Paper Citation Record · LEDGER

Harnessing Generalist Agents for Contextualized Time Series

As of 5 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2606.05404.

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

pith.paper-citation-record.v1
2606.05404 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T05:45:48.655352Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

30 of 30 outbound references displayed

verified exact7
verified fuzzy0
unresolved15
parse uncertain0
malformed identifier1
metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70b1930b-c34c-4810-84d5-aca8e9d70d67 · outbound

This paper cites A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems.

Harnessing Generalist Agents for Contextualized Time Series A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-02T08:46:49.087671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 79e7a665-2bbe-4466-a6c8-d86294aea8de · outbound

This paper cites The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology.

Harnessing Generalist Agents for Contextualized Time Series The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:46:49.117583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 245cf93e-abdc-4c82-9f56-1e27b9a21c09 · outbound

This paper cites Monash Time Series Forecasting Archive.

Harnessing Generalist Agents for Contextualized Time Series Monash Time Series Forecasting Archive

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T08:46:49.110736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d039e4c0-1a46-42a8-bc12-e724899b7c85 · outbound

This paper cites Memory in the Age of AI Agents.

Harnessing Generalist Agents for Contextualized Time Series Memory in the Age of AI Agents

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T08:46:49.112455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f368d4d6-4217-4199-8ea5-0b68ca553bb1 · outbound

This paper cites Rethinking memory mechanisms of foundation agents in the second half.

Harnessing Generalist Agents for Contextualized Time Series Rethinking memory mechanisms of foundation agents in the second half

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T08:46:49.115053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c100b35d-70ab-4814-b380-404daa2e7d6a · outbound

This paper cites TSAQA: Time Series Analysis Question And Answering Benchmark.

Harnessing Generalist Agents for Contextualized Time Series TSAQA: Time Series Analysis Question And Answering Benchmark

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T08:46:49.094581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fa7b5c90-abbc-4b7b-b476-735afd25957a · outbound

This paper cites AI for Auto-Research: Roadmap & User Guide.

Harnessing Generalist Agents for Contextualized Time Series AI for Auto-Research: Roadmap & User Guide

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T08:46:49.113088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5ba24063-614b-4f1f-8993-db01a43de80f · outbound

This paper cites InProceedings of the 30th ACM SIGKDD conference on knowledge discovery and data mining, pages 5351–5362.

Harnessing Generalist Agents for Contextualized Time Series InProceedings of the 30th ACM SIGKDD conference on knowledge discovery and data mining, pages 5351–5362

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:46:49.110259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9e47920c-560c-41d9-a8a9-3ed3e8c39885 · outbound

This paper cites Learnable Spatial-Temporal Positional Encoding for Link Prediction.

Harnessing Generalist Agents for Contextualized Time Series Learnable Spatial-Temporal Positional Encoding for Link Prediction

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:46:49.107529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f0a21c4b-e803-435c-85b7-d088f58db8e2 · outbound

This paper cites TimeART: Towards agentic time series reasoning via tool-augmentation.

Harnessing Generalist Agents for Contextualized Time Series TimeART: Towards agentic time series reasoning via tool-augmentation

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T08:46:49.099616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a2ff5a6b-21dc-4665-bddd-47856009417f · outbound

This paper cites TradingAgents: Multi-Agents LLM Financial Trading Framework.

Harnessing Generalist Agents for Contextualized Time Series TradingAgents: Multi-Agents LLM Financial Trading Framework

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:46:49.100535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1b9c9b6f-3dc8-4b81-bf61-54b869f79cf3 · outbound

This paper cites When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference.

Harnessing Generalist Agents for Contextualized Time Series When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T08:46:49.087019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d941330a-4f25-4b84-a263-b14a671bd07e · outbound

This paper cites Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow.

Harnessing Generalist Agents for Contextualized Time Series Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:46:49.103046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d489e22c-6841-48fa-ac94-f718be6974aa · outbound

This paper cites arXiv preprint arXiv:2504.01346 , year =.

Harnessing Generalist Agents for Contextualized Time Series arXiv preprint arXiv:2504.01346 , year =

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:46:49.104825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fa7e01f4-8eb4-439e-839c-8f313b07f9e1 · outbound

This paper cites struct” features describe the channel pool as a whole; “per-ch.

Harnessing Generalist Agents for Contextualized Time Series struct” features describe the channel pool as a whole; “per-ch

Reference 15

Resolution: malformed identifier; arxiv_id, observed 2026-07-02T08:46:49.120050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cd68ac15-36d1-4b4e-a710-99c8e03fb5cf · outbound

This paper cites Withk= 1on this task both stages converge on the same family (FULLCAUSALCONTEXTIMPLICITEQUATIONBIVARLINSVAR) seen during training.

Harnessing Generalist Agents for Contextualized Time Series Withk= 1on this task both stages converge on the same family (FULLCAUSALCONTEXTIMPLICITEQUATIONBIVARLINSVAR) seen during training

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0e39870-e0ba-42df-85c4-ae434ef5c181 · outbound

This paper cites an unresolved cited work.

Harnessing Generalist Agents for Contextualized Time Series Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96ff5fcc-2bf2-4424-8432-e41ee141bb56 · outbound

This paper cites an unresolved cited work.

Harnessing Generalist Agents for Contextualized Time Series Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c570d6a3-191d-4f4c-b969-edad76f8449b · outbound

This paper cites 1")→compute_acf(.

Harnessing Generalist Agents for Contextualized Time Series 1")→compute_acf(

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a8bc3df-c982-4090-b9c5-3a224c68c3e1 · outbound

This paper cites parents forX1 at lagk∈ {1,2,3}areX0, X1,.

Harnessing Generalist Agents for Contextualized Time Series parents forX1 at lagk∈ {1,2,3}areX0, X1,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 917406c6-9344-4995-89e3-ce335f8a9662 · outbound

This paper cites Then TIMECLAWretrievesk=3records.

Harnessing Generalist Agents for Contextualized Time Series Then TIMECLAWretrievesk=3records

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd71cb93-98c8-476b-8d99-cca852f312bb · outbound

This paper cites the mechanism mapping is upstream-to-downstream edges.

Harnessing Generalist Agents for Contextualized Time Series the mechanism mapping is upstream-to-downstream edges

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 143d9b5e-78d8-4518-8c49-8ba0538aa802 · outbound

This paper cites Execution Stage.

Harnessing Generalist Agents for Contextualized Time Series Execution Stage

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 605ec016-6cd0-43db-bf57-69591edccc6c · outbound

This paper cites It skips the exhaustive per- channel statistics, peak-finding, and periodicity-detection that the no-memory agent runs through.

Harnessing Generalist Agents for Contextualized Time Series It skips the exhaustive per- channel statistics, peak-finding, and periodicity-detection that the no-memory agent runs through

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c01bce0a-e252-4fa2-ad90-2bdd3b6f554b · outbound

This paper cites The rule then determines option D, in which the sink row R176 is densely populated with parents from the tributaries and the tributaries themselves are source rows.

Harnessing Generalist Agents for Contextualized Time Series The rule then determines option D, in which the sink row R176 is densely populated with parents from the tributaries and the tributaries themselves are source rows

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37057e61-f43b-46cb-9120-0995487017ff · outbound

This paper cites Counterfactual: Same Series, No Memory.Re-running the identical task atk=0removes only theREFERENCESblock.

Harnessing Generalist Agents for Contextualized Time Series Counterfactual: Same Series, No Memory.Re-running the identical task atk=0removes only theREFERENCESblock

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be276ca8-212d-4352-829c-2106e52bb734 · outbound

This paper cites Each successful trajectory is summarized into a compact routine description that records the input conventions, intermediate computations, and final decision rule.

Harnessing Generalist Agents for Contextualized Time Series Each successful trajectory is summarized into a compact routine description that records the input conventions, intermediate computations, and final decision rule

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1298b48b-b4c7-46a8-8490-7ddd30ad0e38 · outbound

This paper cites parametric.

Harnessing Generalist Agents for Contextualized Time Series parametric

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea70fd90-d406-4b62-9632-dcad9847c590 · outbound

This paper cites an unresolved cited work.

Harnessing Generalist Agents for Contextualized Time Series Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6141292c-0712-4c5d-a06f-b94e9c379c88 · outbound

This paper cites scenario says ‘heat wave for 2 hours’→ground truth has a 4×spike at the stated start→because air-conditioning load scales with cooling demand.

Harnessing Generalist Agents for Contextualized Time Series scenario says ‘heat wave for 2 hours’→ground truth has a 4×spike at the stated start→because air-conditioning load scales with cooling demand

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T05:45:48.655352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.