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Paper Citation Record · LEDGER

Logical Reasoning in Large Language Models: A Survey

As of 8 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 2026-08-08T06:32:00.761636+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
raw_fallback, observed 2026-08-07T22:39:46.656314Z

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.

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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
raw_fallback, observed 2026-08-07T22:39:46.624801Z

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.

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.407227Z digest=sha256:a69bc6e0f749b11d8df3968fdc9e7503e6b23ad7e0e805bcc8a0e12f6128315a

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.

source=pdf_text observed=2026-08-07T22:39:45.411467Z digest=sha256:a2428a81e2d1d85fc9fa312fee89457ba56e0e6a0d8e15d7660f39498b75d065

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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.426644Z digest=sha256:946ada9b7d335588e233cb460445e4629f37406fda95c2ab7043e58b8428358c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.430505Z digest=sha256:6323bc794b2c891d707be5e03f30cefd72d9f6bff0b7cc4290318261f5b614b3

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.

source=pdf_text observed=2026-08-07T22:39:45.434372Z digest=sha256:40278f64b1ef52c679980acc4a4181d38beb84992e8e2b2db5692e4c73d99420

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
unresolved
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:c09fb77023ec7e3aa020822656a8f70f39de1cb661721abf4905ce5d0e0f6a79

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:39:45.442603Z digest=sha256:6e20624189860eecaebce25589edb46f5840070f8d1da80ce92542bd7de4c616

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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.450473Z digest=sha256:d98968d611e344efaa3d77dec25cedd1762b61832bed1954140ee98d4ae64c8c

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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.457730Z digest=sha256:5885c60ee70e16255e83deed8658d7f494482e947f36935cf6c9c1204cd0208f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.461386Z digest=sha256:cf48585e3a06ec33a48fa9dd96249885fb7149c4dad6795db0db1406e3281bbe

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=sha256:077fd1b840d98653badfa82bf485a6de667bd5447b81bcbffb3439f8cccbd8a5

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
raw_fallback, observed 2026-08-07T22:39:46.456610Z

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.

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.488871Z digest=sha256:c1156f1991ac0ee0a96571cc3ee313ad359490dafb59a52cc2fa8061543c6dd2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.492585Z digest=sha256:0fd2bcf2605e39cce6223bd62c4bddb4d940ab0d8cd6f18458f5e052af43f5ad

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.496244Z digest=sha256:7187057ad8871d246e1b1134795b9af6e9dbcdcd6b90511b9f6d8f4ed17e646e

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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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
raw_fallback, observed 2026-08-07T22:39:46.370143Z

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.

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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=sha256:4bbee48ce9a980549de8f3a56ad26f8312d93f9949e97833c3b1ae597f06c984

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.524227Z digest=sha256:b8413ecd30ebd75f6c057b835b63c0326113c145004bec797f88f32b9141dc3b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.527460Z digest=sha256:de30d8dbc546b4efc65f211df6a4e6eb5fbea6a5176dcd9d32d1d7fde1e72da2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.530757Z digest=sha256:c6bc40b6fe12db56b0d2e4ecbd6c0847a5451aa76bcd88560f1e2b50cb995fd2

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=sha256:2cc7d6fc2d47fb31eb14e44733b46ffda95889a3b530d28af53fe5cecfb537ea

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.537694Z digest=sha256:18e8b616a5f31a9c8b6610e110a810be2e63f59e93c239bc4736aa8e5f7033b8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.541348Z digest=sha256:cb87932296955f111a2a4669862c218bc153c9a01b7415a2a5cb0c0f01f1099f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.544738Z digest=sha256:be585f7f0202bf74e335d2fdf4174668822b93e235559c006ff3833bc89688fd

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.547909Z digest=sha256:14c2974a69e2481161f2c05c97e090b93e17198652d8bd8c890595f05a929761

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=sha256:80d5de8d2f03bbb11a4ed6efd09449c1047eb39048ecccd0e1b558beb67385d8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.554856Z digest=sha256:01be87a2e9f72ad04e318c1b9250380c0f081a88b0aaaac74dd0036353f4b596

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.558462Z digest=sha256:0d85fdfb387b7d0f2907bf24176a71c2af75ea6d8919029848bda5aab336c3fc

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=sha256:9fb43a4efc2da9eae3da85adfa4cf11779785f870eaab5595b3f7b779a3dd2da

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.565778Z digest=sha256:ff927af9c5e7ec3c35dde3dfdfbd6b00ef62ab4683d44146c959ebe652d2e622

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.569958Z digest=sha256:5a276a05ef27b179e6af67b8b3f74a33b7fd9d53d1bd5747b8debeb62c03d67f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.573633Z digest=sha256:9cfe3f97aa9b6206038cfc3653079739d5cd34d3bfed4c0c2e45fa423c5e1709

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.577477Z digest=sha256:38f13bbb938eda76d82f8888cd36f91504618e678d790ad9ff922ae2d6b2d662

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.581013Z digest=sha256:3feff43c2241a75283addd5f1f2226d3c0dea1a6ada6e14b31c3bf7df093a682

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.584456Z digest=sha256:181c8806153f41248dc6605d3eae3ed5d2e3ae2f923bd03563f29b53b251f4aa

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.588039Z digest=sha256:0819ed687f5e128b4e6234f6275d8f2f91a144d2aa4e0b6105338599e9ec5910

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.591444Z digest=sha256:28880f89ab7c64fbb749bbfabfbfc6c898cbda367ab6c72b8d827560db3ff442

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.595350Z digest=sha256:ac83ca04497131bb7d576a2d59aa7965508da98ff4901975b8cae8f599912b74

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.599320Z digest=sha256:d7ee0cf26097d8d6659b619dbf82e42deb353a9d26bfeebb3e077c1f8c1362f6

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=sha256:687c4925e5f8afe8fb1276fb23adb6c4930c0c11fdbe14312608ab9676756dbb

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.607071Z digest=sha256:e5dfd2a9238d1ea7ab23155a923790b58b0900f3552b39aea5ec047aecb75934

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:bb146a8bd4bc20d6b403acdaaf4f7604995535e3afc459ac6ddf312ea3acc578

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.614980Z digest=sha256:c23578468526b201f6573680bfd08f1e911e11a1b4cfd7a6261650bd94978511

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.618585Z digest=sha256:eeffcd82f4e7b58228f5be15f3adf0831728c7a8938c4ccf4e8e87316b651b7d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.622388Z digest=sha256:3ae6d78fd6c4e74bc570f85d6eb5e37f1d3582577de33852607eb489d77efbe4

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.626498Z digest=sha256:f47e744c7836ea868214d87248a92d596d73a67ba470974fce4ef34961bc3d58

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.631030Z digest=sha256:9616090c8877e24dcd00c91407c97928977962897cbc740bc4a98e9b4c36c3e2

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=sha256:0547f1541f25fc5f68479103da83c2281d2a8334f4b7fd1b7bc42d4180c26659

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=sha256:21f03b92b236111fcb734224eba65642956ae30713b2a54e12fba92223be74a3

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.484882Z digest=sha256:a5816cb9b48d9adc718b60464d4685398e694ac5f0f660ceb8f5cbee98aebfc5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.469064Z digest=sha256:981552bf63c0768919196afa2452ad5a1dea30bad758f82a8489fef7229792c0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.465289Z digest=sha256:b6cf15ed5c477053bc9520efa766c5a08d31c0e2a6cc2e4f108919c212799a22

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.516592Z digest=sha256:f9956e944eaaf3a73f8e7587d3b1bd9c12b6a00f9a7dd61782ef091093c6b3af

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.472809Z digest=sha256:d6742af81aed4328174771faa60678aa5ac76969cfca7f9bbbfa20b7c0bcd185

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.384609Z digest=sha256:cc817850bd525aab9da0cde38bc580b248224247d61a0fd3f883cdefb37e64ac

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.388876Z digest=sha256:29f97964db9702ad6be77a9d5a29f9f1cfddc8fcb88b91d6b0912496f9c45251

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.418606Z digest=sha256:fbeba346aaf6a3633d0cc1bc5bc27c7bffeb0fb127e69614fa72266c52d03b69

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=sha256:7596a257133e3ea4ceb5b8459e2d0fe43ef3732425134836a1c91b30e83a63b1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.422374Z digest=sha256:e3173ff6e10b09b3e4260388d062bf9f6980e91f65efcefc7c7b0d2167b60015

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.400365Z digest=sha256:27d9862bd763dec8a98f2d237246a75c7adb9dac03a04836f9f36f4666ad01b9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.376340Z digest=sha256:db8b6d1d156930128793560c187d9efbf4ff9a585b35925e0e513cb95adc477f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T22:39:45.403801Z digest=sha256:fc5c4cc49178267cf1efcec22aa9f8cf578534628ee187a6786ac9a531812cef

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:f2fecd7460e332b75763db65ded2f6e6e7c807f7c0b31cc9ee6ddda47a045fc0

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:b035748c0d4a07f0b0b31f0bf138183cf49eaa67456c699edbef3277f3bd8da5

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=sha256:84bd36952c4d9b4fe94092e6aae07098cf41730a813ad45e28f0e63972b6ef99

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=sha256:50970e7e77f31ed79c56140a0769bbc4ab3a1b1636bda7724f5073cf7855e3de

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:f398ad9478dc6305f34f9e43d559e217501bfae4dc9c98ce1ca54bae0d77a8dc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T22:15:18.366486Z digest=sha256:4272488eca1ab556111d82f435ef31efffbc568d78116c64b8b909d98691b506

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T21:42:10.217380Z digest=sha256:e9efa9d27a274c575e167a8307facefe4e09bbf3f4f85549dff045df62440e15

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-07T08:57:05.520335Z digest=sha256:bd8823f50f51839f4e0be50548273002822f5557b8b0cf916cb2a54af550910f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T18:56:46.692954Z digest=sha256:3d59b9203093614fb6a3f7748a3ca0ea612de8b0b3c41a98ff3e0f4b5baad202

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-21T04:52:44.897900Z digest=sha256:6750b53cffe4a2b7ec8989b22d0e1ca707c5a451700e72d88566bc152793d90f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T21:57:56.104751Z digest=sha256:5a1dcdca76faa8393419f1fdaee1d1daf383ed34c5668eb6b9fde459ea223923

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T08:27:29.468354Z digest=sha256:51e914396e5651ac2407745fe85950dccff0901ccd1bf73b64dccbfc541e3c91

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T08:03:23.581020Z digest=sha256:ec70d2e764f8469ee6fa906a6168ec324e6c8ebf62f6e6a87aeb73eef41197ef