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Paper Citation Record · LEDGER

Is There a Case for Conversation Optimized Tokenizers in Large Language Models?

As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2506.18674.

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

pith.paper-citation-record.v1
2506.18674 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:19:15.885007Z

measured 14 of 14 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 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

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 725f6711-9b46-4f34-b203-63df23ab2765 · outbound

This paper cites https://allenai.org/.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? https://allenai.org/

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:19:17.302133Z

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=2026-08-06T23:19:14.640456Z digest=sha256:1ad742450710939a6dba73afdc194b320e7924af70f5a906df29d737902b6c45

Observation 95586cea-cfea-4675-9341-53c8a8900702 · outbound

This paper cites Accessed: 2024-06-08.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? Accessed: 2024-06-08

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:19:17.076164Z

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=2026-08-06T23:19:14.785714Z digest=sha256:01c96805a1afba8624938e6c501bfcfeb85fd5ddea8497642b962fe7fb4af369

Observation ed8f7381-cfaf-4990-9304-42eb9b4ac645 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T23:19:14.869810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:14.869810Z digest=sha256:ed1635db6ce9f80ba0068bb9f6f03acc786d8e68483692373add75127319a9e8

Observation 0f8b2201-94f5-481a-b4fd-b4565cd64973 · outbound

This paper cites https://huggingface.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? https://huggingface

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:19:16.429621Z

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=2026-08-06T23:19:15.296021Z digest=sha256:454ca70ea8adf3fd8b3683dd766f2ff52a3594786239331c39ea66eb88181da1

Observation 4bd3b149-c04f-4bea-a3c6-e77e24d1dd7c · outbound

This paper cites How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T23:19:15.359114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:15.359114Z digest=sha256:e9ae633eb8561d7a1a9df10988024f1adbe49773bf020c548ffb9ba37924fdbb

Observation 0e2288a8-c6bb-474d-80dc-8905e470c649 · outbound

This paper cites Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T23:19:15.550305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:15.550305Z digest=sha256:542dc6b945b69377bc2e5f3288af339b9f3d1b72112d1460ae87da2c8a7c162b

Observation b6552b5f-5d64-46e9-9c13-6d3acd288c70 · outbound

This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T23:19:15.802586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:15.802586Z digest=sha256:02b4ffeb4490bf5c5d4ee64416f2ba0633e5c9155511d5a18d6411795b18a0f9

Observation da335835-1b20-4270-b1cf-b13241b3ddce · outbound

This paper cites LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T23:19:15.885007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:15.885007Z digest=sha256:cdc6c10afd4b3fbc60c483bb83af7de81cbc9b4050e21c83170baa9499ee432d

Observation 4341cc1e-cde5-4471-a04b-606ce150088b · outbound

This paper cites Neural Machine Translation with Byte-Level Subwords.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? Neural Machine Translation with Byte-Level Subwords

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-06T23:19:15.667006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:15.667006Z digest=sha256:a8bac53576a09e9f393b694649251c341f531df37f6ca69bce8a3d2a7130a369

Observation 04343bb5-875a-4885-925b-9b6921216121 · outbound

This paper cites https://pile.eleuther.ai/.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? https://pile.eleuther.ai/

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:19:16.814416Z

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=2026-08-06T23:19:14.959868Z digest=sha256:7c580ff2954091e7b4ea55bac36612326e05e4c6a3061a55afc21f76d1e4b81f

Observation c4f9ba5f-e3f0-4321-a224-fd5e3daa375c · outbound

This paper cites Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-06T23:19:15.192201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:15.192201Z digest=sha256:05df39d7500461aef6c6ca024d9200cf7cdc093b2e8c5e35213a08e4c332e42c

Observation be4c696a-12d2-40ed-935d-ebe6b5a460a2 · outbound

This paper cites In 2023 IEEE High Performance Extreme Computing Conference (HPEC), pages 1–9.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? In 2023 IEEE High Performance Extreme Computing Conference (HPEC), pages 1–9

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:19:16.191426Z

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=2026-08-06T23:19:15.459801Z digest=sha256:8535e1b60d1008f8b126c6aa420f2247ee8d60cf70f4ac852658f47081caf03a

Observation 72344704-6d8c-46f2-b5e6-1b11d0c1550e · outbound

This paper cites Associa- tion for Computational Linguistics.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? Associa- tion for Computational Linguistics

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:19:17.538945Z

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=2026-08-06T23:19:14.564604Z digest=sha256:8570faf95fa25e263d7a205cd97dcdc17c28fe515d698df7fa5f638ea4302581

Observation d8ac7d09-d05a-4675-9bc9-932cf9f107f6 · outbound

This paper cites https://www.demandsage.com/chatbot-statistics/.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? https://www.demandsage.com/chatbot-statistics/

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:19:16.614492Z

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=2026-08-06T23:19:15.082079Z digest=sha256:735c4587bc9d06b264a5ed7fab0e2899dbac10c921f740e1d203526847ae5ad5

Pith citing papers

No inbound Pith citation observations are available.