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Paper Citation Record · LEDGER

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 2 inbound Pith citation observations for arXiv:2506.13681.

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

pith.paper-citation-record.v1
2506.13681 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:31:57.090248Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:49:03.090744Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:13:23.801132Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved28
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e8dcc021-4f6c-4f67-91dc-c33f88444fc4 · outbound

This paper cites A learning algorithm for boltzmann machines.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models A learning algorithm for boltzmann machines

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.441350Z digest=sha256:af93bb7ef8a0da784737a327c40330a47594cf008eea7d0f3128c79666e10b35

Observation 2a7b3092-29d8-4d1a-9d8a-47ce63def399 · outbound

This paper cites Mirostat: A Neural Text Decoding Algorithm that Directly Controls Perplexity.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Mirostat: A Neural Text Decoding Algorithm that Directly Controls Perplexity

Reference 2

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T00:31:55.463720Z digest=sha256:0a8d79dde13ae87308f39634edda239e5b149d0fa1bbec6065f77154485e44bf

Observation ae03c04a-fd84-42c9-a0de-1407915bc635 · outbound

This paper cites Lessons from the Trenches on Reproducible Evaluation of Language Models.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Lessons from the Trenches on Reproducible Evaluation of Language Models

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.489701Z digest=sha256:ce2a91ae6e85a178b637eaad0382a96f8d6101c1282c76c25fa2fa7ade4b3bec

Observation 3c9e3d06-27a1-4597-a771-bcf490d1e2bd · outbound

This paper cites Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Reference 4

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no resolver link, observed 2026-08-07T00:31:55.513078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.513078Z digest=sha256:d14e4ac868be8b13833f58e67c7eea2b6316b8e45bf11f66ca6f476516ccfad1

Observation 9b3e1509-4d3a-431d-b48a-814c81cce5b3 · outbound

This paper cites All that’s ‘human’is not gold: Evaluating human evaluation of generated text.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models All that’s ‘human’is not gold: Evaluating human evaluation of generated text

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-07T00:31:58.183104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T00:31:55.537274Z digest=sha256:82f0171d27e772a55901fbeb22429d363648af6e598759db16130e8f81cd4d1f

Observation 9dac3f31-58ca-4613-a4ef-147a0fa15ce6 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Training Verifiers to Solve Math Word Problems

Reference 6

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no resolver link, observed 2026-08-07T00:31:55.565400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.565400Z digest=sha256:d41782a82f792015783feca915ec55b6b7e4f052ab66df0fdddaad0287441df3

Observation cebc7a95-0549-483c-855c-5a9d1e63926f · outbound

This paper cites Alpacafarm: A simulation framework for methods that learn from human feedback.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Alpacafarm: A simulation framework for methods that learn from human feedback

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.593366Z digest=sha256:0d4b119ba99012a8de0fcc508a1f468dd8b318e6fd645cc9fee4e2227a774729

Observation f1b2d0a9-8605-4548-b823-3041c1e64597 · outbound

This paper cites Hierarchical Neural Story Generation.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Hierarchical Neural Story Generation

Reference 8

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no resolver link, observed 2026-08-07T00:31:55.619376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.619376Z digest=sha256:0dafd26127790bbba3dec4eb4e6d7759e0246b77839b97a6ada68862b2602d7f

Observation f79fa9a3-b52d-4d9c-82f3-8e145a4be9a8 · outbound

This paper cites A framework for few-shot language model evaluation.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models A framework for few-shot language model evaluation

Reference 9

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unresolved
no resolver link, observed 2026-08-07T00:31:55.637364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.637364Z digest=sha256:c3ee5a5e4b15f2b0c5630ee839cb59473c8b7e9215d6e38c81258988d756abed

Observation 4b9a0148-f519-44b5-ae65-fe3a2859a2e8 · outbound

This paper cites The Llama 3 Herd of Models.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models The Llama 3 Herd of Models

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.669362Z digest=sha256:85e3c30ae2d410059da1fdaf31a21b1ad95562e56120a869fd38cc114f84e756

Observation fed55ea1-2044-49be-9455-f1d2eea268bd · outbound

This paper cites Truncation sampling as language model desmoothing.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Truncation sampling as language model desmoothing

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:31:58.045129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T00:31:55.702401Z digest=sha256:8819a535237bd445cbb403ec7915f73f7590a35d3512dfb2badb6176ae348138

Observation 78bfc7e5-da21-453d-ba15-e801554402c9 · outbound

This paper cites The curious case of neural text degeneration.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models The curious case of neural text degeneration

Reference 12

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no resolver link, observed 2026-08-07T00:31:55.748459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.748459Z digest=sha256:432e4180e3e320f537ffb03feec8975d2c6f9b0f79cca5ffd90e90da5f905c04

Observation d0b60f6a-0eed-4a4f-99de-a18e3c05246f · outbound

This paper cites Twenty years of confusion in human evaluation: Nlg needs evaluation sheets and standardised definitions.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Twenty years of confusion in human evaluation: Nlg needs evaluation sheets and standardised definitions

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-07T00:31:57.899068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T00:31:55.782082Z digest=sha256:d7fbcad45ffe18e53d1cead9e1e13ed8baef829efb67d4114810c5e9e41451a7

Observation 09d6e90e-bba0-4890-9cb1-187c5f4cdcb6 · outbound

This paper cites Best-of-N Jailbreaking.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Best-of-N Jailbreaking

Reference 14

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no resolver link, observed 2026-08-07T00:31:55.835946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.835946Z digest=sha256:0a1d08ce602e4c0c20046cb6f95d826aa826cf30e1fb731c8adee699eb61bb81

Observation 06acc435-58f0-4929-bef1-202e0f9db2c6 · outbound

This paper cites Mistral 7B.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Mistral 7B

Reference 15

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.879471Z digest=sha256:a1c01675b0062487ad08d7593e0d7fce53035e2b0c92adfdc50cae982c7d2768

Observation 615b277e-dbe7-4134-9274-7e992d1817d0 · outbound

This paper cites GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation

Reference 16

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no resolver link, observed 2026-08-07T00:31:55.913375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.913375Z digest=sha256:6425f9f613511f64d708932112d6fbda0532dd16c148b712728faa0cc8a9c092

Observation 9b4e5a4b-cb9c-4437-9fbb-da517ee04f3b · outbound

This paper cites Holistic Evaluation of Language Models.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Holistic Evaluation of Language Models

Reference 17

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no resolver link, observed 2026-08-07T00:31:55.961100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.961100Z digest=sha256:d8e35906d8f2aff323a170925211c3aa84ab34d79b35353607fa0fea4c705c95

Observation 33e20b17-c968-485a-bb33-cfa6b64915d5 · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models WebGPT: Browser-assisted question-answering with human feedback

Reference 18

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no resolver link, observed 2026-08-07T00:31:56.008652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.008652Z digest=sha256:08a215927f74ecf5aeabdd0d6af70a94df6f693c9b418a4c6ec8d21b93ceab7f

Observation 313b3695-ad47-4e79-879f-e56df6c2a21b · outbound

This paper cites Qwen2.5 Technical Report.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Qwen2.5 Technical Report

Reference 20

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no resolver link, observed 2026-08-07T00:31:56.081070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.081070Z digest=sha256:0e02c9a781e88701e55de983a550d535a60db1eae241028f75f5a0c46c66fc94

Observation c239b07c-5622-45bd-94d1-0ca3336170a3 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 21

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no resolver link, observed 2026-08-07T00:31:56.121768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.121768Z digest=sha256:e4124e8081521a3823ce83f768035c4ce966b9bfdd080bb0a0089a3eb4674630

Observation ca7b6a6a-36c9-41d9-9879-c58c496484c9 · outbound

This paper cites Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions

Reference 22

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no resolver link, observed 2026-08-07T00:31:56.162766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.162766Z digest=sha256:9f1cb09f99e24d304222f02513ae5634e85fc9e4ef8cb7275cb3d2d9cd3a06ba

Observation ac143d01-b5cc-471d-87fb-70751c3cedd8 · outbound

This paper cites How Do Large Language Monkeys Get Their Power (Laws)?.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models How Do Large Language Monkeys Get Their Power (Laws)?

Reference 23

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no resolver link, observed 2026-08-07T00:31:56.210081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.210081Z digest=sha256:8a42285ad4fa0c0c601e267f4f9e908761a6eb85eeca6b771a5934be3901ceb7

Observation 523f81be-7186-450e-9f35-57f6dd470994 · outbound

This paper cites Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks

Reference 24

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metadata mismatch
local_arxiv, observed 2026-08-07T00:31:57.274449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T00:31:56.255771Z digest=sha256:215689683e58aa78002f16b0bef5a854240153ec3d76be794fe729a8f9290c82

Observation a67831ca-7072-4711-b97e-397476428a2b · outbound

This paper cites Learning to summarize with human feedback.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Learning to summarize with human feedback

Reference 25

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no resolver link, observed 2026-08-07T00:31:56.309943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.309943Z digest=sha256:f976e8cb4fd49ec74c7ad71893eff71004040c358aa356004aff2fc9a6a4aebd

Observation c5db7987-a4ed-4a92-8dba-5edd52d2596c · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 26

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no resolver link, observed 2026-08-07T00:31:56.373953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.373953Z digest=sha256:db281d159d6ec2c0ad3987cb540c384b82209d4577705cb7a1095fcf827613ee

Observation da8861f4-44c7-4d06-856f-0f855884c2d5 · outbound

This paper cites Best practices for the human evaluation of automatically generated text.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Best practices for the human evaluation of automatically generated text

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T00:31:57.775291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T00:31:56.444503Z digest=sha256:d9a41caaf8363744ee6b2bf1c3062a9689480f5476ea5c9c818759cb6bb550ee

Observation a71ed187-186d-4b4f-9697-0ac273e92bb4 · outbound

This paper cites Do Large Language Model Benchmarks Test Reliability?.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Do Large Language Model Benchmarks Test Reliability?

Reference 28

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unresolved
no resolver link, observed 2026-08-07T00:31:56.526077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.526077Z digest=sha256:b0b879762f43239e879012fecc9514ecb40aa4a76877f9de12ac5b8f130e590b

Observation 48d20450-4ce6-4684-b241-ea212b417015 · outbound

This paper cites Investigating Non-Transitivity in LLM-as-a-Judge.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Investigating Non-Transitivity in LLM-as-a-Judge

Reference 29

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unresolved
no resolver link, observed 2026-08-07T00:31:56.606349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.606349Z digest=sha256:7378bfd4b05a5cd9f6e536257932ddbcf56564022e4903e9394b04a6d46424d1

Observation 0db17fcf-b662-4fd6-aa54-17928e53e6eb · outbound

This paper cites A careful examination of large language model performance on grade school arithmetic.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models A careful examination of large language model performance on grade school arithmetic

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:31:57.661575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T00:31:56.681151Z digest=sha256:78dbc02e60c4f2216ac04d6391676d77c78ff0408dbfdad191e62a62cbc85993

Observation 970e9838-cdef-4d8c-a380-973dc9418e95 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 31

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no resolver link, observed 2026-08-07T00:31:56.784918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.784918Z digest=sha256:551ca6a51e4b459a58a10d603c41b08a9082647fa616d9e35400e85a094db94a

Observation 656dbe27-9ce0-4b9c-ba1a-4deeea2c5c50 · outbound

This paper cites write newline.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models write newline

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.873071Z digest=sha256:f87bc6d4aa38bc1c5a82c18d6de65ba1391d400a4bcc754ac383a2c0b0a200d4

Observation f0efe822-62ee-4987-8c3d-439a686af387 · outbound

This paper cites @esa (Ref.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models @esa (Ref

Reference 33

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no resolver link, observed 2026-08-07T00:31:56.947707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.947707Z digest=sha256:08f6bae6483981e7ca3c98939f8e87cf0bd6d2c967fe43cfcb7faecafea7f933

Observation ba3415b9-00c1-4e09-b128-b39339e4f8e9 · outbound

This paper cites an unresolved cited work.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Unresolved cited work

Reference 34

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unresolved
no resolver link, observed 2026-08-07T00:31:57.035227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:57.035227Z digest=sha256:9e3f2f75a629dd3ccc3a3d1f70e1b1ab50110201e05946a6646b6f3eb840468e

Observation 9963d8d9-259b-4585-85c8-9eb804606146 · outbound

This paper cites an unresolved cited work.

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models Unresolved cited work

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:57.090248Z digest=sha256:b7b547575a0830c9d93e5b4b294aad3a4cd8ab766437a07de5928a2e1cb00bfe

Pith citing papers

Observation b699c5cc-096b-4905-afd9-1ec58f34a800 · inbound

Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track cites this paper.

Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models

Reference 83

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:13:23.915811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-06T23:13:20.622187Z digest=sha256:e89c53cca40383dd4671d7e3197168b4284b14e9f129f763c8fbd62e074ed93b

Observation 5211dacc-8084-4023-b3be-f4ce55c42205 · inbound

Test-Time Scaling in Reasoning LLMs: Inference Regimes, Evaluation, and Reproducibility cites this paper.

Test-Time Scaling in Reasoning LLMs: Inference Regimes, Evaluation, and Reproducibility Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models

Reference 4

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unresolved
no resolver link, observed 2026-08-15T14:49:03.090744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:49:03.090744Z digest=sha256:f9d1a9a70b0e2518584cdd2ead75337b45a29f293e0329f95cff5ae6348d6dc9