Paper Citation Record · LEDGER

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents

As of 16 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 6 inbound Pith citation observations for arXiv:2505.13291.

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

pith.paper-citation-record.v1
2505.13291 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:19:00.060451Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:49:26.556497Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

39 of 39 outbound references displayed

verified exact0
verified fuzzy15
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 2ea33136-a37e-4b42-901c-e7988cb349c5 · outbound

This paper cites SUPER: Evaluating agents on setting up and executing tasks from research repositories.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents SUPER: Evaluating agents on setting up and executing tasks from research repositories

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.483284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4603ccb4-9e91-4701-8246-15b282072923 · outbound

This paper cites TimeSeriesExam: A time series understanding exam.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents TimeSeriesExam: A time series understanding exam

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.472619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0f1d8f87-d393-4504-8214-2171215022bf · outbound

This paper cites MLE-bench: Evaluating machine learning agents on machine learning engineering.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents MLE-bench: Evaluating machine learning agents on machine learning engineering

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.892321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2551a59d-074f-4fa0-a940-d3b1b0746636 · outbound

This paper cites Item response theory for psychologists.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Item response theory for psychologists

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.455975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 74b0d594-04a3-44c9-a550-632f7fecef07 · outbound

This paper cites Aqua: A benchmarking tool for label quality assessment.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Aqua: A benchmarking tool for label quality assessment

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.444556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation eee9b12d-0399-43c0-a564-dfac00d89c65 · outbound

This paper cites MOMENT: A family of open time-series foundation models.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents MOMENT: A family of open time-series foundation models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.432880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation baf4cd05-914e-42da-b655-54ad818a79fa · outbound

This paper cites Automated evaluation of retrieval-augmented language models with task-specific exam generation.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Automated evaluation of retrieval-augmented language models with task-specific exam generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.909255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7edd78a-4889-4e5f-9a8f-a61a701885af · outbound

This paper cites Map it anywhere: Em- powering bev map prediction using large-scale public datasets.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Map it anywhere: Em- powering bev map prediction using large-scale public datasets

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.412201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9e2be6ea-c999-4fd3-8d3e-73d494fd487e · outbound

This paper cites MLAgentbench: Evaluating language agents on machine learning experimentation.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents MLAgentbench: Evaluating language agents on machine learning experimentation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.399911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0de5330c-fcde-499a-9c7c-a04e796a8402 · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.919766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6805f4ca-e3ab-47dd-8fed-15a7cae08f69 · outbound

This paper cites AIDE: AI-Driven Exploration in the Space of Code.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents AIDE: AI-Driven Exploration in the Space of Code

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.923904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9e5819d-35a1-4dfb-8df7-63fff78cc1e8 · outbound

This paper cites DSBench: How far are data science agents from becoming data science experts? In The Thirteenth International Conference on Learning Representations, 2025.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents DSBench: How far are data science agents from becoming data science experts? In The Thirteenth International Conference on Learning Representations, 2025

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.927902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b099e41-9d2c-41c1-abba-424777f6191b · outbound

This paper cites Holistic Evaluation of Language Models.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Holistic Evaluation of Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.931309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dd110d3-20f9-449e-abc6-3fd204066dbd · outbound

This paper cites G-eval: Nlg evaluation using gpt-4 with better human alignment.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents G-eval: Nlg evaluation using gpt-4 with better human alignment

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.381929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 05465f35-87ea-4539-88ee-f4780c762ea4 · outbound

This paper cites The kolmogorov-smirnov test for goodness of fit.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents The kolmogorov-smirnov test for goodness of fit

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.371348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 03241c31-c9d5-40ff-bd77-0c16fc90e1d5 · outbound

This paper cites GAIA: a benchmark for general ai assistants.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents GAIA: a benchmark for general ai assistants

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.359555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fade1209-042c-44bf-ae32-42151cc45c7f · outbound

This paper cites MLGym: A new framework and benchmark for advancing ai research agents, 2025.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents MLGym: A new framework and benchmark for advancing ai research agents, 2025

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.348525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7f02a243-9282-402d-a7ad-4fb36d30ad65 · outbound

This paper cites ML-Dev-Bench: Comparative Analysis of AI Agents on ML development workflows.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents ML-Dev-Bench: Comparative Analysis of AI Agents on ML development workflows

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.948386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b64c1703-19b1-4272-a90a-529bd47e4473 · outbound

This paper cites Meta kaggle, 2022.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Meta kaggle, 2022

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.337871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ebfff6ab-3eb5-467d-97f9-cefbfd68fe81 · outbound

This paper cites ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.955968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cc08aad-4bf9-4fbb-ba59-55f3d00d6a1b · outbound

This paper cites Openhands: An open platform for ai software developers as generalist agents.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Openhands: An open platform for ai software developers as generalist agents

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.960760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79ec15b4-8781-468b-8d3e-beeea998a9e1 · outbound

This paper cites RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.964481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2da82a0e-27e2-4d9d-9d73-ee1733c96bab · outbound

This paper cites TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T20:18:59.968530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation affb81bf-98c2-4afa-b852-e3cc5300c2f4 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.320077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fc8b3daa-860a-4ffa-9f00-37b2105021c5 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.310430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cdd0b947-2141-4618-ad1a-0022bec2f6ab · outbound

This paper cites We reduced the RAM allowance to 10 GiB (from 100 GiB) as we did not observe any memory-related issues during our tests.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents We reduced the RAM allowance to 10 GiB (from 100 GiB) as we did not observe any memory-related issues during our tests

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.298682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 71dd60f2-747e-4fda-8c24-00f9f61841f5 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.287524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6b067f90-be27-45bd-be5f-a7e27ab89d28 · outbound

This paper cites file=@${SUBMISSION_FILE}.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents file=@${SUBMISSION_FILE}

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.274655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 86454d14-50b0-4e57-ab32-d80b8bfc08a2 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.264405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8f20f3d0-f33e-4309-9404-63d093dbeb87 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.253077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation adfc6117-0448-4be0-bc8b-56407914ea1e · outbound

This paper cites w") as f: f.write(code) event_outq.put((.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents w") as f: f.write(code) event_outq.put((

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:19:00.242645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d1203a5f-8534-4917-9d24-dda3defafbdb · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.231710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 07fd6ac8-6821-4a9d-9067-056491a52640 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.220289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0da4dbc9-95cd-4635-a32d-fb213656d409 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.208913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ad253fbf-878e-492d-81b5-ea5d409a2e8a · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.197763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cdf6dfc7-54b8-4483-b095-e1d9e7549ae5 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.187150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4cff18ce-501e-4da7-9c1f-c9506117f5bd · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.176865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c8ad2f47-c0f2-4d1d-85df-133ae275e399 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.166111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 02df5ee5-b26e-44d6-b218-b29fc537e572 · outbound

This paper cites an unresolved cited work.

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:19:00.154520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation ea263905-0699-4356-beb2-4d25ed8ddebd · inbound

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models cites this paper.

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T16:49:26.556497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation feffffa7-2a42-4bac-9d78-5bf1e0b78556 · inbound

TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale cites this paper.

TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:36:04.498123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e683b470-0353-44ab-8478-8501010056f6 · inbound

AION: Next-Generation Tasks and Practical Harness for Time Series cites this paper.

AION: Next-Generation Tasks and Practical Harness for Time Series TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T11:54:38.614553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6aad474d-5e5c-404c-84a5-cce3e9d26bad · inbound

Business Utility of Large Language Models as Exploratory Data Analysis Agents cites this paper.

Business Utility of Large Language Models as Exploratory Data Analysis Agents TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T23:35:06.916216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 29cec238-4a26-4be5-afbc-b14478c80094 · inbound

OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents cites this paper.

OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-04T15:39:57.076434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 04118d40-c7c1-4cde-825b-e557454a790b · inbound

Predicting Pseudo-nitzschia harmful algal blooms along the Portuguese Coast using satellite-derived predictors cites this paper.

Predicting Pseudo-nitzschia harmful algal blooms along the Portuguese Coast using satellite-derived predictors TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents

Reference 137

Resolution: verified exact; local_arxiv, observed 2026-07-10T17:07:25.685453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.