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Paper Citation Record · LEDGER

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model

As of 9 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 2 inbound Pith citation observations for arXiv:2502.05701.

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

pith.paper-citation-record.v1
2502.05701 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:22:10.338542Z

measured 22 of 22 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T15:18:09.444513Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:16:24.885436Z

Reference resolution

20 of 20 outbound references displayed

  • verified exact1
  • verified fuzzy12
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation de75fb93-9e92-4b88-97c0-c1ff2b8fc5a0 · outbound

This paper cites Deep Learning for Natural Language Processing: A Survey,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Deep Learning for Natural Language Processing: A Survey,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.728717Z

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=pdf_text observed=2026-08-08T18:22:10.224664Z digest=sha256:14d02b86cb5665e7a00da99a2f8ffd7a6482ea5efca019c25bae07ad9519b22d

Observation eb6b5ddc-e8f7-480f-8f86-984ab7aaa0f8 · outbound

This paper cites MM- LLMs: Recent Advances in MultiModal Large Language Models,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model MM- LLMs: Recent Advances in MultiModal Large Language Models,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.711861Z

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=pdf_text observed=2026-08-08T18:22:10.232262Z digest=sha256:53b2a80d2cb72eabd0191582d2b792e63c04c9b528f852336057d5172e3e55c3

Observation 08e50ad5-4808-4a8c-8b16-f3d5365b226e · outbound

This paper cites A Review of Multi-Modal Large Language and Vision Models.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model A Review of Multi-Modal Large Language and Vision Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-08T18:22:10.238771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:22:10.238771Z digest=sha256:18d69ca26fd8a50a50a4da32afa6abca7ac3527d09cdcba3b449bef888cfdf41

Observation 70a2bfdb-2443-45e6-9065-d52943fe7c2a · outbound

This paper cites Can Large Language Models be Anomaly Detectors for Time Series?,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Can Large Language Models be Anomaly Detectors for Time Series?,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.694982Z

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=pdf_text observed=2026-08-08T18:22:10.246131Z digest=sha256:ec6a4fc6db69390ffe274befd59f861133aa86447f1700970e1855475f7479af

Observation a6809297-d898-4bd5-b6a8-b9aed2b7fc27 · outbound

This paper cites LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.678503Z

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=pdf_text observed=2026-08-08T18:22:10.252221Z digest=sha256:c2fae3442c84beb8cd3cb22f9d2294a887bb6dcd7967daa684944df59e9109e7

Observation e06463e3-bab4-48f8-8249-d506ce431b24 · outbound

This paper cites Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-08T18:22:10.258245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:22:10.258245Z digest=sha256:67dee3999b3dc7fc887504779169280fd4c3ced20af2ee888e7bd1049b464ee1

Observation 74c11df8-794d-4af9-887b-1a71950ae628 · outbound

This paper cites PromptCast: A New Prompt-Based Learning Paradigm for Time Series Forecasting,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model PromptCast: A New Prompt-Based Learning Paradigm for Time Series Forecasting,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.661564Z

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=pdf_text observed=2026-08-08T18:22:10.265774Z digest=sha256:cffefc7c460cb78108eb38dc7573345f8707e61708605e265aa8de9f3e525d46

Observation 4f7b7e03-46ea-4c01-9077-d050195c5075 · outbound

This paper cites LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T18:22:10.271309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:22:10.271309Z digest=sha256:14149e193c328763d6cb8efd931ffe6274ef0edf98e2a67fcf0d61317bfabe10

Observation 8fc3e7cf-fdaf-48cb-8bdc-2362a821a5d3 · outbound

This paper cites TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-08T18:22:10.277176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:22:10.277176Z digest=sha256:8554fc0dd32a5b9316c634ff0638a719f3b600fcc2e83b76e23f4a9bb3fb53d4

Observation 0b9e417d-1384-48d9-9926-26d41a516636 · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-08T18:22:10.283183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:22:10.283183Z digest=sha256:fb50b00edfce2f11aa312e6121e44964574ffd93221ec28745d4419811ce90fd

Observation e53567d5-12d7-4cdf-a85c-39c232fd7db2 · outbound

This paper cites UnitNorm: Rethinking Normalization for Transformers in Time Series.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model UnitNorm: Rethinking Normalization for Transformers in Time Series

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-08T18:22:10.423326Z

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=pdf_text observed=2026-08-08T18:22:10.289229Z digest=sha256:d861433762abe00bc0fd6435555c44456b844baacd75204e51fa25beceb64e0b

Observation 4fb26f59-9a53-49a1-b9d4-e4f0c00c8164 · outbound

This paper cites A filter-augmented auto-encoder with learnable normalization for robust multivariate time series anomaly detection,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model A filter-augmented auto-encoder with learnable normalization for robust multivariate time series anomaly detection,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.644782Z

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=pdf_text observed=2026-08-08T18:22:10.295241Z digest=sha256:85cc571d029d41135a1cbb5b590135d14b9bb111b37f4579f1692571fedd0f62

Observation 98808161-3e69-4dd9-bfd0-93678276dd95 · outbound

This paper cites Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural Networks,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural Networks,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.626399Z

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=pdf_text observed=2026-08-08T18:22:10.300348Z digest=sha256:7a655ad273585bd41ff48438567bb1a9a610aafaa250e3b5acbf3d28e5783c50

Observation 7ba5b6f3-3974-4e54-b5f7-0a5ea9a1c1b9 · outbound

This paper cites A Large Comparison of Normalization Methods on Time Series,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model A Large Comparison of Normalization Methods on Time Series,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.606452Z

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=pdf_text observed=2026-08-08T18:22:10.305623Z digest=sha256:e6ab2155d329eaf310233cfff84d9aad936d2d4a3fbfe983d9f557305f000c5f

Observation ff64d697-e009-4290-b796-ec8bad04655c · outbound

This paper cites Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T18:22:10.311028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:22:10.311028Z digest=sha256:183d11a313aab4bb0932499fd98818f0886691aeaff18f1aaf5a8ff4d64c413d

Observation 77b47668-f2ab-431c-adb9-c2c1f196ed8c · outbound

This paper cites One Fits All: Power General Time Series Analysis by Pretrained LM,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model One Fits All: Power General Time Series Analysis by Pretrained LM,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.588698Z

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=pdf_text observed=2026-08-08T18:22:10.316568Z digest=sha256:6abb3ed3d738d540ac4768c3cd37aa5f7a684af04a4a224905bbaeb97a63d181

Observation 990f1664-85e4-4c4d-9665-7d3501ef68ef · outbound

This paper cites Large Language Models as General Pattern Machines,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Large Language Models as General Pattern Machines,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.569750Z

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=pdf_text observed=2026-08-08T18:22:10.321969Z digest=sha256:84bd6fb2577abfdfd99e51c24b30e748997e8b0e37349ddd94bbec57e4f7e83b

Observation fc9469d1-a01c-4ab6-9372-973eb8a74e09 · outbound

This paper cites Frozen Language Model Helps ECG Zero-Shot Learning,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Frozen Language Model Helps ECG Zero-Shot Learning,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.550927Z

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=pdf_text observed=2026-08-08T18:22:10.327352Z digest=sha256:e68b0037acbe48443a1686686306a717a277605c8bc4bb43be3dda2511b6566c

Observation b5719966-3aa6-43e9-b187-84c3ebda61c5 · outbound

This paper cites TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T18:22:10.332919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:22:10.332919Z digest=sha256:df887390064ab8fddf57701ddb054d9f0151acd5c2576b722d9e3e41ff7a28da

Observation e175592e-fa35-424b-b6a9-90724ffc5e2b · outbound

This paper cites Context information can be more important than reasoning for time series forecasting with a large language model,.

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model Context information can be more important than reasoning for time series forecasting with a large language model,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:22:10.532940Z

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=pdf_text observed=2026-08-08T18:22:10.338542Z digest=sha256:fc45ccdf961b97642e3e7cadf5a64fb2cf0d7b6c339d20b2ee010c4ebf4d78dc

Pith citing papers

Observation 8a7f61b8-8e57-473b-9a58-cd4ebfcbf944 · inbound

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures cites this paper.

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-07-02T01:16:24.887449Z

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=pdf_text observed=2026-06-28T12:15:29.291378Z digest=sha256:c6d9f88df975df97f1018f1517450c674a144987245b6826a01d19409183e75e

Observation 3c736fcc-04b5-434f-a20e-1ff65676209d · inbound

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures cites this paper.

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model

Reference 38

Resolution
unresolved
no resolver link, observed 2026-07-12T15:18:09.444513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T15:18:09.444513Z digest=sha256:15e56e6b2fa815f7aa9e11f0c6ef09da65702448755a61acf82e3acb7c54d521