Paper Citation Record · LEDGER

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

As of 7 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 100 inbound Pith citation observations for arXiv:2410.07095.

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

pith.paper-citation-record.v1
2410.07095 v6

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-23T19:11:20.600633Z

measured 136 of 136 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 100 of 127 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:57:36.403917Z

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

36 of 36 outbound references displayed

verified exact15
verified fuzzy16
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

9
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 10058669-c66c-4d10-931e-d0de89239b7b · outbound

This paper cites Anthropic's Responsible Scaling Policy , Version 1.0, September 2023.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Anthropic's Responsible Scaling Policy , Version 1.0, September 2023

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.251461Z

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.

Observation b41e221d-f8cb-4ff6-9116-74d91283c89c · outbound

This paper cites Program Synthesis with Large Language Models.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Program Synthesis with Large Language Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-23T19:13:21.578703Z

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.

Observation 69eb685f-89f0-40b6-97f7-cdb6cb72e6bd · outbound

This paper cites Quantifying Memorization Across Neural Language Models.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Quantifying Memorization Across Neural Language Models

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-23T19:13:21.574142Z

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.

Observation 31abeee7-f11b-4692-9173-46311c65a0b1 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Evaluating Large Language Models Trained on Code

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-23T19:13:21.570148Z

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.

Observation a2285312-d1d7-4a8c-b93e-ec90e7c1b685 · outbound

This paper cites Cognition Introducing Devin , the first AI software engineer, March 2024.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Cognition Introducing Devin , the first AI software engineer, March 2024

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.247456Z

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.

Observation 063ad94b-622d-44f6-9392-3df1945fcdd7 · outbound

This paper cites Openvaccine: Covid-19 mrna vaccine degradation prediction.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Openvaccine: Covid-19 mrna vaccine degradation prediction

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.239077Z

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.

Observation bfc1c359-73ad-4401-95e5-ac006cf958c6 · outbound

This paper cites ConStat: Performance-Based Contamination Detection in Large Language Models.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering ConStat: Performance-Based Contamination Detection in Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:13:21.549550Z

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.

Observation 0a4c73d4-f7b1-4862-912d-044d64b9f07f · outbound

This paper cites GitHub Copilot Workspace : Welcome to the Copilot -native developer environment, April 2024.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering GitHub Copilot Workspace : Welcome to the Copilot -native developer environment, April 2024

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.234961Z

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.

Observation 91bcb36d-b566-4dc5-85bc-cba24f532b4f · outbound

This paper cites Code Droid Technical Report , June 2024.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Code Droid Technical Report , June 2024

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.231007Z

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.

Observation 1ad5e1cc-4025-4189-834a-920f3b668c5c · outbound

This paper cites AgentQuest: A Modular Benchmark Framework to Measure Progress and Improve LLM Agents.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering AgentQuest: A Modular Benchmark Framework to Measure Progress and Improve LLM Agents

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:13:21.517261Z

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.

Observation b17d8e9a-d934-49d7-88d9-6219f8ef0a17 · outbound

This paper cites Frontier Safety Framework , May 2024.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Frontier Safety Framework , May 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.226806Z

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.

Observation 43b31cb2-ca58-4eef-8763-1347390b8110 · outbound

This paper cites Measuring Coding Challenge Competence With APPS.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Measuring Coding Challenge Competence With APPS

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-23T19:13:21.521250Z

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.

Observation 4a595fff-28c7-4351-a9f6-de5ac44b11e9 · outbound

This paper cites AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation

Reference 13

Resolution: metadata mismatch; local_arxiv, observed 2026-05-23T19:13:21.526637Z

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.

Observation b0ced4d7-6faf-4949-b66b-16f20112a0c3 · outbound

This paper cites MLAgentBench : Evaluating Language Agents on Machine Learning Experimentation.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering MLAgentBench : Evaluating Language Agents on Machine Learning Experimentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.219044Z

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.

Observation 8db45d11-7b65-4b61-804c-b0b81bf12438 · outbound

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

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-23T19:13:21.544518Z

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.

Observation 8af70357-a0e3-45bc-929d-a3a2381a43b2 · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-05-23T19:13:21.566443Z

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.

Observation 556b8617-b887-420c-9d9f-a9e5dc970094 · outbound

This paper cites DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:13:21.510007Z

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.

Observation 4fc3763e-a96e-4bdf-9174-369cbc7c776e · outbound

This paper cites Kaggle Progression System Kaggle.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Kaggle Progression System Kaggle

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.215181Z

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.

Observation e80d8849-0494-4cf5-97a1-9a33bc0c445a · outbound

This paper cites Research: quantifying GitHub Copilot ’s impact on developer productivity and happiness, September 2022.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Research: quantifying GitHub Copilot ’s impact on developer productivity and happiness, September 2022

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.211519Z

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.

Observation 0d7dd57a-ebc5-419b-a74b-fff200b39d49 · outbound

This paper cites AI Agents That Matter.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering AI Agents That Matter

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:13:21.505537Z

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.

Observation a88b45dc-14c6-4881-8967-babcd2da0a5d · outbound

This paper cites Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando De Freitas, Koray Kavukcuoglu, and Oriol Vinyals.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando De Freitas, Koray Kavukcuoglu, and Oriol Vinyals

Reference 21

Resolution: verified exact; doi, observed 2026-05-23T19:13:20.478391Z

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.

Observation 129dc745-ebc3-4563-ac56-0c49e86d4d97 · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering AgentBench: Evaluating LLMs as Agents

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-23T19:13:21.557714Z

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.

Observation d67ec729-61b6-428c-999c-2ea8b6b34c40 · outbound

This paper cites Vesuvius challenge - ink detection.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Vesuvius challenge - ink detection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.207090Z

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.

Observation 740a3b7a-a86a-4816-8326-2bc938fef9e8 · outbound

This paper cites Discovering and exploring cases of educational source code plagiarism with Dolos.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Discovering and exploring cases of educational source code plagiarism with Dolos

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.203336Z

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.

Observation 08f8be6f-122d-49e2-832e-4b75c9d471ac · outbound

This paper cites GAIA: a benchmark for General AI Assistants.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering GAIA: a benchmark for General AI Assistants

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-05-23T19:13:21.553404Z

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.

Observation eabc68ac-2f55-445e-9fca-cbee9fb43411 · outbound

This paper cites Preparedness Framework , December 2023.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Preparedness Framework , December 2023

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.198351Z

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.

Observation fb6f2bfa-73e9-4738-933f-8410d816ac27 · outbound

This paper cites Introducing Weco AIDE , April 2024.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Introducing Weco AIDE , April 2024

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.194782Z

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.

Observation 230b2e79-42ba-4507-bf2f-bb3b8e302bd2 · outbound

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

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:13:21.535616Z

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.

Observation f2d1aebf-c91e-43e6-bca1-a6111eda7e80 · outbound

This paper cites OpenHands: An Open Platform for AI Software Developers as Generalist Agents.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering OpenHands: An Open Platform for AI Software Developers as Generalist Agents

Reference 29

Resolution: metadata mismatch; local_arxiv, observed 2026-05-23T19:13:21.562094Z

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.

Observation ef46fc68-42e6-4160-adc9-00f48e3a7f2e · outbound

This paper cites The shift from models to compound ai systems.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering The shift from models to compound ai systems

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.191266Z

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.

Observation 52ade589-ecb0-4e0a-8f4b-9fb84951d706 · outbound

This paper cites AutoCodeRover: Autonomous Program Improvement.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering AutoCodeRover: Autonomous Program Improvement

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:13:21.530857Z

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.

Observation a36e9827-74bb-41e2-9818-050d571d840b · outbound

This paper cites Can GPT-4 Perform Neural Architecture Search?.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Can GPT-4 Perform Neural Architecture Search?

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:13:21.540246Z

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.

Observation 6f895805-6347-4eac-800d-13ca628d0fbd · outbound

This paper cites write newline.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering write newline

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.187338Z

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.

Observation f847085e-e9ab-47cc-9d4b-77a13c06e902 · outbound

This paper cites @esa (Ref.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering @esa (Ref

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:03:26.243426Z

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.

Observation 3db40eef-97a1-40e9-bc8f-41c2a5fa4593 · outbound

This paper cites an unresolved cited work.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-05-23T20:03:26.183215Z

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.

Observation ccc572ff-0c54-41e8-8e34-f6e8b3856200 · outbound

This paper cites an unresolved cited work.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-05-23T20:03:26.178485Z

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.

Pith citing papers

Observation 0949488f-6b45-47ab-99f4-ccf2509dce71 · inbound

Frontier Models are Capable of In-context Scheming cites this paper.

Frontier Models are Capable of In-context Scheming MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-16T14:22:01.708833Z

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.

Observation 2c8a8636-7558-4f7c-b51b-62ff7e988de6 · inbound

Humanity's Last Exam cites this paper.

Humanity's Last Exam MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-10T18:40:50.382147Z

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.

Observation baf3ef74-fbc2-4445-8a92-07d2c91f88e8 · inbound

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models cites this paper.

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:40:41.266922Z

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.

Observation f883961b-a295-4de7-95c4-00bcd68091d6 · inbound

Large Language Model Agent: A Survey on Methodology, Applications and Challenges cites this paper.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 144

Resolution: verified exact; local_arxiv, observed 2026-05-22T21:52:10.592130Z

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.

Observation 46a8763d-d797-452b-adba-009b1d51cbe2 · inbound

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review cites this paper.

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 127

Resolution: verified exact; local_arxiv, observed 2026-05-15T02:57:38.488809Z

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.

Observation 800e8d9e-d336-4dbf-b08d-e2ba52b7c0aa · inbound

From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization cites this paper.

From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:57:36.403917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94911a56-4025-4428-a8db-5db3c2374852 · inbound

Large Language Models for Planning: A Comprehensive and Systematic Survey cites this paper.

Large Language Models for Planning: A Comprehensive and Systematic Survey MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:51.566184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db9ab53c-6279-496e-9327-d61a9c33d19d · inbound

RepoMaster: Autonomous Exploration and Understanding of GitHub Repositories for Complex Task Solving cites this paper.

RepoMaster: Autonomous Exploration and Understanding of GitHub Repositories for Complex Task Solving MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:16.130724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cd5b506-3428-41fe-843e-60bc3e7b709a · inbound

Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks cites this paper.

Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T12:18:50.576064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 089f937e-d284-4d45-9032-4f160e40483b · inbound

AI Scientists Fail Without Strong Implementation Capability cites this paper.

AI Scientists Fail Without Strong Implementation Capability MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T11:49:01.526190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ed01d53-5a9b-436b-82be-455d36c104a1 · inbound

VS-Bench: Evaluating VLMs for Strategic Abilities in Multi-Agent Environments cites this paper.

VS-Bench: Evaluating VLMs for Strategic Abilities in Multi-Agent Environments MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-19T11:57:16.254409Z

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.

Observation 7765159c-2546-4784-b802-f379cc58522b · inbound

TextAtari: 100K Frames Game Playing with Language Agents cites this paper.

TextAtari: 100K Frames Game Playing with Language Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T10:51:57.932392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00a96ab0-57aa-4f08-a269-a73cf4789e00 · inbound

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data cites this paper.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T10:22:59.340621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b37b2185-8b21-4127-a86d-11fa9a8c23d5 · inbound

OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems cites this paper.

OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:23:50.616857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9aa265e-c0c0-4265-b9a9-2354de16d98e · inbound

Evolutionary Perspectives on the Evaluation of LLM-Based AI Agents: A Comprehensive Survey cites this paper.

Evolutionary Perspectives on the Evaluation of LLM-Based AI Agents: A Comprehensive Survey MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 172

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:19.820876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81445514-0b9c-4510-bfc1-5ad5d93c31d6 · inbound

DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents cites this paper.

DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-16T08:07:39.426511Z

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.

Observation 1333024c-de16-4666-82d9-44d41a199367 · inbound

Perspective on Utilizing Foundation Models for Laboratory Automation in Materials Research cites this paper.

Perspective on Utilizing Foundation Models for Laboratory Automation in Materials Research MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T00:55:16.898887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc444aa-7de8-44e9-b689-0b6714a020eb · inbound

RExBench: Can coding agents autonomously implement AI research extensions? cites this paper.

RExBench: Can coding agents autonomously implement AI research extensions? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-05-19T07:37:08.913299Z

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.

Observation dbeba95d-0dd7-46bf-9482-91eef5049960 · inbound

DABstep: Data Agent Benchmark for Multi-step Reasoning cites this paper.

DABstep: Data Agent Benchmark for Multi-step Reasoning MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T21:37:50.650169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fe5516d-1166-42c1-9628-e810171168ca · inbound

AI4Research: A Survey of Artificial Intelligence for Scientific Research cites this paper.

AI4Research: A Survey of Artificial Intelligence for Scientific Research MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:12.210151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3080b94-bee8-43c4-a758-4a0b10a01473 · inbound

Establishing Best Practices for Building Rigorous Agentic Benchmarks cites this paper.

Establishing Best Practices for Building Rigorous Agentic Benchmarks MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T20:24:21.069258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 150e9c98-f8c7-42fb-922b-8887deee6850 · inbound

AblationBench: Evaluating Automated Planning of Ablations in Empirical AI Research cites this paper.

AblationBench: Evaluating Automated Planning of Ablations in Empirical AI Research MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T19:00:08.554622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc15c45f-a2ad-4758-adad-4896e7be1a57 · inbound

Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity cites this paper.

Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T18:12:29.955772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e26fafb-125c-42f3-9fa6-98a8e1106f7f · inbound

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence cites this paper.

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 73

Resolution: metadata mismatch; local_arxiv, observed 2026-05-14T22:23:15.658139Z

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.

Observation 96bba6a7-7066-4c86-8529-f0aae9c18d72 · inbound

How Far Are AI Scientists from Changing the World? cites this paper.

How Far Are AI Scientists from Changing the World? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T10:55:14.616722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c8caff6-8dcb-45c4-9c85-80b1ad948731 · inbound

TextQuests: How Good are LLMs at Text-Based Video Games? cites this paper.

TextQuests: How Good are LLMs at Text-Based Video Games? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T10:32:33.646495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b912a33-b4a6-4a11-bbfa-cfa0ac414b7e · inbound

Preliminary suggestions for rigorous GPAI model evaluations cites this paper.

Preliminary suggestions for rigorous GPAI model evaluations MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T15:20:12.437386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46c82f76-f455-4970-8219-272ba1e8053b · inbound

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems cites this paper.

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:22:51.728367Z

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.

Observation e0f69ee3-1813-43c4-9ef2-efff9eb485ec · inbound

Reliable Weak-to-Strong Monitoring of LLM Agents cites this paper.

Reliable Weak-to-Strong Monitoring of LLM Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T15:53:47.697485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9966b5d1-224c-4fea-9a94-78f61bc54f1f · inbound

Reinforcement Learning for Machine Learning Engineering Agents cites this paper.

Reinforcement Learning for Machine Learning Engineering Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T12:24:02.235163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc36038c-3468-43e8-a1e8-9d5666dab71a · inbound

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining cites this paper.

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T18:11:42.733862Z

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.

Observation 66fb61dd-5ec4-455b-9983-47a6a7b6d04c · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-05-18T00:02:25.003117Z

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.

Observation 8efd4654-b1fb-4d81-bad9-179da1230ff3 · inbound

Towards Adaptive ML Benchmarks: Web-Agent-Driven Construction, Domain Expansion, and Metric Optimization cites this paper.

Towards Adaptive ML Benchmarks: Web-Agent-Driven Construction, Domain Expansion, and Metric Optimization MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T19:21:20.611481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c91b463-b855-4a13-a201-70374c10804e · inbound

What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations cites this paper.

What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T06:00:57.896540Z

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.

Observation cdcbd144-bca0-4e94-9a72-46a5a6bc8518 · inbound

BadScientist: Can a Research Agent Write Convincing but Unsound Papers that Fool LLM Reviewers? cites this paper.

BadScientist: Can a Research Agent Write Convincing but Unsound Papers that Fool LLM Reviewers? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T08:59:45.080256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2290bce9-fdff-431d-9d56-67285c1d0f87 · inbound

End-to-end PDDL Planning with Hardcoded and Dynamic Agents cites this paper.

End-to-end PDDL Planning with Hardcoded and Dynamic Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T23:38:41.675007Z

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.

Observation 45a15d5e-76cb-48b3-8d58-1c69d11df068 · inbound

Automated Modernization of Machine Learning Engineering Notebooks for Reproducibility cites this paper.

Automated Modernization of Machine Learning Engineering Notebooks for Reproducibility MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T03:43:05.501625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89386d3a-3e0e-46dc-aef9-00b813d0419a · inbound

AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine Learning Engineering cites this paper.

AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine Learning Engineering MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T06:32:27.285326Z

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.

Observation 73cfc36c-eea1-4951-b0be-8f9df34bd852 · inbound

iML: Executable, Problem-Grounded, and Broadly Exploratory Code-Driven AutoML cites this paper.

iML: Executable, Problem-Grounded, and Broadly Exploratory Code-Driven AutoML MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T23:25:33.220360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc560ce5-11dd-48aa-a399-67b7b6147fd9 · inbound

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search cites this paper.

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-15T17:50:12.253270Z

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.

Observation 4118b16a-0b55-44a3-a83a-f8d953c886b1 · inbound

AI Can Learn Scientific Taste cites this paper.

AI Can Learn Scientific Taste MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T18:14:52.244321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b09ef985-2053-4c07-b40f-c57aa800b28c · inbound

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments cites this paper.

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-05-15T01:23:27.135290Z

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.

Observation 2b64becb-1446-4d02-b3a9-1c144242b0f0 · inbound

TIR-Agent: Training an Explorative and Efficient Agent for Image Restoration cites this paper.

TIR-Agent: Training an Explorative and Efficient Agent for Image Restoration MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-13T16:50:50.552104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 548d6f2c-9474-40b7-b595-4bdfdf214bb8 · inbound

Multilingual Prompt Localization for Agent-as-a-Judge: Language and Backbone Sensitivity in Requirement-Level Evaluation cites this paper.

Multilingual Prompt Localization for Agent-as-a-Judge: Language and Backbone Sensitivity in Requirement-Level Evaluation MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:15:50.744720Z

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.

Observation 1485e507-b83d-48cb-9c8d-5c7be3e37f64 · inbound

FrontierFinance: A Long-Horizon Computer-Use Benchmark of Real-World Financial Tasks cites this paper.

FrontierFinance: A Long-Horizon Computer-Use Benchmark of Real-World Financial Tasks MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:30:49.944041Z

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.

Observation 5401f046-ac6e-40d6-9445-7369c63ebad1 · inbound

In-Place Test-Time Training cites this paper.

In-Place Test-Time Training MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:30:49.058898Z

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.

Observation 8c76dcaa-1c19-4cae-90fd-690547baf310 · inbound

Pioneer Agent: Continual Improvement of Small Language Models in Production cites this paper.

Pioneer Agent: Continual Improvement of Small Language Models in Production MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:05:57.568178Z

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.

Observation ea68e041-dfcd-410b-a9b8-b2602f0a0fb3 · inbound

SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences? cites this paper.

SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:36:03.503133Z

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.

Observation 78afe47a-b5d9-48f7-b914-0cc5619ce32b · inbound

Spatial Atlas: Compute-Grounded Reasoning for Spatial-Aware Research Agent Benchmarks cites this paper.

Spatial Atlas: Compute-Grounded Reasoning for Spatial-Aware Research Agent Benchmarks MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:31:01.230008Z

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.

Observation 64982a15-6358-4aa5-9359-19eef36708b0 · inbound

Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering Tasks with Generative Optimization cites this paper.

Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering Tasks with Generative Optimization MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T09:01:01.084341Z

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.

Observation 680be77e-6b91-4632-bc70-5246ade11647 · inbound

TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration cites this paper.

TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:46:34.784533Z

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.

Observation a624fea8-8603-4239-beba-02a5a84879da · inbound

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale cites this paper.

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:01:13.394419Z

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.

Observation b08bc7e2-ff39-416d-9d0a-85ab7a1f7825 · inbound

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale cites this paper.

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-05T17:51:14.765804Z

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.

Observation e2136a57-a6db-45e2-8324-eec869a62ade · inbound

Evaluation-driven Scaling for Scientific Discovery cites this paper.

Evaluation-driven Scaling for Scientific Discovery MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:26:07.565713Z

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.

Observation 80be0d3b-badd-4671-9d41-49cbf429c6c6 · inbound

On Benchmark Hacking in ML Contests: Modeling, Insights and Design cites this paper.

On Benchmark Hacking in ML Contests: Modeling, Insights and Design MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:21:12.738010Z

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.

Observation 7cc74e0f-2b06-412a-a1ad-f53a219a33d8 · inbound

Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning cites this paper.

Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:16:09.185864Z

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.

Observation fc6af751-d40f-4062-b432-34e55189aefd · inbound

AcademiClaw: When Students Set Challenges for AI Agents cites this paper.

AcademiClaw: When Students Set Challenges for AI Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-09T05:55:29.695068Z

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.

Observation 313fca62-7306-40cf-9175-65e1b277c37b · inbound

PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents cites this paper.

PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:00:56.387556Z

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.

Observation 8f610c96-c7e3-462e-9038-b3956a66b57a · inbound

TeamBench: Evaluating Agent Coordination under Enforced Role Separation cites this paper.

TeamBench: Evaluating Agent Coordination under Enforced Role Separation MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:00:55.525903Z

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.

Observation eb03d3b3-e7ad-4c7b-baa3-d79464aaf430 · inbound

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces cites this paper.

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 142

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:01:18.592393Z

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.

Observation 6e96672d-fb47-41b1-87d5-efd84d4ccf42 · inbound

DataMaster: Data-Centric Autonomous AI Research cites this paper.

DataMaster: Data-Centric Autonomous AI Research MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:36:24.801807Z

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.

Observation f1c856d2-85f2-4075-a859-4985e291ed36 · inbound

DataMaster: Data-Centric Autonomous AI Research cites this paper.

DataMaster: Data-Centric Autonomous AI Research MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-14T21:12:59.133651Z

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.

Observation cfd3bf6c-cbdc-4ae8-b32b-7bda4deff2cd · inbound

SkillSafetyBench: Evaluating Agent Safety under Skill-Facing Attack Surfaces cites this paper.

SkillSafetyBench: Evaluating Agent Safety under Skill-Facing Attack Surfaces MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:12:17.914966Z

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.

Observation f1f887bd-a17f-4a92-b2ef-065878966ef9 · inbound

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack cites this paper.

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-14T20:32:56.909283Z

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.

Observation 4ba5177d-4501-49f5-b6e8-2acd5155a599 · inbound

Europe and the Geopolitics of AGI: The Need for a Preparedness Plan cites this paper.

Europe and the Geopolitics of AGI: The Need for a Preparedness Plan MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-14T17:49:23.579524Z

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.

Observation df6e7b88-e280-4dcd-8151-e0557fa17296 · inbound

Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction cites this paper.

Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 19

Resolution: metadata mismatch; local_arxiv, observed 2026-05-15T06:05:06.706952Z

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.

Observation a239fdf7-7476-420a-abdd-f2561ed0e672 · inbound

FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale cites this paper.

FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-15T02:03:28.882759Z

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.

Observation 1516a089-4cdb-4397-a03d-9b2f3b7c0b19 · inbound

Graphs of Research: Citation Evolution Graphs as Supervision for Research Idea Generation cites this paper.

Graphs of Research: Citation Evolution Graphs as Supervision for Research Idea Generation MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-30T20:55:04.045232Z

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.

Observation 97b19e26-c772-4343-9579-bc8081f1aac1 · inbound

SMCEvolve: Principled Scientific Discovery via Sequential Monte Carlo Evolution cites this paper.

SMCEvolve: Principled Scientific Discovery via Sequential Monte Carlo Evolution MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-19T16:22:39.499555Z

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.

Observation a711806f-cefe-41e7-aff4-214ea632e467 · inbound

BioXArena: Benchmarking LLM Agents on Multi-Modal Biomedical Machine Learning Tasks cites this paper.

BioXArena: Benchmarking LLM Agents on Multi-Modal Biomedical Machine Learning Tasks MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-19T19:32:43.762882Z

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.

Observation 92bd12e4-4819-4baa-8d3b-88a8a9a2219f · inbound

MLReplicate: Benchmarking Autonomous Research Systems for Machine Learning Reproducibility cites this paper.

MLReplicate: Benchmarking Autonomous Research Systems for Machine Learning Reproducibility MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T20:03:44.137430Z

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.

Observation f29b7ab8-9d8a-4738-8d69-a85e6ac2b3f2 · inbound

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics cites this paper.

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:28:21.432887Z

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.

Observation 26dca1fb-2a0c-44d7-84b5-6d5f62d7a0c3 · inbound

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics cites this paper.

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-06-30T19:05:00.903660Z

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.

Observation 2d271753-d42e-4655-b891-26878c699197 · inbound

DiagEval: Trajectory-Conditioned Diagnosis for Reliable Software Evaluation with GUI Agents cites this paper.

DiagEval: Trajectory-Conditioned Diagnosis for Reliable Software Evaluation with GUI Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 33

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T23:12:51.589025Z

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.

Observation ae64da6d-0fa5-465b-bcb9-14f40f62d585 · inbound

DiagEval: Trajectory-Conditioned Diagnosis for Reliable Software Evaluation with GUI Agents cites this paper.

DiagEval: Trajectory-Conditioned Diagnosis for Reliable Software Evaluation with GUI Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 33

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T13:08:17.865759Z

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.

Observation 47cadefa-3de7-42a4-8968-5415fc8a6fe2 · inbound

WebGameBench: Requirement-to-Application Evaluation for Coding Agents via Browser-Native Games cites this paper.

WebGameBench: Requirement-to-Application Evaluation for Coding Agents via Browser-Native Games MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-20T12:28:17.264615Z

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.

Observation 00bc18d5-ec31-494c-8b6c-b2308cea62e8 · inbound

WebGameBench: Requirement-to-Application Evaluation for Coding Agents via Browser-Native Games cites this paper.

WebGameBench: Requirement-to-Application Evaluation for Coding Agents via Browser-Native Games MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:45:23.240288Z

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.

Observation f4293ff5-e60d-4736-9d3e-1c6fdbe8ad82 · inbound

DecisionBench: A Benchmark for Emergent Delegation in Long-Horizon Agentic Workflows cites this paper.

DecisionBench: A Benchmark for Emergent Delegation in Long-Horizon Agentic Workflows MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-20T10:18:11.752386Z

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.

Observation 5f4e81b0-4561-4a35-b96a-98a815f18d14 · inbound

How Far Are We From True Auto-Research? cites this paper.

How Far Are We From True Auto-Research? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T09:58:11.265272Z

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.

Observation 41b8d2f9-b593-42da-a0a8-1c5783be82f9 · inbound

What and When to Distill: Selective Hindsight Distillation for Multi-Turn Agents cites this paper.

What and When to Distill: Selective Hindsight Distillation for Multi-Turn Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-20T05:43:05.771032Z

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.

Observation 02af144c-51c0-4476-bf9c-11c9f6a69597 · inbound

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration cites this paper.

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-20T05:23:03.562193Z

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.

Observation 1d4d4ea8-3b43-47c9-9d54-b10f82bdb35e · inbound

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration cites this paper.

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-07-01T15:05:47.884299Z

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.

Observation e2ee0fa7-77a2-43b0-be19-d29bd853ec47 · inbound

What Do Evolutionary Coding Agents Evolve? cites this paper.

What Do Evolutionary Coding Agents Evolve? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-05-20T03:48:03.327687Z

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.

Observation bbab3210-536e-4bbe-ae63-fdb65a033849 · inbound

WildRoadBench: A Wild Aerial Road-Damage Grounding Benchmark for Vision-Language Models and Autonomous Agents cites this paper.

WildRoadBench: A Wild Aerial Road-Damage Grounding Benchmark for Vision-Language Models and Autonomous Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 6

Resolution: malformed identifier; local_arxiv, observed 2026-05-21T07:54:49.600155Z

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.

Observation 104b269d-9077-47f1-80db-b816e75ff523 · inbound

WildRoadBench: A Wild Aerial Road-Damage Grounding Benchmark for Vision-Language Models and Autonomous Agents cites this paper.

WildRoadBench: A Wild Aerial Road-Damage Grounding Benchmark for Vision-Language Models and Autonomous Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 6

Resolution: malformed identifier; local_arxiv, observed 2026-06-30T18:14:59.143256Z

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.

Observation 14b3caf7-8f5f-4193-9edf-63d6d36a4d44 · inbound

Declarative Data Services: Structured Agentic Discovery for Composing Data Systems cites this paper.

Declarative Data Services: Structured Agentic Discovery for Composing Data Systems MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-05-21T05:19:39.287742Z

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.

Observation 7c85de97-2215-434f-8825-ee600e61f827 · inbound

Declarative Data Services: Structured Agentic Discovery for Composing Data Systems cites this paper.

Declarative Data Services: Structured Agentic Discovery for Composing Data Systems MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-07-01T15:05:48.125602Z

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.

Observation 85350ddd-64b2-4a6c-b328-e22f820dc274 · inbound

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents cites this paper.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.483673Z

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.

Observation b4578c69-a663-4e2f-ae8e-ab40b82ddf6a · inbound

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

AION: Next-Generation Tasks and Practical Harness for Time Series MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T11:54:38.596441Z

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.

Observation 1fc5fd31-db11-4b37-89bb-27d93630b493 · inbound

ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence cites this paper.

ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-29T21:23:59.052296Z

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.

Observation 11e75caa-4fdc-43c9-8be3-57473bdf22ff · inbound

SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones? cites this paper.

SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-06-29T08:23:15.805279Z

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.

Observation d4cb0844-9fd9-46a9-a2ab-7445ea2a6490 · 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 MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T23:35:06.995731Z

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.

Observation 7c39c3e1-b733-4c05-a127-d018a7747b8f · inbound

VESTA: Visual Exploration with Statistical Tool Agents cites this paper.

VESTA: Visual Exploration with Statistical Tool Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-01T19:56:10.520983Z

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.

Observation ac48592d-2c15-40fc-9674-b48ffeda9bf4 · inbound

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models cites this paper.

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-01T23:06:21.108710Z

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.

Observation ba8327f8-3fcf-45f8-97e5-32533a365df6 · inbound

Can Generalist Agents Automate Data Curation? cites this paper.

Can Generalist Agents Automate Data Curation? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:56:35.137529Z

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.

Observation bb561dac-0119-4a07-b03e-764941fb9271 · inbound

The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development? cites this paper.

The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development? MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-02T07:56:47.678461Z

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.

Observation c2edd2e1-602e-4a3b-aa4e-74a69caf9de2 · inbound

Towards Persistent Case-Based Memory for Autonomous Data Science: A CBR-Augmented R&D-Agent with a Locally Deployable Small Language Model cites this paper.

Towards Persistent Case-Based Memory for Autonomous Data Science: A CBR-Augmented R&D-Agent with a Locally Deployable Small Language Model MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-07-02T10:06:51.727212Z

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.

Observation 53dc74d2-7240-4d29-8666-bc7c511b3a01 · inbound

Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories cites this paper.

Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-07-03T04:37:37.769214Z

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.

Observation 63a7b378-6de1-4e7d-8e33-4a76c8fd6d57 · inbound

Search Discipline for Long-Horizon Research Agents cites this paper.

Search Discipline for Long-Horizon Research Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-06-27T13:30:57.161480Z

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.

Observation 63ca5120-9179-411c-96a6-ee7e58da9f14 · inbound

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement cites this paper.

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 115

Resolution: verified exact; local_arxiv, observed 2026-06-27T09:40:47.023998Z

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.