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Paper Citation Record · LEDGER

Position: It's Time to Optimize LLMs for Self-Consistency

As of 10 August 2026, this Paper Citation Record lists 100 of 137 outbound references and 0 inbound Pith citation observations for arXiv:2608.05188.

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

pith.paper-citation-record.v1
2608.05188 v1

Coverage vector

measured 100 of 137 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:00:05.538459Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

100 of 137 outbound references displayed

  • verified exact1
  • verified fuzzy7
  • unresolved90
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e90ed867-a0dd-43a8-aa9a-e10bf015b356 · outbound

This paper cites Forty-second International Conference on Machine Learning , year =.

Position: It's Time to Optimize LLMs for Self-Consistency Forty-second International Conference on Machine Learning , year =

Reference 1

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Source-reported events for the cited work

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Observation a8d7244b-c9f9-4c21-8475-51bc40e29461 · outbound

This paper cites Lew and Tan Zhi-Xuan and Gabriel Grand and Vikash Mansinghka , title =.

Position: It's Time to Optimize LLMs for Self-Consistency Lew and Tan Zhi-Xuan and Gabriel Grand and Vikash Mansinghka , title =

Reference 2

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Observation facad052-fbac-4944-a7c0-0956bb985331 · outbound

This paper cites Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , year =.

Position: It's Time to Optimize LLMs for Self-Consistency Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , year =

Reference 3

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Observation 2a0b5bf1-ded8-4f9a-a966-dda986492f9e · outbound

This paper cites ICLR 2026 Workshop on Lifelong Agents: Learning, Aligning, Evolving , year =.

Position: It's Time to Optimize LLMs for Self-Consistency ICLR 2026 Workshop on Lifelong Agents: Learning, Aligning, Evolving , year =

Reference 4

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Observation 6558e500-5cb4-44f9-b9f5-6b229aa434a4 · outbound

This paper cites , journal=.

Position: It's Time to Optimize LLMs for Self-Consistency , journal=

Reference 5

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Observation cc16ae14-7418-4526-9bb5-e0e2f91aa71c · outbound

This paper cites International conference on machine learning , pages=.

Position: It's Time to Optimize LLMs for Self-Consistency International conference on machine learning , pages=

Reference 6

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Observation 57e17fc0-b61d-4743-b3f1-8d3dd79ad7f7 · outbound

This paper cites International Conference on Learning Representations , year=.

Position: It's Time to Optimize LLMs for Self-Consistency International Conference on Learning Representations , year=

Reference 7

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Observation 869a580f-5233-440a-8622-d31d7f34f5c8 · outbound

This paper cites The Eleventh International Conference on Learning Representations , year=.

Position: It's Time to Optimize LLMs for Self-Consistency The Eleventh International Conference on Learning Representations , year=

Reference 8

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source=arxiv_source observed=2026-08-07T01:00:00.071020Z digest=sha256:8729c9446d224337043b7ee62b6e143b37d8db1c36863a17ae4dd83498ad885f

Observation acbc8813-ad88-4128-aff0-06ac108f8943 · outbound

This paper cites AI safety via debate.

Position: It's Time to Optimize LLMs for Self-Consistency AI safety via debate

Reference 9

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Observation 3ea37a87-09c9-4673-94f2-0f5936be8b64 · outbound

This paper cites and Zoph, Barret and Mane, Dandelion and Vasudevan, Vijay and Le, Quoc V.

Position: It's Time to Optimize LLMs for Self-Consistency and Zoph, Barret and Mane, Dandelion and Vasudevan, Vijay and Le, Quoc V

Reference 10

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Observation b400ab30-98e6-462d-a5d9-564ea3168b8a · outbound

This paper cites ImageNet Classification with Deep Convolutional Neural Networks , url =.

Position: It's Time to Optimize LLMs for Self-Consistency ImageNet Classification with Deep Convolutional Neural Networks , url =

Reference 11

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Observation 091fa136-98ef-4ea0-ba87-6d6ef77b7d4a · outbound

This paper cites Adversarial Example Generation with Syntactically Controlled Paraphrase Networks.

Position: It's Time to Optimize LLMs for Self-Consistency Adversarial Example Generation with Syntactically Controlled Paraphrase Networks

Reference 12

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Observation fe90b36a-1bd8-479a-97b7-5f4ba434839b · outbound

This paper cites Semantically Equivalent Adversarial Rules for Debugging NLP models.

Position: It's Time to Optimize LLMs for Self-Consistency Semantically Equivalent Adversarial Rules for Debugging NLP models

Reference 13

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Observation 5f81436c-969f-4247-99cc-19b9b2c440dd · outbound

This paper cites and Wallach, Hanna and Cotterell, Ryan.

Position: It's Time to Optimize LLMs for Self-Consistency and Wallach, Hanna and Cotterell, Ryan

Reference 14

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Observation 02103931-5505-47fa-a12a-c12bf4c0b30a · outbound

This paper cites Journal of Machine Learning Research , volume=.

Position: It's Time to Optimize LLMs for Self-Consistency Journal of Machine Learning Research , volume=

Reference 15

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Observation 610d80a1-c4e9-4024-9871-241de5765c3e · outbound

This paper cites 2021 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2021 , eprint=

Reference 16

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Observation 38c96be3-4e77-44d4-9396-7340f649b78b · outbound

This paper cites Langley , title =.

Position: It's Time to Optimize LLMs for Self-Consistency Langley , title =

Reference 17

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Observation 7dc4851a-fd24-4b60-b591-7b84bc4996b1 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Position: It's Time to Optimize LLMs for Self-Consistency The Twelfth International Conference on Learning Representations , year=

Reference 18

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Observation 71e49842-7415-4a1b-865b-1db6ea498049 · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 19

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Observation 2520bde9-b858-4643-8aab-a53b1ba96355 · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 20

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Observation 697ae874-4b9a-431c-ac9b-09e8c292c694 · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 21

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Observation f3693410-ab59-4ea0-bc70-96ebdae17be2 · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 22

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Observation adbf3ab0-be97-4a32-a43f-1866bc774f42 · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 23

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Observation 529f7cf6-34ad-4231-aee5-cbeae873628a · outbound

This paper cites Newell and P.

Position: It's Time to Optimize LLMs for Self-Consistency Newell and P

Reference 24

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Observation f5ab3c6d-3a65-4bf8-85ef-0383ad4ef523 · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 25

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Observation d3d4ccc6-c3d6-4051-905f-37eb5d4aa6d6 · outbound

This paper cites Aho and Jeffrey D.

Position: It's Time to Optimize LLMs for Self-Consistency Aho and Jeffrey D

Reference 26

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Observation ec496f82-f1df-4ab5-acc7-d992fa8d0072 · outbound

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Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 27

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Observation 8a08f3e5-52d1-4f09-97e8-0be5dba60d26 · outbound

This paper cites Chandra and Dexter C.

Position: It's Time to Optimize LLMs for Self-Consistency Chandra and Dexter C

Reference 28

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Observation 899ed323-d3bb-4358-865f-32b63913bb4c · outbound

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Position: It's Time to Optimize LLMs for Self-Consistency Scalable training of

Reference 29

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Observation 0022adef-b8f3-4cb5-9df9-d189bab3eaf2 · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 30

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Observation dd3a4db6-735d-4273-a82f-40a2d26c1f23 · outbound

This paper cites NeurIPS , year =.

Position: It's Time to Optimize LLMs for Self-Consistency NeurIPS , year =

Reference 31

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Observation e0f72a31-5e9a-49e4-b057-c1fcd1e9d77f · outbound

This paper cites Tetreault , title =.

Position: It's Time to Optimize LLMs for Self-Consistency Tetreault , title =

Reference 32

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Observation 32037017-2bf5-406d-bdfd-e75c919e4796 · outbound

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Position: It's Time to Optimize LLMs for Self-Consistency A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data , Volume =

Reference 33

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Observation cd6d2886-4acd-4c3c-8159-5a637c7b141d · outbound

This paper cites The Reversal Curse:.

Position: It's Time to Optimize LLMs for Self-Consistency The Reversal Curse:

Reference 34

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Observation 055be35c-8f31-456b-a1a9-c13f8f4d6e2d · outbound

This paper cites Exploring the Sensitivity of LLM s' Decision-Making Capabilities: Insights from Prompt Variations and Hyperparameters.

Position: It's Time to Optimize LLMs for Self-Consistency Exploring the Sensitivity of LLM s' Decision-Making Capabilities: Insights from Prompt Variations and Hyperparameters

Reference 35

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Observation 07a5158b-28f2-42e4-a80f-01cb2307644a · outbound

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Position: It's Time to Optimize LLMs for Self-Consistency 2023 , eprint=

Reference 36

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Observation 2ee25e9a-0d62-47d8-ad84-f7ac1074eefe · outbound

This paper cites Emergent Misalignment: Narrow finetuning can produce broadly misaligned.

Position: It's Time to Optimize LLMs for Self-Consistency Emergent Misalignment: Narrow finetuning can produce broadly misaligned

Reference 37

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Observation 4c035069-a05d-4751-be96-7aa64e3d8d3f · outbound

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Position: It's Time to Optimize LLMs for Self-Consistency Fundamental Problems With Model Editing: How Should Rational Belief Revision Work in

Reference 38

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Observation c58cb977-ff2c-4a30-927f-63de70d0dd0e · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2024 , pages=.

Position: It's Time to Optimize LLMs for Self-Consistency Findings of the Association for Computational Linguistics: ACL 2024 , pages=

Reference 39

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source=arxiv_source observed=2026-08-07T01:00:02.714971Z digest=sha256:8fe44c10461376b4b5b03acba8260394f55df5ed528ca6aa68b189fda25d4468

Observation 5df23ee8-ec91-433f-b223-19032536c458 · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2023 , pages=.

Position: It's Time to Optimize LLMs for Self-Consistency Findings of the Association for Computational Linguistics: ACL 2023 , pages=

Reference 40

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source=arxiv_source observed=2026-08-07T01:00:02.751205Z digest=sha256:d72bc868a8fb58d5ed72a6e208b4f85f3c084f789952d27186060902c6b7ab2b

Observation 9f09b363-19cf-4b5b-89f5-c7add8f0eab7 · outbound

This paper cites Existing LLMs Are Not Self-Consistent For Simple Tasks.

Position: It's Time to Optimize LLMs for Self-Consistency Existing LLMs Are Not Self-Consistent For Simple Tasks

Reference 41

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local_arxiv, observed 2026-08-07T01:00:09.757846Z

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source=arxiv_source observed=2026-08-07T01:00:02.801114Z digest=sha256:32284c85ef40f023f71107b317465946bd2fc0a1a279a24caa3f8d21c5f15d0a

Observation 0a046ac6-1ae1-42b5-ae0b-3a955004e30a · outbound

This paper cites Transactions on Machine Learning Research , year =.

Position: It's Time to Optimize LLMs for Self-Consistency Transactions on Machine Learning Research , year =

Reference 42

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source=arxiv_source observed=2026-08-07T01:00:02.830124Z digest=sha256:f15432a6fd5601b719de6ff2cba8ee74be6b08165140ddd877c9e00d3389b538

Observation 348ff2bf-9412-4866-80a4-62eff95682f1 · outbound

This paper cites The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs.

Position: It's Time to Optimize LLMs for Self-Consistency The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs

Reference 43

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source=arxiv_source observed=2026-08-07T01:00:02.864040Z digest=sha256:b950cb3eb5d0b955f9a83d379e7951eb7f76d40bbbe35601c3a71279578fed5b

Observation 4247aa3f-4263-408e-a0f3-cecb57a5f0f6 · outbound

This paper cites Proceedings of the 30th Conference on Pattern Languages of Programs , pages=.

Position: It's Time to Optimize LLMs for Self-Consistency Proceedings of the 30th Conference on Pattern Languages of Programs , pages=

Reference 44

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source=arxiv_source observed=2026-08-07T01:00:02.899894Z digest=sha256:48c4411421204b12fec4e4fedba48864139c45042d23fe0d42131cb19a1acafa

Observation 7959ba4e-3792-4775-941a-e62ed1841805 · outbound

This paper cites arXiv preprint arXiv:2512.18311 , year=.

Position: It's Time to Optimize LLMs for Self-Consistency arXiv preprint arXiv:2512.18311 , year=

Reference 45

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source=arxiv_source observed=2026-08-07T01:00:02.950291Z digest=sha256:e7f3d6cc6aa8674064b81ab9c13966737c6c737ecebb5e21f6ac19d91740b4b4

Observation f9f76513-ea0a-44c3-bd5d-64938daac75c · outbound

This paper cites 2025 , note =.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , note =

Reference 46

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source=arxiv_source observed=2026-08-07T01:00:02.996732Z digest=sha256:115b9018952914a4334b5a1f82b177ea32ac8e20c96214f0b0d4ffccb86411af

Observation b52fe816-9294-4367-904a-815e2837ccbb · outbound

This paper cites 2025 , month = nov, url =.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , month = nov, url =

Reference 47

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source=arxiv_source observed=2026-08-07T01:00:03.034094Z digest=sha256:91e6be4ebad0fe311ef5c1ecd20566e27d1dfd9a84508ac86f6d88ff87c69dc4

Observation ca3167b5-9e56-42f3-8407-4bf9b1759a0e · outbound

This paper cites 2025 , month = dec, date =.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , month = dec, date =

Reference 48

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source=arxiv_source observed=2026-08-07T01:00:03.074425Z digest=sha256:c13d98f1ca61d0b7cd3f1042039cb51e0cab15b640daf28672ba13c8ced186da

Observation c037b9e0-8431-4ab2-9427-d6a75d805c1b · outbound

This paper cites Prompt Injection attack against LLM-integrated Applications.

Position: It's Time to Optimize LLMs for Self-Consistency Prompt Injection attack against LLM-integrated Applications

Reference 49

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source=arxiv_source observed=2026-08-07T01:00:03.128642Z digest=sha256:beb8da0452ceb980d714e7532045a10061c0a1701dd3f6d9f7d34294a99557d1

Observation d3701356-3dc4-4008-b1d6-abd0a49f0187 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Position: It's Time to Optimize LLMs for Self-Consistency Advances in Neural Information Processing Systems , volume=

Reference 50

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source=arxiv_source observed=2026-08-07T01:00:03.168539Z digest=sha256:7dd2f751de6e040073cb1ff8faaf02d03764de48dbb9ac849846b88c4621bfbc

Observation 2f6fcc8f-0817-4044-8971-ddbf7e95922a · outbound

This paper cites Attacking Large Language Models with Projected Gradient Descent.

Position: It's Time to Optimize LLMs for Self-Consistency Attacking Large Language Models with Projected Gradient Descent

Reference 51

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source=arxiv_source observed=2026-08-07T01:00:03.202299Z digest=sha256:c9b02ee8257ec2a94949fe19aed20ba85aa2f56f42b92beb5bf038eadb5d625a

Observation 467c59e1-c17c-42ac-81d1-f454e961d0b1 · outbound

This paper cites Same Question, Different Words: A Latent Adversarial Framework for Prompt Robustness.

Position: It's Time to Optimize LLMs for Self-Consistency Same Question, Different Words: A Latent Adversarial Framework for Prompt Robustness

Reference 52

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doi, observed 2026-08-07T01:00:08.795786Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:00:03.238559Z digest=sha256:e2a81690ffb6f8f18b0df5396e9067ea661798fe583b175b78152031345b6573

Observation b8a2a4ce-6b37-49c2-827f-4b079ba0dc9a · outbound

This paper cites Findings of the Association for Computational Linguistics: EACL 2024 , pages=.

Position: It's Time to Optimize LLMs for Self-Consistency Findings of the Association for Computational Linguistics: EACL 2024 , pages=

Reference 53

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source=arxiv_source observed=2026-08-07T01:00:03.273843Z digest=sha256:1db56a6ea1365c7cb1730ff9ec71ec76fcf111371b4fbc100f608a5da10aecda

Observation 6f94687b-1df6-4a7a-aa34-d570d123ee9f · outbound

This paper cites arXiv preprint arXiv:2511.08579 , year=.

Position: It's Time to Optimize LLMs for Self-Consistency arXiv preprint arXiv:2511.08579 , year=

Reference 54

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source=arxiv_source observed=2026-08-07T01:00:03.310535Z digest=sha256:37058fa8299d834b4057a9e7ef8616df0a6d63f9418d6cb7a77097f473eed9c3

Observation 84a33b69-351a-4a29-a393-4206ca9611c7 · outbound

This paper cites arXiv preprint arXiv:2510.05092 , year=.

Position: It's Time to Optimize LLMs for Self-Consistency arXiv preprint arXiv:2510.05092 , year=

Reference 55

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source=arxiv_source observed=2026-08-07T01:00:03.343011Z digest=sha256:3c652e6f6080833b9bf5bce613d86025b2b49895346763066b5322543393bd93

Observation 5710649b-d9fa-48b7-91e1-170662fee5e7 · outbound

This paper cites 2025 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , eprint=

Reference 56

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source=arxiv_source observed=2026-08-07T01:00:03.373258Z digest=sha256:2848bba32b6bf3ce6ca5b5930c4c6c9a5178b632d23612dbbda1b0ba5e7381e5

Observation 35155c98-0973-46b5-8e3a-f506d0b29627 · outbound

This paper cites Looking Inward: Language Models Can Learn About Themselves by Introspection.

Position: It's Time to Optimize LLMs for Self-Consistency Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 57

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source=arxiv_source observed=2026-08-07T01:00:03.398770Z digest=sha256:b9399cbb600b47aa894696b86d50fe6b098e4b487307dfc57e5fca3ee0378dc3

Observation c8706016-1a67-475e-8c14-aa5d5052e18c · outbound

This paper cites Designing a Dashboard for Transparency and Control of Conversational AI.

Position: It's Time to Optimize LLMs for Self-Consistency Designing a Dashboard for Transparency and Control of Conversational AI

Reference 58

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source=arxiv_source observed=2026-08-07T01:00:03.431188Z digest=sha256:fa578a06e1c45c4bfd23d3c67814f106ac108e31bd744366d260ce1721e4c55b

Observation 5be114f6-f0d4-4c22-b0f2-3ac9a2bb46d4 · outbound

This paper cites Forty-first International Conference on Machine Learning , year=.

Position: It's Time to Optimize LLMs for Self-Consistency Forty-first International Conference on Machine Learning , year=

Reference 59

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source=arxiv_source observed=2026-08-07T01:00:03.457643Z digest=sha256:81d1f8ebdb6a293826d9ba86401e63693cfcfca23aae08cccf18afbb5989a46c

Observation 4c57d267-b80b-4dbc-b413-8d7a60f91bd9 · outbound

This paper cites 2021 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2021 , eprint=

Reference 60

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source=arxiv_source observed=2026-08-07T01:00:03.492465Z digest=sha256:4b7fb27d09463f6d872dfa88871f0dd8b197a7278c72bde2b13560ed09455af6

Observation bb2c52b8-43cb-476a-9751-68aa94b26fc6 · outbound

This paper cites A Benchmark Dataset for Learning to Intervene in Online Hate Speech.

Position: It's Time to Optimize LLMs for Self-Consistency A Benchmark Dataset for Learning to Intervene in Online Hate Speech

Reference 61

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source=arxiv_source observed=2026-08-07T01:00:03.534854Z digest=sha256:f759e8a8de3ae830340de3f03081fb77c6068aefe2cba26d0d3281270433fa89

Observation 531206ec-d29e-4987-a1a7-98c1cdba086b · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 , year =.

Position: It's Time to Optimize LLMs for Self-Consistency Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 , year =

Reference 62

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source=arxiv_source observed=2026-08-07T01:00:03.577218Z digest=sha256:5b5a3752c314f3b862986a85cb2e83b0e7da12c4b518406e5c93e30e04e2bf90

Observation 370552d5-5df1-432d-b322-8be6582d9771 · outbound

This paper cites Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts.

Position: It's Time to Optimize LLMs for Self-Consistency Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts

Reference 63

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source=arxiv_source observed=2026-08-07T01:00:03.602192Z digest=sha256:c39bff875d203d6c8e6325a0db9b1851dace5d5cdfa417b162e28fcc622b960c

Observation 74a2332a-1a25-48b7-b016-463eb0901c52 · outbound

This paper cites Logic, language, and security: essays dedicated to Andre Scedrov on the occasion of his 65th birthday , pages=.

Position: It's Time to Optimize LLMs for Self-Consistency Logic, language, and security: essays dedicated to Andre Scedrov on the occasion of his 65th birthday , pages=

Reference 64

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source=arxiv_source observed=2026-08-07T01:00:03.642054Z digest=sha256:90b3aae71c8f869b4ef15e729049030f97f47ae06ac3d601ff74290c9a2f4efc

Observation 42495f78-5459-4bbb-86fe-7db80ebfaa70 · outbound

This paper cites Measuring and Reducing Gendered Correlations in Pre-trained Models.

Position: It's Time to Optimize LLMs for Self-Consistency Measuring and Reducing Gendered Correlations in Pre-trained Models

Reference 65

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source=arxiv_source observed=2026-08-07T01:00:03.678214Z digest=sha256:84674b2e37fbe5d4c4073b545f3020532806bcaea627e3ac20c6eb8bd5d960f9

Observation aae94d49-cd63-46c6-b266-6a3eeba0a79b · outbound

This paper cites Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society , pages =.

Position: It's Time to Optimize LLMs for Self-Consistency Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society , pages =

Reference 66

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source=arxiv_source observed=2026-08-07T01:00:03.707309Z digest=sha256:bf1f7f77940a0d6d2f4fb7adbda879193277064c561db36060ae5e11cdc7b4c9

Observation 186ae3c9-cc82-45b9-962a-3cc8c51c307b · outbound

This paper cites and Rossi, Ryan A.

Position: It's Time to Optimize LLMs for Self-Consistency and Rossi, Ryan A

Reference 67

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source=arxiv_source observed=2026-08-07T01:00:03.744783Z digest=sha256:e996cbc2657cd51dac3bc363063a5315869b72ced6468c55f59035c1e54dc081

Observation d8bd19a9-2e85-41dc-a8c3-55b3f3d19e7c · outbound

This paper cites and Rambachan, Ashesh and Mullainathan, Sendhil , booktitle =.

Position: It's Time to Optimize LLMs for Self-Consistency and Rambachan, Ashesh and Mullainathan, Sendhil , booktitle =

Reference 68

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source=arxiv_source observed=2026-08-07T01:00:03.777948Z digest=sha256:175fe32c8b5ac0d2cdb556529154c6317f29c908bc02d44bede90b676730d8cf

Observation 1f554348-a0a4-488c-a4d9-c049d64e80e1 · outbound

This paper cites Highly accurate protein structure prediction with.

Position: It's Time to Optimize LLMs for Self-Consistency Highly accurate protein structure prediction with

Reference 69

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source=arxiv_source observed=2026-08-07T01:00:03.818316Z digest=sha256:be9a72d6fd3d00a1038234dbeca1a44e9966bc45fc63acdd5ccd895b6f93c3a1

Observation 8d35d536-0ec7-42fb-9fd7-d245812d75ec · outbound

This paper cites 2025 , month = feb, day =.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , month = feb, day =

Reference 70

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source=arxiv_source observed=2026-08-07T01:00:03.853250Z digest=sha256:a4dc7604e2c7dfcc744fefeeeac31b9779c21b7d2e5b705f48cbba321d5970f0

Observation e9261986-e2b4-47fb-83dc-78acc858b010 · outbound

This paper cites 2025 , url=.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , url=

Reference 71

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source=arxiv_source observed=2026-08-07T01:00:03.892656Z digest=sha256:fe08853b6158e77017a3004870deea5787513aca49b0c14ac7ff4f528ea2e0e1

Observation af4b989b-28a3-40b0-8841-89303ad98f45 · outbound

This paper cites Position: Will we run out of data? Limits of.

Position: It's Time to Optimize LLMs for Self-Consistency Position: Will we run out of data? Limits of

Reference 72

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source=arxiv_source observed=2026-08-07T01:00:03.957174Z digest=sha256:710b2a755fea8c5c712d8b50b79f630a77f9ed21a13103f5a14f77f6b887bb06

Observation ded8bacf-9508-4591-8b77-aa50627ea8ed · outbound

This paper cites 2024 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2024 , eprint=

Reference 73

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source=arxiv_source observed=2026-08-07T01:00:04.032184Z digest=sha256:553d0f595afe2d6f8afc5db96d2ca3635244e649f56a0a4f89f04491073df91e

Observation 50a6009a-a0e6-4cb6-a2d5-3eca3430d478 · outbound

This paper cites 2025 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , eprint=

Reference 74

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source=arxiv_source observed=2026-08-07T01:00:04.083412Z digest=sha256:d01ff59bf78f43c88febdde5c892348009cfa7d7ba6c9d4459885c885944b0c4

Observation 6f999f18-5ff4-4081-9dc3-237600849dc4 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Position: It's Time to Optimize LLMs for Self-Consistency The Twelfth International Conference on Learning Representations , year=

Reference 75

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source=arxiv_source observed=2026-08-07T01:00:04.150341Z digest=sha256:3dc24c1fda30d36b7c4f0cd83983cbce8100c51c3f304fd332514699eb16f7ee

Observation aa64b172-31fb-47d1-b215-90bdd00d1e6d · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 76

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source=arxiv_source observed=2026-08-07T01:00:04.189873Z digest=sha256:a02938bc998f007a3b9e917f976106c0aef9a52149e225bc33f3b6fec06c9e6c

Observation 0b59c8d4-b23b-45e7-b4a5-6685a77dae00 · outbound

This paper cites What Did I Do Wrong? Quantifying LLM s' Sensitivity and Consistency to Prompt Engineering.

Position: It's Time to Optimize LLMs for Self-Consistency What Did I Do Wrong? Quantifying LLM s' Sensitivity and Consistency to Prompt Engineering

Reference 77

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source=arxiv_source observed=2026-08-07T01:00:04.283696Z digest=sha256:824af9cd115600a4a9d06e5587849c51ec836097d0dddc35a799e58549cfa663

Observation a744e4f3-c032-4dd9-b761-b344b05b4e5b · outbound

This paper cites Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 , pages =.

Position: It's Time to Optimize LLMs for Self-Consistency Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 , pages =

Reference 78

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source=arxiv_source observed=2026-08-07T01:00:04.324946Z digest=sha256:82c716b414aa936c2930e27e10480a9fde8639cee48fd472c1c7497e843cfa1f

Observation 58a5240f-5ee3-42b4-b91b-06bd4c537ab1 · outbound

This paper cites First Workshop on Foundations of Reasoning in Language Models , year=.

Position: It's Time to Optimize LLMs for Self-Consistency First Workshop on Foundations of Reasoning in Language Models , year=

Reference 79

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no resolver link, observed 2026-08-07T01:00:04.405254Z

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source=arxiv_source observed=2026-08-07T01:00:04.405254Z digest=sha256:ed3e43b9547dbf31d8c0b9e7fc454e3593f7d2457d74f315485b74192a8320df

Observation 567a9d5e-9ebb-4d7f-a119-37014f8577b1 · outbound

This paper cites Bell , booktitle=.

Position: It's Time to Optimize LLMs for Self-Consistency Bell , booktitle=

Reference 80

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:00:04.462238Z digest=sha256:a6be04a4bb2d71105cb4ebd2f6bd8b51f13266a7f506121689fc3c3471c76136

Observation 8c8f1a32-2e48-4e16-84b5-e66407e83b5e · outbound

This paper cites Transactions on Machine Learning Research , issn=.

Position: It's Time to Optimize LLMs for Self-Consistency Transactions on Machine Learning Research , issn=

Reference 81

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no resolver link, observed 2026-08-07T01:00:04.581949Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:00:04.581949Z digest=sha256:8f58a5bd1f9861da49c4be32a1329ae80d391e102ed63a07045c88aaa4f7c757

Observation b302514d-8ab7-4fa0-8eea-49a8990029fd · outbound

This paper cites Journal of the American statistical Association , volume=.

Position: It's Time to Optimize LLMs for Self-Consistency Journal of the American statistical Association , volume=

Reference 82

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no resolver link, observed 2026-08-07T01:00:04.632449Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:00:04.632449Z digest=sha256:c762599ab1651aff75670b3e4d11a5b2acaedb2804690a93e995545282cf0823

Observation 39592e61-bbf8-40d1-b6f8-a485a784f964 · outbound

This paper cites Beyond Binary Rewards: Training.

Position: It's Time to Optimize LLMs for Self-Consistency Beyond Binary Rewards: Training

Reference 83

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verified fuzzy
raw_fallback, observed 2026-08-07T01:00:14.172064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:00:04.700103Z digest=sha256:702c1c9e05886fd81bd9cbb98fa6f694529f9f9db9968c3597da5ea870df772e

Observation 134876b5-d102-4f61-933e-cce71c257a27 · outbound

This paper cites Taming Overconfidence in.

Position: It's Time to Optimize LLMs for Self-Consistency Taming Overconfidence in

Reference 84

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verified fuzzy
raw_fallback, observed 2026-08-07T01:00:13.968074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:00:04.739140Z digest=sha256:7037aa0250a2e41e5c45ad40757c16e2fc23b2ff7e395637ef36f3a236280c08

Observation 3ad2562a-255d-42a9-99f8-60657a1b7bf9 · outbound

This paper cites Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style , url =.

Position: It's Time to Optimize LLMs for Self-Consistency Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style , url =

Reference 85

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raw_fallback, observed 2026-08-07T01:00:13.746400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:00:04.790567Z digest=sha256:f2d2f3ed5709f80aff19ab2d4a0c607e1e4d5737b9fd7f95778f6b8df982d4ae

Observation 456f6f3e-53ac-477b-a5f3-c370ba8c1f2b · outbound

This paper cites and Darzi, Ara and Etemadi, Mozziyar and Garcia-Vicente, Florencia and Gilbert, Fiona J.

Position: It's Time to Optimize LLMs for Self-Consistency and Darzi, Ara and Etemadi, Mozziyar and Garcia-Vicente, Florencia and Gilbert, Fiona J

Reference 86

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:00:04.870308Z digest=sha256:2658b89d4bb1984c2c85bdd45ab5ae9ff098f5f927005dd6c0dafaa427687765

Observation a743035c-3e22-4f7b-8048-84edbfc5784c · outbound

This paper cites International Conference on Learning Representations , year=.

Position: It's Time to Optimize LLMs for Self-Consistency International Conference on Learning Representations , year=

Reference 87

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source=arxiv_source observed=2026-08-07T01:00:04.910308Z digest=sha256:4891cb8b22681b5321dcfb90d0e9d82c1154de11dce13b9d3d8ba92e45d58f85

Observation dc95c206-a00b-4b22-b2fb-6e5e7a777844 · outbound

This paper cites an unresolved cited work.

Position: It's Time to Optimize LLMs for Self-Consistency Unresolved cited work

Reference 88

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source=arxiv_source observed=2026-08-07T01:00:04.961726Z digest=sha256:eb276c50d12c853888b2dddd2d627bb14e14e0321737f8392fc240be48446708

Observation e1bbe726-1d4f-4ab1-b67f-9bb97b0457d4 · outbound

This paper cites Training language models to follow instructions with human feedback , url =.

Position: It's Time to Optimize LLMs for Self-Consistency Training language models to follow instructions with human feedback , url =

Reference 89

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source=arxiv_source observed=2026-08-07T01:00:05.010917Z digest=sha256:35936f5ac234a6638aba3ac07b820ab9307fa233cfda7fd17560e1d240b5dd4d

Observation a5b30529-1350-45ae-8280-0135a486c212 · outbound

This paper cites 2025 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , eprint=

Reference 90

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:00:05.064810Z digest=sha256:54fbcb511a15ae6cbd260372eb25aba564d62283657ff12ebd20c06ff453b960

Observation 2fbc9d49-e613-49ec-9098-a69657b18ff1 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Position: It's Time to Optimize LLMs for Self-Consistency The Twelfth International Conference on Learning Representations , year=

Reference 91

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source=arxiv_source observed=2026-08-07T01:00:05.113646Z digest=sha256:ce4702fc73fd170f6d579fb8e7707afa8559bbdf9e51ad692642dd899150d5c2

Observation b866670a-4576-4f2b-bd4f-e535fdf2e4aa · outbound

This paper cites Science , year =.

Position: It's Time to Optimize LLMs for Self-Consistency Science , year =

Reference 92

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source=arxiv_source observed=2026-08-07T01:00:05.143765Z digest=sha256:eb3bde30dcfcf94ebb03042c84a6e546a72bc5bf546ef989f20fd49daa8f064e

Observation 83061ecd-a0f8-43e3-8bc0-d0cc184b11ca · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2025 , year =.

Position: It's Time to Optimize LLMs for Self-Consistency Findings of the Association for Computational Linguistics: EMNLP 2025 , year =

Reference 93

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source=arxiv_source observed=2026-08-07T01:00:05.173696Z digest=sha256:7028375c9521f92e334ef9e6deb9ffb63e46396ffff62af4e85d8da4369c8745

Observation 79c49949-3d19-424c-b7b5-35ad2838c0d3 · outbound

This paper cites Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society , author=.

Position: It's Time to Optimize LLMs for Self-Consistency Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society , author=

Reference 94

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no resolver link, observed 2026-08-07T01:00:05.254558Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:00:05.254558Z digest=sha256:fb3a8e6d79fd09a966f9aa8894416df7558ba594473634851786d5cdb91d4bb1

Observation c08add28-008d-4c07-a974-79c20a406d08 · outbound

This paper cites Goodfire , year =.

Position: It's Time to Optimize LLMs for Self-Consistency Goodfire , year =

Reference 95

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verified fuzzy
raw_fallback, observed 2026-08-07T01:00:13.506604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:00:05.287762Z digest=sha256:7512a1db173d11c3e1bfca5745f8f1a519a2bb1feea5521536bfee42dbfaa575

Observation 5b8ab816-8b26-4f64-91d6-25d106b51c1b · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Position: It's Time to Optimize LLMs for Self-Consistency The Twelfth International Conference on Learning Representations , year=

Reference 96

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verified fuzzy
raw_fallback, observed 2026-08-07T01:00:13.334348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:00:05.335196Z digest=sha256:d7f6ff9cfd1a2b1e89dc4a29fd969d20eec109201a9c94a18cd0f9446d2be9f1

Observation ca98f7f3-4ffc-422a-a313-7eb5aff739f2 · outbound

This paper cites 2024 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2024 , eprint=

Reference 97

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source=arxiv_source observed=2026-08-07T01:00:05.390394Z digest=sha256:85f25151223b1f3130df7c83f6636c3b846134bfff77ca114ac0e8c3a57e2dda

Observation 2116e455-6a34-4de1-9f13-9771682e4607 · outbound

This paper cites 2024 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2024 , eprint=

Reference 98

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no resolver link, observed 2026-08-07T01:00:05.427725Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:00:05.427725Z digest=sha256:26ceb1bf8659e400db0f6e65121f6a11a74cbd8d97cd94b9c982a7216d36d6a5

Observation 2229003b-0522-4656-a36b-ea3af1f58f5f · outbound

This paper cites 2025 , eprint=.

Position: It's Time to Optimize LLMs for Self-Consistency 2025 , eprint=

Reference 99

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verified fuzzy
raw_fallback, observed 2026-08-07T01:00:13.139690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:00:05.472750Z digest=sha256:352403cba271964c39d348ff19718c631c36447ea81141ff0b0f13452837c5b6

Observation fb0a62de-816c-409f-8a84-40a342faf50a · outbound

This paper cites The Alignment Problem from a Deep Learning Perspective , booktitle =.

Position: It's Time to Optimize LLMs for Self-Consistency The Alignment Problem from a Deep Learning Perspective , booktitle =

Reference 100

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raw_fallback, observed 2026-08-07T01:00:12.951199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:00:05.538459Z digest=sha256:050a8877457138ce13483c051c7a5b93429e6f69315a045ec9f7045a62a106bb

Pith citing papers

No inbound Pith citation observations are available.