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Paper Citation Record · LEDGER

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks

As of 7 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 4 inbound Pith citation observations for arXiv:2505.20047.

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

pith.paper-citation-record.v1
2505.20047 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:06:33.306043Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:45:12.671790Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T07:54:43.182673Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact3
  • verified fuzzy6
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 300f7ad8-e1ea-4eb0-9b14-e0b431907868 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 6

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source=pdf_text observed=2026-08-07T14:06:29.697285Z digest=sha256:0e4daed3c64eb981c7d8ecf35893f5f5cb503ecc6b5481282862c237f00c0613

Observation 3535cf87-e067-4d87-bf36-c89ab0beacfb · outbound

This paper cites URLhttps://aclanthology.org/2021.tacl-1.21/.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks URLhttps://aclanthology.org/2021.tacl-1.21/

Reference 7

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source=pdf_text observed=2026-08-07T14:06:29.808546Z digest=sha256:fbc6fc49fe8dd766fa524b49064a8444114cbe05be9de4a2e41a5d93fc396e25

Observation e34a6ebb-e18b-4f4b-81fe-53d10bae56a9 · outbound

This paper cites FOLIO: Natural language reasoning with first-order logic.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks FOLIO: Natural language reasoning with first-order logic

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-07T14:06:35.653914Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:29.908396Z digest=sha256:f7d1c5ce4d9543d23f1870d098be270a823a9bf026a48bae59529911023ecd05

Observation 68bba2f4-5ba6-4154-bb67-951a0485e0aa · outbound

This paper cites tailedness.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks tailedness

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-07T14:06:34.476109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:33.306043Z digest=sha256:6ed698e00af9275e13c2043618bf2292d7162a4eaf2c55778105bc33766af9cd

Observation 17ff4aad-6d54-4831-9c44-eac50c3acc1f · outbound

This paper cites Towards a Mathematics Formalisation Assistant using Large Language Models.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Towards a Mathematics Formalisation Assistant using Large Language Models

Reference 11

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:06:30.094004Z digest=sha256:b8f37fda45e6257db0dc97f1d397baf946110d49f901e18d5da0fdd689ce9c89

Observation 87665c19-5bb5-4104-922c-890f80c4f568 · outbound

This paper cites FIMO: A Challenge Formal Dataset for Automated Theorem Proving.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks FIMO: A Challenge Formal Dataset for Automated Theorem Proving

Reference 12

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source=pdf_text observed=2026-08-07T14:06:30.120173Z digest=sha256:eb9d1070ac0d5cb5e7893c9f576fe1654f584e888bf8bc81ed4d8bb29777359d

Observation 5894d4ff-3ce2-452b-828a-ad0ab1158df2 · outbound

This paper cites Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving

Reference 13

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source=pdf_text observed=2026-08-07T14:06:30.223009Z digest=sha256:f2671c4f3623877c7c77b47b6ec1706ff50d253d19c5b6ef1e67ca2547185f85

Observation 59730723-51a4-461f-82a8-a0eeb2d107c7 · outbound

This paper cites DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data

Reference 14

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source=pdf_text observed=2026-08-07T14:06:30.321310Z digest=sha256:c162913bc9e8fd845707704b1a98b3894977c05304b299d5af5980590e58dd21

Observation f5f7fc77-3ba5-4e58-baec-1c94e59c31db · outbound

This paper cites Proving Theorems Recursively.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Proving Theorems Recursively

Reference 16

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source=pdf_text observed=2026-08-07T14:06:30.451938Z digest=sha256:fa8374e75584289c9e8bc1ccf6596befa3978dbf4a4a1249dac98c71ebc604d3

Observation 84f816bf-9ae5-4b7d-a69b-8777ebb6bdc7 · outbound

This paper cites Large Language Models' Understanding of Math: Source Criticism and Extrapolation.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Large Language Models' Understanding of Math: Source Criticism and Extrapolation

Reference 17

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verified exact
local_arxiv, observed 2026-08-07T14:06:34.217293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:30.524766Z digest=sha256:7e90b69e87729261c2340fe0a4db8b3bc44a7fc84fb8af9881e64a27b01ea644

Observation 3af7d02f-b50c-4b84-8c2e-abe168312436 · outbound

This paper cites Experimental results from applying GPT-4 to an unpublished formal language.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Experimental results from applying GPT-4 to an unpublished formal language

Reference 18

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local_arxiv, observed 2026-08-07T14:06:34.087320Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:30.595514Z digest=sha256:615e47a496e445430a928f8388c97068e12e1e66ed40ade4e6bd4de178ac2cac

Observation b7071168-7956-4444-926e-7f149b065854 · outbound

This paper cites Large Language Models for Mathematicians.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Large Language Models for Mathematicians

Reference 19

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source=pdf_text observed=2026-08-07T14:06:30.665664Z digest=sha256:4cc9e1e1039bb04b6b723e8b99dd098991908f809257d1961157a303af70a307

Observation 33f465c2-ff0d-44f4-8428-488c028241e4 · outbound

This paper cites An In-Context Learning Agent for Formal Theorem-Proving.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks An In-Context Learning Agent for Formal Theorem-Proving

Reference 20

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source=pdf_text observed=2026-08-07T14:06:30.740697Z digest=sha256:86b5e5ce6aea6473e5759f3c737dc24e629f147cf28395fd2dbb46a264da3c49

Observation af203b79-7824-4211-af81-b60ed8f6bc56 · outbound

This paper cites Automated Theorem Proving in Intuitionistic Propositional Logic by Deep Reinforcement Learning.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Automated Theorem Proving in Intuitionistic Propositional Logic by Deep Reinforcement Learning

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:06:33.898352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:30.809313Z digest=sha256:ffe1990f527bd2ade7ab416ae00d4710bba3ae859fdb626fcb18562e01a74d93

Observation 81c35cd2-6997-4824-8bc3-e5bde035bdf5 · outbound

This paper cites Learn from Failure: Fine-Tuning LLMs with Trial-and-Error Data for Intuitionistic Propositional Logic Proving.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Learn from Failure: Fine-Tuning LLMs with Trial-and-Error Data for Intuitionistic Propositional Logic Proving

Reference 22

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local_arxiv, observed 2026-08-07T14:06:33.826206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:30.898686Z digest=sha256:824c2e917a1dd7f470e9a0ea776fe0886e53a03c8157fcc5139eb26fdc4c3a03

Observation d757dba6-40e5-45d3-922b-cec9bb3913d9 · outbound

This paper cites Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation

Reference 23

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source=pdf_text observed=2026-08-07T14:06:31.022782Z digest=sha256:3025dfd170558f2c6d7ad29e53d2410e0cd1337277e8e0eda55f836a8eb3bb5f

Observation 117a72f0-ac6a-4a25-9b3a-786bc51021ee · outbound

This paper cites GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations

Reference 24

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source=pdf_text observed=2026-08-07T14:06:31.207570Z digest=sha256:f730ad14621bc83f80d185fa99c908e98d4bdff5d66882aa31e446e70f811827

Observation 9248041d-88a7-4cec-ae3d-9d377ef6af79 · outbound

This paper cites Uncertainty estimation in large language models to support biodiversity conservation.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Uncertainty estimation in large language models to support biodiversity conservation

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-07T14:06:35.475117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:31.382488Z digest=sha256:c4c17a0ab56910d7388eddd4f0618963d4d36d3732393e8b381aefb6bccda38f

Observation 35d8ddcd-51b4-4bd8-913c-a753309add62 · outbound

This paper cites BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning

Reference 28

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source=pdf_text observed=2026-08-07T14:06:31.859886Z digest=sha256:118f0f7c2b1f51d9af104c9a6210f584125cfa794c49fe85707a0ecd544e6d3e

Observation 7ca760b9-ce92-4066-84e9-27a2b8c60474 · outbound

This paper cites Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models

Reference 29

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source=pdf_text observed=2026-08-07T14:06:31.972141Z digest=sha256:c88ec00846b086303606d2e971df95ab843b9f572468de8f1c15287aa2de8ea8

Observation 536404a5-66bb-4d0b-985c-7493657f9ddc · outbound

This paper cites Selectively Answering Ambiguous Questions.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Selectively Answering Ambiguous Questions

Reference 30

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source=pdf_text observed=2026-08-07T14:06:32.093530Z digest=sha256:de89822a4162614a605f1d42bdaae724282c4f19efbf9ee54df92ac6dbec8917

Observation 1db8c8c1-f61c-4f55-9fd9-cb4334c94bc3 · outbound

This paper cites SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Reference 31

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source=pdf_text observed=2026-08-07T14:06:32.166409Z digest=sha256:6d356d02616bb65105d533e1ebfbb8f4241d165599d45ecf90996e6a2b8201b4

Observation 6bd4ec45-2561-4467-870b-0a729ffb7ada · outbound

This paper cites URLhttps://aclanthology.org/2024.acl-long.283.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks URLhttps://aclanthology.org/2024.acl-long.283

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-07T14:06:35.263822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:32.231112Z digest=sha256:0a69a76dcd2209c7e8bb180b28c2b414e4fa74cdd550c8fd761998122aa2a1c6

Observation 36eeba6a-9133-40de-80d8-9cf8a91cda0c · outbound

This paper cites Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models

Reference 33

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source=pdf_text observed=2026-08-07T14:06:32.320811Z digest=sha256:95ac13b2b298bddd071ca34381432cd1fa69a6012f77a3de150a6d81546e620e

Observation a7feac1b-7ee4-43bd-8ef0-431544bef318 · outbound

This paper cites an unresolved cited work.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Unresolved cited work

Reference 34

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:32.433013Z digest=sha256:7e1d1d198c36801d8bde26fc6cfefa12dc16f565f01b82f695c99ff97094d2eb

Observation e3b164d0-649a-4c78-b2b4-debe8abd9ef4 · outbound

This paper cites Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes

Reference 36

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source=pdf_text observed=2026-08-07T14:06:32.571772Z digest=sha256:9daeb4f498b070b519fc97afe205a8f2874a40c54e60b6a83bb5490c7ed721fa

Observation 06224edf-f45c-4091-a543-53e800819559 · outbound

This paper cites Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness

Reference 37

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source=pdf_text observed=2026-08-07T14:06:32.643092Z digest=sha256:072c042f324dca1bd92a3aed074fd45f2bf7116c7b3bbdffc7e9999314437f0e

Observation ec1db97f-76d1-473b-bdd5-ef12a1fd1741 · outbound

This paper cites Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback

Reference 40

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source=pdf_text observed=2026-08-07T14:06:32.927335Z digest=sha256:c615b0f1541e3e76dfec2b1e4f1de2cd1d722433ffbb6c399cefb647e162e110

Observation 2daa234d-4abf-4815-b0d2-c7da57892170 · outbound

This paper cites Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs

Reference 41

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source=pdf_text observed=2026-08-07T14:06:33.003689Z digest=sha256:8e2775499057f7b7b5ef5ca8c095218debe30432dad68d14fab341a5e4966344

Observation c2e52b91-94f0-4570-b6e4-070ccba28b5d · outbound

This paper cites Tobias Groot and Matias Valdenegro-Toro.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Tobias Groot and Matias Valdenegro-Toro

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-07T14:06:34.900367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:33.087549Z digest=sha256:46233ddbdd1086cdd16d11779a1f40278fa274fe60f6905715ab04858d4d48a1

Observation 26ca16a6-c72c-45b0-8734-7d08d3e75e18 · outbound

This paper cites URLhttp://www.jstor.org/stable/2236703.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks URLhttp://www.jstor.org/stable/2236703

Reference 1951

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source=pdf_text observed=2026-08-07T14:06:32.501189Z digest=sha256:6e48611824621efce479a1307e40e7c63c52ac0059c621a934f39fc48ccc2495

Observation 2fb398df-0607-4eb5-b251-2efd24aba0ca · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958,.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Dropout: a simple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958,

Reference 1965

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source=pdf_text observed=2026-08-07T14:06:31.530258Z digest=sha256:c3672c70ada0f431b53fd3c03d85a88f3cac3762e5f7b88051afe8b397adc544

Observation 0322fa87-bd72-4352-92b1-d471be2480f1 · outbound

This paper cites Teaching Models to Express Their Uncertainty in Words.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Teaching Models to Express Their Uncertainty in Words

Reference 1996

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source=pdf_text observed=2026-08-07T14:06:32.818788Z digest=sha256:7134cbd5af8b3e01467f878bfd93c9209e7aa3895a9bd37e528f4434d2430227

Observation c1562269-ef36-462f-9eca-00d5ce2bc3ac · outbound

This paper cites Synthesizing finite-state protocols from scenarios and requirements.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Synthesizing finite-state protocols from scenarios and requirements

Reference 1998

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verified fuzzy
raw_fallback, observed 2026-08-07T14:06:34.751805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:33.175591Z digest=sha256:0f30769618fb6b72d086b1575ddb24f50e17d907a747ec681662cd050f19048c

Observation 7978093a-8da9-47ff-b710-e0b5b4aeedf3 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,

Reference 2009

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source=pdf_text observed=2026-08-07T14:06:29.203613Z digest=sha256:142013ec045794778a868c6d5452b5a5ee422ebc9e5538d2eb12faacd6bb76fc

Observation 147a9f44-3ac0-4450-8d3a-88f847a284b9 · outbound

This paper cites LM-Polygraph: Uncertainty Estimation for Language Models.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks LM-Polygraph: Uncertainty Estimation for Language Models

Reference 2017

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no resolver link, observed 2026-08-07T14:06:31.679535Z

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source=pdf_text observed=2026-08-07T14:06:31.679535Z digest=sha256:f74bba228917a013d6896c9a858e121d390e84ebd2090fd7833c62c21c2da35c

Observation 4111abfd-0bbd-45ff-9d42-7042cc604811 · outbound

This paper cites Quantifying Uncertainties in Natural Language Processing Tasks.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Quantifying Uncertainties in Natural Language Processing Tasks

Reference 2018

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metadata mismatch
local_arxiv, observed 2026-08-07T14:06:33.482051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:06:32.739732Z digest=sha256:b95c4b3a2a41274ebc94aabc17e82cce503af23654453793ac2cf672e60ac2ca

Observation 3d942f1d-7334-4118-8833-460ceb6f8036 · outbound

This paper cites Generative Language Modeling for Automated Theorem Proving.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Generative Language Modeling for Automated Theorem Proving

Reference 2019

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no resolver link, observed 2026-08-07T14:06:30.374808Z

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source=pdf_text observed=2026-08-07T14:06:30.374808Z digest=sha256:1717f1bdf047038783bf5dc0a7e0c18c39424320bad9cb6493bb2814a09f8a52

Observation 1a89ae7f-4259-4120-892d-42ff6f6bd11f · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Evaluating Large Language Models Trained on Code

Reference 2020

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no resolver link, observed 2026-08-07T14:06:29.257173Z

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source=pdf_text observed=2026-08-07T14:06:29.257173Z digest=sha256:220828ca5d4b4a0627f7d3ba94f26e97b4b82cf61a98fc65eebb2f969a4bed53

Observation 184b0bb3-661b-4f22-bc44-f51240de8649 · outbound

This paper cites Mistral 7B.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Mistral 7B

Reference 2021

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no resolver link, observed 2026-08-07T14:06:29.362119Z

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source=pdf_text observed=2026-08-07T14:06:29.362119Z digest=sha256:9a86a4d236de766b67f1b1d7a16de49772cb2c397dc31030d13a90548ebbe6c9

Observation cf8a6316-ee8f-4984-b8ad-0f6c641219ac · outbound

This paper cites Language Models (Mostly) Know What They Know.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Language Models (Mostly) Know What They Know

Reference 2022

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no resolver link, observed 2026-08-07T14:06:29.584972Z

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source=pdf_text observed=2026-08-07T14:06:29.584972Z digest=sha256:350d41e1c24da14176460d99753c222e22d85ea1eca5caa0ee1f803c4f99337e

Observation 5f2baf8d-bde2-4b56-8c9a-d70924117819 · outbound

This paper cites Emergent Abilities of Large Language Models.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks Emergent Abilities of Large Language Models

Reference 2023

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no resolver link, observed 2026-08-07T14:06:29.472186Z

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source=pdf_text observed=2026-08-07T14:06:29.472186Z digest=sha256:4c9c13623543e710ac0bddd1c2ce0e848004ee449bbe8f6ce70c2269f55944d3

Observation 72b19340-8d15-42e1-bb17-b4e2376a1c54 · outbound

This paper cites doi: 10.18653/v1/2024.

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks doi: 10.18653/v1/2024

Reference 2024

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no resolver link, observed 2026-08-07T14:06:29.995705Z

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source=pdf_text observed=2026-08-07T14:06:29.995705Z digest=sha256:16470cc72c8e666c1ccb00504ad5cc84618cb1d675e083d55dee77743c155fad

Pith citing papers

Observation a0a854e3-0c2d-4435-9dfe-59f31b2e00ba · inbound

AI4Research: A Survey of Artificial Intelligence for Scientific Research cites this paper.

AI4Research: A Survey of Artificial Intelligence for Scientific Research Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks

Reference 221

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no resolver link, observed 2026-08-06T20:45:12.671790Z

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source=pdf_text observed=2026-08-06T20:45:12.671790Z digest=sha256:d994bfe5e9102f62279ad9c381616b71b67a5c6beb100e1d9c0d9d1ce7c61acb

Observation aa54143a-4923-43ac-9b70-45b696456023 · inbound

Reliability-Gated Source Anchoring for Continual Test-Time Adaptation cites this paper.

Reliability-Gated Source Anchoring for Continual Test-Time Adaptation Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks

Reference 6

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verified exact
arxiv_id, observed 2026-05-15T05:29:46.944740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T05:29:17.744966Z digest=sha256:dcb6ff691e669d7eb307f58d10505860f0cec0ded6b752efd4d3960498e8935e

Observation 108fe26f-bc3f-46f9-91bb-e3da03d1e4a8 · inbound

Reliability-Gated Source Anchoring for Continual Test-Time Adaptation cites this paper.

Reliability-Gated Source Anchoring for Continual Test-Time Adaptation Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks

Reference 6

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verified exact
arxiv_id, observed 2026-05-20T20:29:00.068897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T20:24:01.811656Z digest=sha256:a0c0c619d5ef2339cfa570bc3ed13ed560321f3222e101d3c1c314f4790505a2

Observation 25f15a8b-2f9e-4019-80d3-9c5bbef526f5 · inbound

CausalGuard: Conformal Inference under Graph Uncertainty cites this paper.

CausalGuard: Conformal Inference under Graph Uncertainty Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks

Reference 22

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verified exact
arxiv_id, observed 2026-05-22T07:54:43.185224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T07:51:41.874143Z digest=sha256:12db3a31b709910d4b2bbf7893d3d515a509e7f34832068d066da71f1af2766f