Paper Citation Record · LEDGER

TusoAI: Agentic Optimization for Scientific Methods

As of 5 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 3 inbound Pith citation observations for arXiv:2509.23986.

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

pith.paper-citation-record.v1
2509.23986 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-21T22:34:06.906427Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T21:56:39.900301Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-02T17:37:14.707396Z

Reference resolution

47 of 47 outbound references displayed

verified exact23
verified fuzzy18
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5eeeefd5-1972-49c4-b240-23c1346220c6 · outbound

This paper cites Semantic scholar.

TusoAI: Agentic Optimization for Scientific Methods Semantic scholar

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.630572Z

Source-reported events for the cited work

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

Observation 29338dad-9689-4615-9e81-b444d86fc608 · outbound

This paper cites OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs.

TusoAI: Agentic Optimization for Scientific Methods OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T22:34:23.817614Z

Source-reported events for the cited work

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

Observation 66bced95-6ae6-4c54-9ade-6c8aafd3c66a · outbound

This paper cites An AI system to help scientists write expert-level empirical software.

TusoAI: Agentic Optimization for Scientific Methods An AI system to help scientists write expert-level empirical software

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-21T22:34:23.807513Z

Source-reported events for the cited work

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

Observation c0795c81-ec9f-49da-b5aa-f0ad7ce8f31f · outbound

This paper cites Bower, E.

TusoAI: Agentic Optimization for Scientific Methods Bower, E

Reference 4

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.494056Z

Source-reported events for the cited work

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

Observation 3596d654-e197-4cd1-8753-7a2aa8ebe8ca · outbound

This paper cites Roumeliotis, et al.

TusoAI: Agentic Optimization for Scientific Methods Roumeliotis, et al

Reference 5

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.497132Z

Source-reported events for the cited work

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

Observation 1adb897b-5e97-4b9e-aab8-6840958c4868 · outbound

This paper cites Chakera, Anna M.

TusoAI: Agentic Optimization for Scientific Methods Chakera, Anna M

Reference 6

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.490769Z

Source-reported events for the cited work

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

Observation f8960f2d-87f4-4f4b-b903-a8654070d102 · outbound

This paper cites an unresolved cited work.

TusoAI: Agentic Optimization for Scientific Methods Unresolved cited work

Reference 7

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.487603Z

Source-reported events for the cited work

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

Observation f009be91-7579-4a70-bf30-1baa6f10e72e · outbound

This paper cites Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance.

TusoAI: Agentic Optimization for Scientific Methods Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.587669Z

Source-reported events for the cited work

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

Observation 32d8b357-4674-4403-b2c9-3bf4dc0ae97b · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

TusoAI: Agentic Optimization for Scientific Methods AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-21T22:34:23.810638Z

Source-reported events for the cited work

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

Observation a4bceed7-2c12-4bfc-8d6a-316b0b84330f · outbound

This paper cites CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

TusoAI: Agentic Optimization for Scientific Methods CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-21T22:34:23.814355Z

Source-reported events for the cited work

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

Observation 03fa1458-05c7-4f79-a97b-0f8fc2ba3396 · outbound

This paper cites Efficient and robust automated machine learning.

TusoAI: Agentic Optimization for Scientific Methods Efficient and robust automated machine learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.607118Z

Source-reported events for the cited work

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

Observation 10f045d5-43f4-41d5-886c-c669f3c9970b · outbound

This paper cites Alan Permutt, Jacques S.

TusoAI: Agentic Optimization for Scientific Methods Alan Permutt, Jacques S

Reference 12

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.509230Z

Source-reported events for the cited work

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

Observation 5eedb0ce-db15-40d1-9e69-7be4d70ab44a · outbound

This paper cites Empowering biomedical discovery with ai agents.

TusoAI: Agentic Optimization for Scientific Methods Empowering biomedical discovery with ai agents

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.621170Z

Source-reported events for the cited work

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

Observation 9e65d72f-3b98-41c0-af95-e07588259148 · outbound

This paper cites Dey, Joseph Nasser, Kumar A.

TusoAI: Agentic Optimization for Scientific Methods Dey, Joseph Nasser, Kumar A

Reference 14

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.503658Z

Source-reported events for the cited work

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

Observation 44f2056f-ab41-4a1b-b5ce-6602ea9b8569 · outbound

This paper cites DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning.

TusoAI: Agentic Optimization for Scientific Methods DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:34:23.772365Z

Source-reported events for the cited work

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

Observation 57efa7fb-b734-417a-b6a0-2288ae8372e7 · outbound

This paper cites Biomni: A general-purpose biomedical ai agent.

TusoAI: Agentic Optimization for Scientific Methods Biomni: A general-purpose biomedical ai agent

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.626035Z

Source-reported events for the cited work

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

Observation c5f4a6bf-4586-4297-90f2-0c79aa5eb2d0 · outbound

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

TusoAI: Agentic Optimization for Scientific Methods AIDE: AI-Driven Exploration in the Space of Code

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-21T22:34:23.775102Z

Source-reported events for the cited work

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

Observation 43a2d21d-58ea-476a-98b4-6e2f1be95849 · outbound

This paper cites STELLA: Self-Evolving LLM Agent for Biomedical Research.

TusoAI: Agentic Optimization for Scientific Methods STELLA: Self-Evolving LLM Agent for Biomedical Research

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T22:34:23.784285Z

Source-reported events for the cited work

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

Observation de97890f-ed0b-4506-a8a8-7f9b36502426 · outbound

This paper cites From variant to function in human disease genetics.

TusoAI: Agentic Optimization for Scientific Methods From variant to function in human disease genetics

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.615932Z

Source-reported events for the cited work

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

Observation 46c5e5a0-9aaa-4b80-807e-030b3d502c20 · outbound

This paper cites H2o automl: Scalable automatic machine learning.

TusoAI: Agentic Optimization for Scientific Methods H2o automl: Scalable automatic machine learning

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.623735Z

Source-reported events for the cited work

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

Observation cc006ca2-2997-4522-9515-2c83347bb477 · outbound

This paper cites Sullivan, Jens Hjerling-Leffler, Naomi R.

TusoAI: Agentic Optimization for Scientific Methods Sullivan, Jens Hjerling-Leffler, Naomi R

Reference 21

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.506784Z

Source-reported events for the cited work

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

Observation 71bc5a78-e849-4d1f-b27c-8321d72f7ac4 · outbound

This paper cites Linderman, Jiajun Zhao, Maria Roulis, et al.

TusoAI: Agentic Optimization for Scientific Methods Linderman, Jiajun Zhao, Maria Roulis, et al

Reference 22

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.517601Z

Source-reported events for the cited work

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

Observation be8277de-cbf2-4973-bf07-00e0eee7b94c · outbound

This paper cites DARTS: Differentiable Architecture Search.

TusoAI: Agentic Optimization for Scientific Methods DARTS: Differentiable Architecture Search

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-21T22:34:23.778271Z

Source-reported events for the cited work

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

Observation 8218f1b4-6446-47a4-9a8f-eef3751d3103 · outbound

This paper cites an unresolved cited work.

TusoAI: Agentic Optimization for Scientific Methods Unresolved cited work

Reference 24

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.500586Z

Source-reported events for the cited work

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

Observation 98b62349-f1d4-4723-91b1-50fe5229c7ef · outbound

This paper cites Large language models surpass human experts in predicting neuroscience results.

TusoAI: Agentic Optimization for Scientific Methods Large language models surpass human experts in predicting neuroscience results

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.618802Z

Source-reported events for the cited work

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

Observation b8cd0f1b-cb64-4e12-9338-0ae64dfdee8c · outbound

This paper cites Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D White, and Philippe Schwaller.

TusoAI: Agentic Optimization for Scientific Methods Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D White, and Philippe Schwaller

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.613142Z

Source-reported events for the cited work

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

Observation 421181b9-dfe7-492e-8485-7a9976db908a · outbound

This paper cites Miller, Matthew Greenig, Benjamin Tenmann, and Bo Wang.

TusoAI: Agentic Optimization for Scientific Methods Miller, Matthew Greenig, Benjamin Tenmann, and Bo Wang

Reference 27

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.515095Z

Source-reported events for the cited work

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

Observation bdab9276-ba74-4f58-aab8-067ec66b0ca6 · outbound

This paper cites Ajay Nadig, Joseph M Replogle, Angela N Pogson, et al.

TusoAI: Agentic Optimization for Scientific Methods Ajay Nadig, Joseph M Replogle, Angela N Pogson, et al

Reference 28

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.512248Z

Source-reported events for the cited work

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

Observation 3b6f9146-c113-4ca5-b456-545766ad8586 · outbound

This paper cites MLE-STAR: Machine Learning Engineering Agent via Search and Targeted Refinement.

TusoAI: Agentic Optimization for Scientific Methods MLE-STAR: Machine Learning Engineering Agent via Search and Targeted Refinement

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:34:23.769493Z

Source-reported events for the cited work

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

Observation a240e81f-fc7f-4770-8267-04e5a0c28c96 · outbound

This paper cites Tpot: A tree-based pipeline optimization tool for automating machine learning.

TusoAI: Agentic Optimization for Scientific Methods Tpot: A tree-based pipeline optimization tool for automating machine learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.628365Z

Source-reported events for the cited work

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

Observation e9f0be5a-9349-466f-9279-2eb8eda11776 · outbound

This paper cites Introducing chatgpt agent: Bridging research and action.

TusoAI: Agentic Optimization for Scientific Methods Introducing chatgpt agent: Bridging research and action

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.584945Z

Source-reported events for the cited work

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

Observation a4118927-bdd8-4479-8bf5-4373e4ecbd38 · outbound

This paper cites Large Language Models for Code Generation: The Practitioners Perspective.

TusoAI: Agentic Optimization for Scientific Methods Large Language Models for Code Generation: The Practitioners Perspective

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:34:23.791229Z

Source-reported events for the cited work

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

Observation 6522bb75-e442-4e14-8610-6fa5be46a737 · outbound

This paper cites Mathematical discoveries from program search with large language models.

TusoAI: Agentic Optimization for Scientific Methods Mathematical discoveries from program search with large language models

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.582862Z

Source-reported events for the cited work

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

Observation cf66c00d-7588-4ef2-8121-4a237c0fe5f5 · outbound

This paper cites Seo, Sang K.

TusoAI: Agentic Optimization for Scientific Methods Seo, Sang K

Reference 34

Resolution: verified exact; doi, observed 2026-05-21T22:34:23.481102Z

Source-reported events for the cited work

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

Observation 91a3d5a9-40fe-4c18-a285-7db4896df33b · outbound

This paper cites Boxlm: Unifying structures and semantics of medical concepts for diagnosis prediction in healthcare.

TusoAI: Agentic Optimization for Scientific Methods Boxlm: Unifying structures and semantics of medical concepts for diagnosis prediction in healthcare

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.590456Z

Source-reported events for the cited work

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

Observation 5f585861-18d0-4624-a768-109689b502b1 · outbound

This paper cites Cellforge: Agentic design of virtual cell models.

TusoAI: Agentic Optimization for Scientific Methods Cellforge: Agentic design of virtual cell models

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:34:23.797816Z

Source-reported events for the cited work

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

Observation dab6946c-126b-4301-b8bf-295d040083f8 · outbound

This paper cites InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification.

TusoAI: Agentic Optimization for Scientific Methods InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T22:34:23.804595Z

Source-reported events for the cited work

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

Observation 60bc4674-b765-4019-b04a-1f5d1fc0f955 · outbound

This paper cites AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML.

TusoAI: Agentic Optimization for Scientific Methods AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:34:23.801120Z

Source-reported events for the cited work

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

Observation 5a515e29-178f-4324-a079-dcfb129c70d9 · outbound

This paper cites NAS -bench-360: Benchmarking neural architecture search on diverse tasks.

TusoAI: Agentic Optimization for Scientific Methods NAS -bench-360: Benchmarking neural architecture search on diverse tasks

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.587892Z

Source-reported events for the cited work

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

Observation 2d0a8644-415e-48f1-97aa-a0e5d2dbdf84 · outbound

This paper cites R&d-agent: Automating data-driven ai solution building through llm-powered automated research, development, and evolution.

TusoAI: Agentic Optimization for Scientific Methods R&d-agent: Automating data-driven ai solution building through llm-powered automated research, development, and evolution

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:34:23.787609Z

Source-reported events for the cited work

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

Observation aee9e069-ae01-4c67-b85f-9977dbaef5c7 · outbound

This paper cites Dolphin: Moving Towards Closed-loop Auto-research through Thinking, Practice, and Feedback.

TusoAI: Agentic Optimization for Scientific Methods Dolphin: Moving Towards Closed-loop Auto-research through Thinking, Practice, and Feedback

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T22:34:23.794279Z

Source-reported events for the cited work

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

Observation 4da86e16-a958-4ae1-b702-d27b1bb4ebc5 · outbound

This paper cites Polygenic enrichment distinguishes disease associations of individual cells in single-cell rna-seq data.

TusoAI: Agentic Optimization for Scientific Methods Polygenic enrichment distinguishes disease associations of individual cells in single-cell rna-seq data

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.590902Z

Source-reported events for the cited work

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

Observation 50dd02af-d625-4ee4-ab44-fb8b3a5450b6 · outbound

This paper cites An automated framework for efficiently designing deep convolutional neural networks in genomics.

TusoAI: Agentic Optimization for Scientific Methods An automated framework for efficiently designing deep convolutional neural networks in genomics

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.595514Z

Source-reported events for the cited work

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

Observation b4052157-f527-4299-9235-bf92a5e76314 · outbound

This paper cites write newline.

TusoAI: Agentic Optimization for Scientific Methods write newline

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.598482Z

Source-reported events for the cited work

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

Observation 64bdd3ef-b083-439f-8385-7f145bff794c · outbound

This paper cites @esa (Ref.

TusoAI: Agentic Optimization for Scientific Methods @esa (Ref

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T22:34:24.601430Z

Source-reported events for the cited work

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

Observation 9a646be7-758b-4fc3-8c74-0a1388137d77 · outbound

This paper cites an unresolved cited work.

TusoAI: Agentic Optimization for Scientific Methods Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-05-21T22:34:24.604432Z

Source-reported events for the cited work

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

Observation 6d1e10a0-3c06-4e97-b1fc-ef119bdc80a3 · outbound

This paper cites an unresolved cited work.

TusoAI: Agentic Optimization for Scientific Methods Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-05-21T22:34:24.610388Z

Source-reported events for the cited work

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

Pith citing papers

Observation d1e84cd2-d048-4198-aec9-bc7ea687f35f · inbound

SpatialEpiBench: Benchmarking Spatial Information and Epidemic Priors in Forecasting cites this paper.

SpatialEpiBench: Benchmarking Spatial Information and Epidemic Priors in Forecasting TusoAI: Agentic Optimization for Scientific Methods

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:02:55.804523Z

Source-reported events for the cited work

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

Observation 121288c7-b6c1-411a-b19c-169802764a39 · inbound

CellScientist: Dual-Space Hierarchical Orchestration for Closed-Loop Refinement of Virtual Cell Models cites this paper.

CellScientist: Dual-Space Hierarchical Orchestration for Closed-Loop Refinement of Virtual Cell Models TusoAI: Agentic Optimization for Scientific Methods

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:02:55.804523Z

Source-reported events for the cited work

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

Observation 5f263f6b-bff8-464f-9495-18f06cf42cc5 · inbound

A case study of evaluating AI agents on a neuroscience data-to-discovery pipeline cites this paper.

A case study of evaluating AI agents on a neuroscience data-to-discovery pipeline TusoAI: Agentic Optimization for Scientific Methods

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T17:37:14.708758Z

Source-reported events for the cited work

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