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Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation 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 35 of 35 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:13:20.622187Z

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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no resolver link, observed 2026-08-07T00:31:55.441350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.441350Z digest=sha256:ec7df26fc6d3968902eb92ac8f3638d834f7471a00b322adaaf617ea77a00fe9

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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no resolver link, observed 2026-08-07T00:31:55.463720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.463720Z digest=sha256:31d9200d50df38fad1d87890fb94390d9b15f5fc4d37835c6c5e7fc0772d524b

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:dbd041c3d4114158fd505ea75dbcdb22c8ce2b20da43562a2406ddba71caa925

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=sha256:7c72590ee121d6338a60d196fa9021666268d23b644783b52765653a8b287b02

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T00:31:55.537274Z digest=sha256:cd37efc57e588449de51a8b636bed3fdabf84da8fdaf56b33f789d9442c1e1f4

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=sha256:23dfb37b74dfb94e7c6319da9f4d3f808d755d79fdbd208ba54f69e0a0dc9ec0

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=sha256:65f69eee9682cb187443bb72ef8b1625057990dffbcf11631afeefcd94b3bb92

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.619376Z digest=sha256:97431e6b2498458c69956dc423dc8448dc465d9bbc70330f1b6010b0eb0449d8

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=sha256:20040e0894cabe96ea6459ef697bd78d2b1db8bc0bbe837d6c1cf10508530db8

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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no resolver link, observed 2026-08-07T00:31:55.669362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.669362Z digest=sha256:14494c4fd5b8151f0e59279af54e4295d5569dbd6e2c620b0b2bcf3a4735fe6c

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T00:31:55.702401Z digest=sha256:260fa2ffd3a3423dea149a8f76065865d979e0f7cb02b12718c912e5026d19a6

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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unresolved
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=sha256:4e323acef5bd0686a6ea546059def0992cc06f8f41d3a8eec0e4c645e99414b7

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

Resolution
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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T00:31:55.782082Z digest=sha256:f0233ab52549ff92e55e05b976bf73ebd28c2bf7246b2ac54ecb27fd1fe9a99d

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.835946Z digest=sha256:474cff1c8fa07dd94cebdc6621681520d5f3de6ee014a7cae778144c35c96103

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:55.879471Z digest=sha256:a25cc6356dfaaa6f8f2fdb3a6631b225ff76851f868b8720ec87108f0f0eff51

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=sha256:95fc88d70a7d5fafd6d4a5a185702b91245b2f65e3f881b3ff8c82a2a1ef0791

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=sha256:870b548ecda62e7f5d8a6964fa91140db0a9479790d14ca8f63244b9897db5f0

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=sha256:829deef280900ae7a088a4986e0ec86c2c7fefd0494dc3636636fd5676142894

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=sha256:663ed82c8e2658917c756cec3fb7bc0d3942362278eb35bd1039bd99e2c42b90

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=sha256:61642ce1690471689c6dbceb95dafc848ce457b0830293d4d5514053ef5b2f1c

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.162766Z digest=sha256:d49f44b6c2fb9c719409ce42bbc52ab52151aee91ee42a499f1f84c552f714ef

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=sha256:4d50166cfbd0fa41d5e32f9162697ea1d9763ed25d55f8dc6a70f1568b98a508

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T00:31:56.255771Z digest=sha256:7f3561df907cc2b79a7b273103b3f22e3623d67b57239fdf79d06bc4e028bfcf

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.309943Z digest=sha256:f6b2eedbfda7cc1e6b0458327019765ed88078095232edd534635795181ebe9f

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=sha256:8121275913c8cd2e81af970cbf119c1d61503231d505d5b7de7ffedbaef9d9e9

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T00:31:56.444503Z digest=sha256:4fad7e42b6f0a852acf0edb6754dc42da1a1f78a767eef5f7a47fc49bef83587

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=sha256:4ce18eb11887dd054b17d8a48c1c22ad15a60befd9a06823e8450b22e102f50e

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:d4ed993d9d2e7211c9520522e973780146faf0e93aa265cbddb138783ca5d46c

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T00:31:56.681151Z digest=sha256:214f051498dc342c45001029d0ce6de893c36f60b19f151e474fdf673e374408

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=sha256:96db98396e47a7e0908847e92c422929c7905bd82b64aa118c173221d577899e

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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unresolved
no resolver link, observed 2026-08-07T00:31:56.873071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:56.873071Z digest=sha256:5dfa51def7fd73a27b5dba4ae3b59f7e7f9540567190c21b940784d449689619

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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unresolved
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=sha256:86277fd0c2034f32efd94589a678249d5e9f15876c3b979b6f2e465d531cd783

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=sha256:8ddd52fa983b51322567d05a6888e12c05ffdaf904f461ac17d64cfe79480e8e

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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unresolved
no resolver link, observed 2026-08-07T00:31:57.090248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:31:57.090248Z digest=sha256:648c38df4139a2ae11f1afae0f92c666af793c83025e6f82f4f85fbbd1ca7303

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

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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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T23:13:20.622187Z digest=sha256:8bd2bfc80a3bbe44ff954b7b14b7452faec6714afea634f92074cafb53fc1d31