196431Z

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.

source=pdf_text observed=2026-08-07T22:39:45.588039Z digest=sha256:d316be99637deddbb5f58eb456f2e267d5af71b6470f4001c99a0077eefd26a4

Observation bd3ef72c-3731-4bf3-97a4-2f8779ab4aee · outbound

This paper cites Thought-Path Contrastive Learning via Premise-Oriented Data Augmentation for Logical Reading Comprehension.

Logical Reasoning in Large Language Models: A Survey Thought-Path Contrastive Learning via Premise-Oriented Data Augmentation for Logical Reading Comprehension

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-08-07T22:39:45.887351Z

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.

source=pdf_text observed=2026-08-07T22:39:45.591444Z digest=sha256:776a0a48ce7ed342dc93fbc9378a8e23bfbb6875d461f216dee5a428cf68e515

Observation d1ebf0e1-f909-4bd7-a746-adfedd9e23aa · outbound

This paper cites ANA- LOGICAL - a novel benchmark for long text analogy evaluation in large language models.

Logical Reasoning in Large Language Models: A Survey ANA- LOGICAL - a novel benchmark for long text analogy evaluation in large language models

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.185016Z

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.

source=pdf_text observed=2026-08-07T22:39:45.595350Z digest=sha256:e9932a5b597e748c2acce95ff541dbeaaecf301c9649d86a0c392c313cfa75ed

Observation c400f1b3-5824-4bb9-b89a-791fb02a1df7 · outbound

This paper cites Training large language models for reasoning through reverse curriculum reinforcement learning.

Logical Reasoning in Large Language Models: A Survey Training large language models for reasoning through reverse curriculum reinforcement learning

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.172898Z

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.

source=pdf_text observed=2026-08-07T22:39:45.599320Z digest=sha256:50a02194519657edd24711deff37211b9fbeedb4e21149a64ad3a23404c4e71a

Observation c4871144-4c89-40c4-a071-93eb4f71556e · outbound

This paper cites Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs.

Logical Reasoning in Large Language Models: A Survey Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.603039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.603039Z digest=sha256:86bd28fa78c5b24caa61c8f3810059634c6b96b5566ef291b0916f9fd95b7867

Observation 49d31e4e-f9aa-43e0-9b5e-bf16f8e80489 · outbound

This paper cites Are large language models really good logical reason- ers? a comprehensive evaluation and beyond,.

Logical Reasoning in Large Language Models: A Survey Are large language models really good logical reason- ers? a comprehensive evaluation and beyond,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.160124Z

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.

source=pdf_text observed=2026-08-07T22:39:45.607071Z digest=sha256:9a516edc8212baec590692383adcd6cb09eb145464e40608728bbce2bcc5a908

Observation 640101bc-8b32-4a36-834b-f7bc25cf2840 · outbound

This paper cites Aristotle: Mastering logical reasoning with a logic-complete decompose-search-resolve framework.

Logical Reasoning in Large Language Models: A Survey Aristotle: Mastering logical reasoning with a logic-complete decompose-search-resolve framework

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.611017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.611017Z digest=sha256:a7f3b2c36ff9e4f7ffdc949d3c75ef372bd3409391dc62d01e83f909735bf3fd

Observation e3703075-98bc-4f41-9c0c-a7720a59e9fe · outbound

This paper cites Swope, Alex Gu, Rahul Chala- mala, Peiyang Song, et al.

Logical Reasoning in Large Language Models: A Survey Swope, Alex Gu, Rahul Chala- mala, Peiyang Song, et al

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.147906Z

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.

source=pdf_text observed=2026-08-07T22:39:45.614980Z digest=sha256:1693232fb0be632877b2ef8df375af182c40af1c9dc563c10197287c0b1a30c4

Observation 3ecc1785-913e-4d15-99cb-7b2b7df49690 · outbound

This paper cites Re- clor: A reading comprehension dataset requiring logical reasoning.

Logical Reasoning in Large Language Models: A Survey Re- clor: A reading comprehension dataset requiring logical reasoning

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.137050Z

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.

source=pdf_text observed=2026-08-07T22:39:45.618585Z digest=sha256:9a41c221dd4e3c55f82f14c1128df0b1f573012e5c7175492885cd3d698d19b9

Observation 3b7ed8bb-4e5d-402b-a75c-297c7a027f3f · outbound

This paper cites Natural language reasoning, a survey.

Logical Reasoning in Large Language Models: A Survey Natural language reasoning, a survey

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.125522Z

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.

source=pdf_text observed=2026-08-07T22:39:45.622388Z digest=sha256:0cad64a5f32b9bd48cb4b4f294d87f230e2d04f3143aeded643a4713a3a3bfa3

Observation 6eb73e51-ed7c-4e23-b31b-1a9e90a104e7 · outbound

This paper cites Can pretrained language models (yet) reason deduc- tively? In Proc.

Logical Reasoning in Large Language Models: A Survey Can pretrained language models (yet) reason deduc- tively? In Proc

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.114794Z

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.

source=pdf_text observed=2026-08-07T22:39:45.626498Z digest=sha256:152e67fd67da29d44225e7bfd6c2774cc95d577232c582bbc237e91b8fddce50

Observation 8f209bd9-2e21-44fb-b793-05bd09a6b736 · outbound

This paper cites Formal language knowledge corpus for retrieval augmented generation,.

Logical Reasoning in Large Language Models: A Survey Formal language knowledge corpus for retrieval augmented generation,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.103248Z

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.

source=pdf_text observed=2026-08-07T22:39:45.631030Z digest=sha256:1e0b63c83920181a9b0b7515e30acac70f2e04e2965872e7b4ef75cae444f114

Observation 1b0f40f6-8a1f-49e0-bdfa-f6ad35ba91ff · outbound

This paper cites o1-Coder: an o1 Replication for Coding.

Logical Reasoning in Large Language Models: A Survey o1-Coder: an o1 Replication for Coding

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.635091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.635091Z digest=sha256:1ef3b93ad14ee6814271da22e9dd1548e9b324d43e2140720217d7cd22cbedd8

Observation 5729f7e5-93fe-4f2d-ac77-1f7bf8ae5f2b · outbound

This paper cites Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions.

Logical Reasoning in Large Language Models: A Survey Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.639575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.639575Z digest=sha256:7d7c8d8c37c0f28bfa678fefba41a58d2fe668f7dca53f0ccb6088fddc58c586

Observation 472c8759-7be1-4607-8a8b-319c43897b22 · outbound

This paper cites How well do sota legal reasoning models support abductive reasoning?,.

Logical Reasoning in Large Language Models: A Survey How well do sota legal reasoning models support abductive reasoning?,

Reference 1956

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.445487Z

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.

source=pdf_text observed=2026-08-07T22:39:45.484882Z digest=sha256:f9a7bdb23d7b7a9460f128b0967bdc10008d11ce3b5522cc79cd711eae0265e7

Observation 0ef42abd-a759-4c1b-b103-1742e10cb153 · outbound

This paper cites Artificial intelligence, logic and formaliz- ing common sense.

Logical Reasoning in Large Language Models: A Survey Artificial intelligence, logic and formaliz- ing common sense

Reference 1959

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.478643Z

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.

source=pdf_text observed=2026-08-07T22:39:45.469064Z digest=sha256:35aa56c17dad909577153851d924fb34071ad27c46a42a5833d07560ce79e5f1

Observation b59d6ff7-460b-4566-a5e2-6f91c26a1b7c · outbound

This paper cites Programs with common sense.

Logical Reasoning in Large Language Models: A Survey Programs with common sense

Reference 1981

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.489646Z

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.

source=pdf_text observed=2026-08-07T22:39:45.465289Z digest=sha256:a50523ae0b8340188a00eb7b5ea591735e278e47fd085325f318cb4951f3f449

Observation ede39628-3514-443f-a0fe-0b7dd4c395c1 · outbound

This paper cites Can language models learn analogical reasoning? investigating training ob- jectives and comparisons to human performance.

Logical Reasoning in Large Language Models: A Survey Can language models learn analogical reasoning? investigating training ob- jectives and comparisons to human performance

Reference 1982

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.359840Z

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.

source=pdf_text observed=2026-08-07T22:39:45.516592Z digest=sha256:99b782f34984ddf42645295b2b2aa8475fb99563492e350bdd7d82b1d76f8263

Observation 330fe452-8239-4669-9803-29052752405a · outbound

This paper cites Enhancing reasoning capabilities of llms via prin- cipled synthetic logic corpus.

Logical Reasoning in Large Language Models: A Survey Enhancing reasoning capabilities of llms via prin- cipled synthetic logic corpus

Reference 1989

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.467699Z

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.

source=pdf_text observed=2026-08-07T22:39:45.472809Z digest=sha256:60ead46f40c75a9293acd0b0c4506e8a2436764447c2272c2fae6b3ba1b7b73f

Observation 52c60847-df98-47f5-9e9a-b382a8822e99 · outbound

This paper cites Deeplogic: Towards end-to-end differentiable logical reasoning,.

Logical Reasoning in Large Language Models: A Survey Deeplogic: Towards end-to-end differentiable logical reasoning,

Reference 1993

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.645894Z

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.

source=pdf_text observed=2026-08-07T22:39:45.384609Z digest=sha256:41dcf502a69ef21f1d7043e8031d41f81c388dedf625cef246137942a0ee06a2

Observation 7b5a2701-0204-4877-9775-b694d598c2f1 · outbound

This paper cites Trans- formers as soft reasoners over language.

Logical Reasoning in Large Language Models: A Survey Trans- formers as soft reasoners over language

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.635306Z

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.

source=pdf_text observed=2026-08-07T22:39:45.388876Z digest=sha256:1d453f65c864ad17d46bfdfcd2fc0581fddd4addb711279177a33412f3978160

Observation 067926a5-5708-43ca-8a00-74745f7cde17 · outbound

This paper cites Log- itorch: A pytorch-based library for logical reasoning on natural language.

Logical Reasoning in Large Language Models: A Survey Log- itorch: A pytorch-based library for logical reasoning on natural language

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.574054Z

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.

source=pdf_text observed=2026-08-07T22:39:45.418606Z digest=sha256:12bee32668f4f2f9774dd461544614e2ac24d54d498bccae03c358ed20db3328

Observation d78407f0-f683-43f0-b8e7-d8d00b8daa03 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Logical Reasoning in Large Language Models: A Survey Training Verifiers to Solve Math Word Problems

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T22:39:45.392571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.392571Z digest=sha256:ba4b22a07848e9f2e82d8618ba4226c9bb1a6592ad0523f1248b27c17f1915df

Observation a12cb4b5-ac0c-4db1-96e9-d78f9995de18 · outbound

This paper cites LogicPro: Improving Complex Logical Reasoning via Program-Guided Learning.

Logical Reasoning in Large Language Models: A Survey LogicPro: Improving Complex Logical Reasoning via Program-Guided Learning

Reference 2022

Resolution
verified exact
local_arxiv, observed 2026-08-07T22:39:46.059462Z

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.

source=pdf_text observed=2026-08-07T22:39:45.422374Z digest=sha256:ea8b51f22c1f4fb07d9771ca79eea52b885690126ef1a547d68477868185547f

Observation 0715924c-ec3a-4b37-9fc4-7f949b61bb93 · outbound

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

Logical Reasoning in Large Language Models: A Survey DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.614189Z

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.

source=pdf_text observed=2026-08-07T22:39:45.400365Z digest=sha256:5eaa5972d58b2e70f48e413339937c05d7ffad14a0d0f3846e9ee2f6995184ce

Observation b1db724d-d13f-4265-bc76-5739bc884427 · outbound

This paper cites A com- prehensive evaluation of inductive reasoning capabilities and problem solv- ing in large language models.

Logical Reasoning in Large Language Models: A Survey A com- prehensive evaluation of inductive reasoning capabilities and problem solv- ing in large language models

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.666841Z

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.

source=pdf_text observed=2026-08-07T22:39:45.376340Z digest=sha256:8ed9454d294327e1e42b8b029f26510d64a83f69a9a15647e1bbd0c9fcc458be

Observation 1d7ec1b6-70c0-4d50-8f3d-a58752382d92 · outbound

This paper cites True detective: A deep abductive reasoning benchmark undoable for GPT-3 and challenging for GPT-4.

Logical Reasoning in Large Language Models: A Survey True detective: A deep abductive reasoning benchmark undoable for GPT-3 and challenging for GPT-4

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:39:46.603743Z

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.

source=pdf_text observed=2026-08-07T22:39:45.403801Z digest=sha256:085e6a8b52c8af155ad3e7b05009ea753b787daf84b87d2b6c57fb4cfd66cd23

Pith citing papers

Observation e5e6db67-813f-4bd4-adbf-a3e06e0a7701 · inbound

MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs cites this paper.

MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs Logical Reasoning in Large Language Models: A Survey

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T13:35:58.452874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:35:58.452874Z digest=sha256:67f74e2a2931fe86e33222fc5b9647c3d86fb0d09d8250056c5549e309ba1829

Observation e2b20e15-00a1-4698-bfd0-95a6354a65c2 · inbound

ARGUS: Hallucination and Omission Evaluation in Video-LLMs cites this paper.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs Logical Reasoning in Large Language Models: A Survey

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:39.710210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.710210Z digest=sha256:040a5dc8447c438294093cd8bbf13eccbf5b7e629766dea03cc957039bdc6505

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

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

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.

source=pdf_text observed=2026-08-06T21:52:53.280834Z digest=sha256:3f639c3d015105c093957f307798de22c6919bfedd00425f37d3f75946ee3f5c

Observation cbe3ef51-352d-42b3-a4b6-c5210b269c19 · inbound

DAFMSVC: One-Shot Singing Voice Conversion with Dual Attention Mechanism and Flow Matching cites this paper.

DAFMSVC: One-Shot Singing Voice Conversion with Dual Attention Mechanism and Flow Matching Logical Reasoning in Large Language Models: A Survey

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T23:03:10.463706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:03:10.463706Z digest=sha256:f5c4fba830d58ea04004bea671e1048be602d5be665537751bae1fc6acc49086

Observation 43b559e0-6cdb-41b1-a5b9-da4e9554cd8d · inbound

Deductive Logic in Language Models: Horizontal vs Vertical Reasoning cites this paper.

Deductive Logic in Language Models: Horizontal vs Vertical Reasoning Logical Reasoning in Large Language Models: A Survey

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-04T10:40:25.530522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:40:25.530522Z digest=sha256:3de559edc74dfda46f6665cd1e5dfaab785648b9eb079433467d66093388e8f5

Observation cba36266-727e-488b-8934-93c5567cfb89 · inbound

Reasoning Primitives in Hybrid and Non-Hybrid LLMs: Do Architectural Differences Yield Advantages in State-Tracking and Recall? cites this paper.

Reasoning Primitives in Hybrid and Non-Hybrid LLMs: Do Architectural Differences Yield Advantages in State-Tracking and Recall? Logical Reasoning in Large Language Models: A Survey

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-09T22:49:16.007942Z

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.

source=pdf_text observed=2026-05-09T22:15:18.366486Z digest=sha256:7c50ee297226794dd32b6c82c9455dc011e371766e3e29b85ab6ecc9a32ec070

Observation 785f00b1-e33a-48be-a0b0-e8b12565985e · inbound

Frozen LLMs as Map-Aware Spatio-Temporal Reasoners for Vehicle Trajectory Prediction cites this paper.

Frozen LLMs as Map-Aware Spatio-Temporal Reasoners for Vehicle Trajectory Prediction Logical Reasoning in Large Language Models: A Survey

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:31:06.305428Z

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.

source=pdf_text observed=2026-05-09T21:42:10.217380Z digest=sha256:43681bb93405c1e44779ee5d7f4da4f0058f7b4b8408e711310c80455d015b99

Observation fe9acc41-1007-426c-9a69-f0f8e2b99d5b · inbound

Compliance versus Sensibility: On the Reasoning Controllability in Large Language Models cites this paper.

Compliance versus Sensibility: On the Reasoning Controllability in Large Language Models Logical Reasoning in Large Language Models: A Survey

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:51:28.984303Z

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.

source=arxiv_source observed=2026-05-07T08:57:05.520335Z digest=sha256:e3274ffc7bed9862e98221ac48e165cc637abc253510fbaa200912ce9363411c

Observation a144cc3b-b740-484b-9e30-8f6111caced6 · inbound

SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking cites this paper.

SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking Logical Reasoning in Large Language Models: A Survey

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:01:13.446899Z

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.

source=pdf_text observed=2026-05-09T18:56:46.692954Z digest=sha256:4bf06807915e418554d0af2d5adf90d7847e4b4c184eea58b22621403db1b730

Observation 0138a289-32b9-41a6-8e4b-d26a4262718c · inbound

Text Analytics Evaluation Framework: A Case Study on LLMs and Social Media cites this paper.

Text Analytics Evaluation Framework: A Case Study on LLMs and Social Media Logical Reasoning in Large Language Models: A Survey

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-21T04:53:57.754653Z

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.

source=arxiv_source observed=2026-05-21T04:52:44.897900Z digest=sha256:f335f8d63cf8b9041f6b35a6821dc24c4376d63b96d508a239ba85525469dea6

Observation 0861c2b2-c57f-41cf-97e8-175838c2a939 · inbound

A Neuro-Symbolic Approach to Strategy Synthesis for Strategic Logics cites this paper.

A Neuro-Symbolic Approach to Strategy Synthesis for Strategic Logics Logical Reasoning in Large Language Models: A Survey

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T23:39:03.823290Z

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.

source=pdf_text observed=2026-06-26T21:57:56.104751Z digest=sha256:fb9f66eafb2958676d966decbc4b3bde0ce4f49f7b84badcb81ae48924dd60bb

Observation cd3727d0-7dad-4376-8627-165eb3fed3cf · inbound

HOLMES: Evaluating Higher-Order Logical Reasoning in LLMs cites this paper.

HOLMES: Evaluating Higher-Order Logical Reasoning in LLMs Logical Reasoning in Large Language Models: A Survey

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T10:49:46.350551Z

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.

source=arxiv_source observed=2026-06-26T08:27:29.468354Z digest=sha256:02677aaa7a7f3046e21b861b5cccb3ca2a149b60293e5a90c8829ad617b005ff

Observation 53ba11ca-ecaa-4680-8339-ab6d754344de · inbound

Symbolic Mechanistic Data Attribution: Tracing Training Influence to Learned Behavioral Policies cites this paper.

Symbolic Mechanistic Data Attribution: Tracing Training Influence to Learned Behavioral Policies Logical Reasoning in Large Language Models: A Survey

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T08:04:27.977342Z

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.

source=arxiv_source observed=2026-06-30T08:03:23.581020Z digest=sha256:fff35170788546f6b8cc5d932861ed3119a38981d7aab54e1ca55c42b9f1adbc