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Paper Citation Record · LEDGER

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams

As of 8 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2508.21273.

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

pith.paper-citation-record.v1
2508.21273 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:28:03.160877Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

21 of 21 outbound references displayed

  • verified exact3
  • verified fuzzy2
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6943f155-dcc8-4d50-afe3-36a39ca398aa · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams A decoder-only foundation model for time-series forecasting

Reference 2

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no resolver link, observed 2026-08-05T14:28:01.651753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:01.651753Z digest=sha256:f0bea3145e1b8b6c0670dcc03ecf06af6a6be60b0a064bc80940cda2f2bf01e6

Observation 949d69ba-61ea-4af9-8db1-f3d7ca6ffd6e · outbound

This paper cites MOMENT: A Family of Open Time-series Foundation Models.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams MOMENT: A Family of Open Time-series Foundation Models

Reference 6

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no resolver link, observed 2026-08-05T14:28:01.983695Z

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source=pdf_text observed=2026-08-05T14:28:01.983695Z digest=sha256:68b321feb36ead10754d35f470b40befaff05f5bd5896b1fb4905386b1a27e3f

Observation 05f6bf64-0518-4f82-ac5a-4d4fb2be6e0c · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams LoRA: Low-Rank Adaptation of Large Language Models

Reference 8

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no resolver link, observed 2026-08-05T14:28:02.135249Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:02.135249Z digest=sha256:687d02b49b08d60343d1076a19b6be5337914bfeb15d504e1f1c8f6558f0b779

Observation 0fb4974c-9414-4ed8-afe5-9c1249ac10e2 · outbound

This paper cites Generic and scalable framework for automated time-series anomaly detection.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Generic and scalable framework for automated time-series anomaly detection

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-05T14:28:04.999848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:28:02.168206Z digest=sha256:707481f7f7caa0f5fc64433c7895adbc369c5c7fbb9ebe218be8ed4eeb2abf60

Observation 062880b6-1975-4c44-b77e-5ad2f413b9c3 · outbound

This paper cites Foundation Models for Time Series Analysis: A Tutorial and Survey.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Foundation Models for Time Series Analysis: A Tutorial and Survey

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:02.294447Z digest=sha256:896b10ccd84038b884c7d47519b024996f8b530aa4b1564e0fc08c267f196a75

Observation dbf9434e-8f09-4457-b6f1-1e5befeae4f6 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 13

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no resolver link, observed 2026-08-05T14:28:02.468019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:02.468019Z digest=sha256:990297f05550fa30b643016b19f9c5992356dcc6a3911e131d969fc6424fe0a2

Observation 2c5c5b43-e23c-4579-9405-2e16353d7e23 · outbound

This paper cites TimeGPT-1.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams TimeGPT-1

Reference 14

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no resolver link, observed 2026-08-05T14:28:02.542035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:02.542035Z digest=sha256:30c0795a69e853a6ae10fbdefe2fbe147d9187a1548f60c452794ebd68ec405d

Observation 8c44c257-25e7-4131-b428-226dfb3c8384 · outbound

This paper cites Deep Learning for Time Series Anomaly Detection: A Survey.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Deep Learning for Time Series Anomaly Detection: A Survey

Reference 15

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metadata mismatch
local_arxiv, observed 2026-08-05T14:28:03.854747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:28:02.607234Z digest=sha256:f427ae7e9aed252afa369b4ea270769eed7955ac7ddef9dd8fd033456132cf41

Observation 4ad92c6e-92e3-47aa-820b-27de669c2013 · outbound

This paper cites Large Language Models for Data Annotation and Synthesis: A Survey.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Large Language Models for Data Annotation and Synthesis: A Survey

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:02.656217Z digest=sha256:e65abb3a932f6bff3d63d67bd677f44864d7bd83eb588ed5a28f00dbba35dbb3

Observation 94f5680b-9aa9-4615-9a5e-4e906ffacaab · outbound

This paper cites MCTS-Judge: Test-Time Scaling in LLM-as-a-Judge for Code Correctness Evaluation.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams MCTS-Judge: Test-Time Scaling in LLM-as-a-Judge for Code Correctness Evaluation

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:02.738112Z digest=sha256:ac2a8ab951d153a677631cd206d6d28f8a68678ffd88e931b97cd04aa20dac66

Observation 26476ef5-3def-4c39-9060-c0481c755eea · outbound

This paper cites Trip-llm: A tri-branch patch- wise large language model framework for time-series anomaly detection.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Trip-llm: A tri-branch patch- wise large language model framework for time-series anomaly detection

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:02.904941Z digest=sha256:9bb403c542b9d61ff611dd224f50e5f4bc15146d65f0b77d4e5d822e2df074ff

Observation 92f047f4-1310-4320-b3d5-024e0c62c565 · outbound

This paper cites Han Zhao, Yuxiang Wang, Juanyong Duan, Chen-Kuo Huang, Dongjie Cao, Yanjie Wang, and Leman Akoglu.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Han Zhao, Yuxiang Wang, Juanyong Duan, Chen-Kuo Huang, Dongjie Cao, Yanjie Wang, and Leman Akoglu

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-05T14:28:04.823734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:28:02.997053Z digest=sha256:31a45519c2e212024b09415221e0551d1c09b50df506d418199ddd6a69b4b6ba

Observation 9cc10a9c-b64b-4c97-8055-ceb281b8f803 · outbound

This paper cites Study of instabilities and outbursts in luminous blue variables AF And $\&$ R 127.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Study of instabilities and outbursts in luminous blue variables AF And $\&$ R 127

Reference 1980

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metadata mismatch
local_arxiv, observed 2026-08-05T14:28:04.268531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:28:02.081626Z digest=sha256:cdad73b81302c0afd7ac7a93f99e5831215cfba772da0880217099a541080714

Observation f2d72e16-2796-4714-96c5-85046a50f400 · outbound

This paper cites an unresolved cited work.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Unresolved cited work

Reference 1995

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unresolved
no resolver link, observed 2026-08-05T14:28:01.802061Z

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source=pdf_text observed=2026-08-05T14:28:01.802061Z digest=sha256:865ff946f6931a3bb5a54744a72de60fc5e8f6a771c6f66d131a8da0fc65a625

Observation def5e55a-038f-4829-91b5-53d6193121d7 · outbound

This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 2015

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no resolver link, observed 2026-08-05T14:28:02.212342Z

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source=pdf_text observed=2026-08-05T14:28:02.212342Z digest=sha256:32184cf93ffb74d000b67e656feac9e324553c01ead14ace05e0021129c74289

Observation e7c1e5c8-efeb-4b69-b8e5-7ba9f92caaaf · outbound

This paper cites Can multimodal llms perform time series anomaly detection? arXiv preprint arXiv:2502.17812,.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Can multimodal llms perform time series anomaly detection? arXiv preprint arXiv:2502.17812,

Reference 2018

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:02.376359Z digest=sha256:cf9e99597e0e02f3a1722da826042832f6db6f1292f153d1652e730337afdf14

Observation 0bb18e5c-2c30-49c6-9692-5e03fd4e7d12 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 2020

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source=pdf_text observed=2026-08-05T14:28:03.160877Z digest=sha256:5b7da396f32bd0275a5c2b2ef5348ca50c04b5da8909844cbc3698b229a5cca1

Observation a9940fff-949f-49e0-b54c-280a945fc266 · outbound

This paper cites Yuan-Cheng Yu, Chun-An Lin, Yen-Chieh Ouyang, and Wen-Chih Peng.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Yuan-Cheng Yu, Chun-An Lin, Yen-Chieh Ouyang, and Wen-Chih Peng

Reference 2021

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verified exact
doi, observed 2026-08-05T14:28:03.410144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:28:02.821216Z digest=sha256:d87cf525d3327baf5147b77d71d55df61928b7b624be1098758af57856d4d67b

Observation 718da173-8d94-4f58-a72c-26a46e90dbeb · outbound

This paper cites Financial Fine-tuning a Large Time Series Model.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Financial Fine-tuning a Large Time Series Model

Reference 2023

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verified exact
local_arxiv, observed 2026-08-05T14:28:04.460962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:28:01.847248Z digest=sha256:ccb3f233f05b1c18f2e3dd12da3e5b976ca362aba11e5ec156ef518e4824047b

Observation 6f4d4f04-82ff-4b5d-9b99-2188c1b1052b · outbound

This paper cites Low-Rank Adaptation of Time Series Foundational Models for Out-of-Domain Modality Forecasting.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Low-Rank Adaptation of Time Series Foundational Models for Out-of-Domain Modality Forecasting

Reference 2024

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verified exact
local_arxiv, observed 2026-08-05T14:28:04.644809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T14:28:01.737705Z digest=sha256:fb84dbc44f654fad88204f6969614f5a323323c13578ea8db83396ef39f33de2

Observation 850f5e68-a4b0-42d7-ba0e-f8e3dd2b085b · outbound

This paper cites Chronos: Learning the Language of Time Series.

CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Chronos: Learning the Language of Time Series

Reference 2025

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:01.616856Z digest=sha256:062e4d84fc08d66bad53bc5c8e70cb03c280bc2d388c22496ad04df3ba279dce

Pith citing papers

No inbound Pith citation observations are available.