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Paper Citation Record · LEDGER

SciDataSailor: Deep Scientific Data Exploring

As of 7 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 2 inbound Pith citation observations for arXiv:2607.28098.

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

pith.paper-citation-record.v1
2607.28098 v1

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:02:42.604007Z

measured 79 of 79 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T03:20:50.048642Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

77 of 77 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved75
  • parse uncertain1
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a19c0c4d-d261-4b45-8320-ea803f21b9e0 · outbound

This paper cites Data mining and knowledge discovery in databases: implications for scientific databases.

SciDataSailor: Deep Scientific Data Exploring Data mining and knowledge discovery in databases: implications for scientific databases

Reference 1

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source=pdf_text observed=2026-08-01T15:02:35.844070Z digest=sha256:b1e935d5634652998c6697855b6384edd3a80553839f92256b57838c65008627

Observation f7ec372e-741f-4dab-a31b-50a8596daef3 · outbound

This paper cites Scidatacopilot: An agentic data preparation framework for agi-driven scientific discovery.

SciDataSailor: Deep Scientific Data Exploring Scidatacopilot: An agentic data preparation framework for agi-driven scientific discovery

Reference 2

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source=pdf_text observed=2026-08-01T15:02:35.949271Z digest=sha256:e2044062098b1568f74c8b31a12ec3bfd32e7c7675884b5c6ff0d428e766e5f2

Observation c4a75035-a32d-4996-b119-042fa16945cf · outbound

This paper cites Cellvoyager: Ai compbio agent generates new insights by autonomously analyzing biological data.Nature Methods, 2026.

SciDataSailor: Deep Scientific Data Exploring Cellvoyager: Ai compbio agent generates new insights by autonomously analyzing biological data.Nature Methods, 2026

Reference 3

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source=pdf_text observed=2026-08-01T15:02:36.046287Z digest=sha256:cf7a1b80cc8775c992dda5ba622e5b18e8396672ac169b213de6019f29c16443

Observation 05322c31-f044-4ca5-9c75-a9d67183c6a0 · outbound

This paper cites scbasecount: an ai agent-curated, uniformly processed, and autonomously updated single cell data repository.bioRxiv, 2025.

SciDataSailor: Deep Scientific Data Exploring scbasecount: an ai agent-curated, uniformly processed, and autonomously updated single cell data repository.bioRxiv, 2025

Reference 4

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source=pdf_text observed=2026-08-01T15:02:36.137282Z digest=sha256:7700e70a826e27f71705a9f10d1fae1b91c857879b4591ffe50d09a09551fbb5

Observation b7b13479-2c42-4215-9ba6-ceb72ba058f4 · outbound

This paper cites Data harmonization for heterogeneous datasets: a systematic literature review.Applied Sciences, 2021.

SciDataSailor: Deep Scientific Data Exploring Data harmonization for heterogeneous datasets: a systematic literature review.Applied Sciences, 2021

Reference 5

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source=pdf_text observed=2026-08-01T15:02:36.222309Z digest=sha256:06b0e6f56752746b31e7a1600325342333479a9b2b55e90673327dd888c211b8

Observation 4a414705-5232-410d-8538-9d6c127192ee · outbound

This paper cites Data integration for heterogenous datasets.Big data, 2014.

SciDataSailor: Deep Scientific Data Exploring Data integration for heterogenous datasets.Big data, 2014

Reference 6

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source=pdf_text observed=2026-08-01T15:02:36.282273Z digest=sha256:4c8dbfc2c530c7157c1fdec898e9d790a26c719ed8c1c391d033fb70d6b89f9c

Observation 33a33fa6-888d-49dc-8485-f0dd27ee6d10 · outbound

This paper cites Does the use of unusual combinations of datasets contribute to greater scientific impact?Proceedings of the National Academy of Sciences, 2024.

SciDataSailor: Deep Scientific Data Exploring Does the use of unusual combinations of datasets contribute to greater scientific impact?Proceedings of the National Academy of Sciences, 2024

Reference 7

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source=pdf_text observed=2026-08-01T15:02:36.366835Z digest=sha256:0de0f81c2edc7eba7cdd78dc05be29bbe4023653288fe2699c83a477f9708480

Observation 26774ca3-c90e-4879-9b3c-41be4a38f8f3 · outbound

This paper cites A repository for the publication and sharing of heterogeneous materials data.

SciDataSailor: Deep Scientific Data Exploring A repository for the publication and sharing of heterogeneous materials data

Reference 8

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source=pdf_text observed=2026-08-01T15:02:36.435339Z digest=sha256:e1bc361f5c5085017492ab89e3e59ded8f60168418e38407f93a0bee426f999c

Observation 05e67e9c-8d4a-4eab-96e9-ee07473f383c · outbound

This paper cites Hiersearch: A hierarchical enterprise deep search framework integrating local and web searches.

SciDataSailor: Deep Scientific Data Exploring Hiersearch: A hierarchical enterprise deep search framework integrating local and web searches

Reference 9

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source=pdf_text observed=2026-08-01T15:02:36.510840Z digest=sha256:9e93d2fb247b1610035af20dd592a05ca7cadd952b40e8d5d34a8299f37c90e2

Observation fc4a7b67-4396-4f28-ae68-fda642726d70 · outbound

This paper cites Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs.

SciDataSailor: Deep Scientific Data Exploring Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs

Reference 10

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source=pdf_text observed=2026-08-01T15:02:36.593145Z digest=sha256:2cf425b8fc99b5a85816dc32d90349a2c9b1027d2c544a891e76a7fd77cd5981

Observation 8705d3e9-149c-4d30-935a-13ff6fe38830 · outbound

This paper cites A survey of personalization: From rag to agent.ACM Transactions on Information Systems, 2025.

SciDataSailor: Deep Scientific Data Exploring A survey of personalization: From rag to agent.ACM Transactions on Information Systems, 2025

Reference 11

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source=pdf_text observed=2026-08-01T15:02:36.691731Z digest=sha256:9aa0d83389885ebaf1df7339c18492e9e91b12fcc87513575e5149f1ed33f543

Observation 74d290db-bb75-4659-861e-0aa3415d78f6 · outbound

This paper cites Sqlfixagent: Towards semantic-accurate text-to-sql parsing via consistency-enhanced multi-agent collaboration.

SciDataSailor: Deep Scientific Data Exploring Sqlfixagent: Towards semantic-accurate text-to-sql parsing via consistency-enhanced multi-agent collaboration

Reference 12

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source=pdf_text observed=2026-08-01T15:02:36.756510Z digest=sha256:89ecdefc81c7ce6b632a8a0015987852eafecf7773ef6904ea8a0c19a96dd6d2

Observation 0b06c174-6040-4f4e-95d9-e6502fa15e3b · outbound

This paper cites this is my sql, are you with me?.

SciDataSailor: Deep Scientific Data Exploring this is my sql, are you with me?

Reference 13

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source=pdf_text observed=2026-08-01T15:02:36.819280Z digest=sha256:0aec218be0b2984fa4d113818b7ae978ba161fd15cfc2e7217dc2b6fae148ae4

Observation ba7bce7b-deed-4f19-8704-ae117fef9445 · outbound

This paper cites From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents.

SciDataSailor: Deep Scientific Data Exploring From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents

Reference 14

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source=pdf_text observed=2026-08-01T15:02:36.884640Z digest=sha256:0be74ef8d3359411f22bac5e90ffb8c8d42618d75c320ae92bdaa8f2f49ecd7b

Observation 739c0335-8ff3-4bea-9c35-098ac4939804 · outbound

This paper cites Deep Research Agents: A Systematic Examination And Roadmap.

SciDataSailor: Deep Scientific Data Exploring Deep Research Agents: A Systematic Examination And Roadmap

Reference 15

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source=pdf_text observed=2026-08-01T15:02:36.965352Z digest=sha256:a1c77f4fbd69bc82a10233ff1e6937e4406fd4c3d200cffb82bf03d13c0d9ebc

Observation 7316b579-fadf-432c-993a-8c296e06f9a3 · outbound

This paper cites DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent.

SciDataSailor: Deep Scientific Data Exploring DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent

Reference 16

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source=pdf_text observed=2026-08-01T15:02:37.058668Z digest=sha256:3b39dc831d5b13d32206477c7e9b19aa2b13bc0c2d63391544f489166f37b5fe

Observation 174cd057-33aa-400c-9e30-e778f10878dc · outbound

This paper cites Deepwidesearch: Benchmarking depth and width in agentic information seeking.arXiv preprint arXiv:2510.20168, 2025.

SciDataSailor: Deep Scientific Data Exploring Deepwidesearch: Benchmarking depth and width in agentic information seeking.arXiv preprint arXiv:2510.20168, 2025

Reference 17

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source=pdf_text observed=2026-08-01T15:02:37.144295Z digest=sha256:7d27b2f9a9ef15d3e8986d0b7b7b4d14fe89ea0713e8a78b01eeb9be206a7b0b

Observation 148d3df6-dd32-4bdb-b58d-8649efa169ba · outbound

This paper cites Openseeker: Democ- ratizing frontier search agents by fully open-sourcing training data.arXiv preprint arXiv:2603.15594, 2026.

SciDataSailor: Deep Scientific Data Exploring Openseeker: Democ- ratizing frontier search agents by fully open-sourcing training data.arXiv preprint arXiv:2603.15594, 2026

Reference 18

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source=pdf_text observed=2026-08-01T15:02:37.228103Z digest=sha256:85b39676381388b80b3012f79d5f3b1cc540e4d6f9aa6f0e78e5f5545a2e2ec6

Observation 4b7a2568-b7df-4f4f-8715-e76b6994cb1b · outbound

This paper cites WebSailor: Navigating Super-human Reasoning for Web Agent.

SciDataSailor: Deep Scientific Data Exploring WebSailor: Navigating Super-human Reasoning for Web Agent

Reference 19

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source=pdf_text observed=2026-08-01T15:02:37.319474Z digest=sha256:145f96f595841747d70a019c3c87e51d58bc12ac45694c264a00ae52aa0e0044

Observation 28e34892-344b-417f-903b-fb7931de2bbb · outbound

This paper cites Websailor-v2: Bridging the chasm to proprietary agents via synthetic data and scalable reinforcement learning.arXiv preprint arXiv:2509.13305, 2025.

SciDataSailor: Deep Scientific Data Exploring Websailor-v2: Bridging the chasm to proprietary agents via synthetic data and scalable reinforcement learning.arXiv preprint arXiv:2509.13305, 2025

Reference 20

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source=pdf_text observed=2026-08-01T15:02:37.402678Z digest=sha256:ed5df85d587a1df4bf569a4feda3994b7532cc63d92ceee5e1857b8345bbbc33

Observation 4dad7483-1a9d-443a-bdd5-154efb22a1b4 · outbound

This paper cites Open Deep Search: Democratizing Search with Open-source Reasoning Agents.

SciDataSailor: Deep Scientific Data Exploring Open Deep Search: Democratizing Search with Open-source Reasoning Agents

Reference 21

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source=pdf_text observed=2026-08-01T15:02:37.488903Z digest=sha256:584e69d3b65e6b442140b5e57e31c7b4b7d21e339b455d093f33f297dba8eca8

Observation 37c8a74a-ced0-4a12-8385-bd36b3640d68 · outbound

This paper cites LAB-Bench: Measuring Capabilities of Language Models for Biology Research.

SciDataSailor: Deep Scientific Data Exploring LAB-Bench: Measuring Capabilities of Language Models for Biology Research

Reference 22

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source=pdf_text observed=2026-08-01T15:02:37.574663Z digest=sha256:52d23314e6cc22ed5348fe53f4f26e1ccfe069472231ebf968d126c9b704cccc

Observation 0cc883a2-0f45-4795-b01b-0f8119b96d96 · outbound

This paper cites BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science.

SciDataSailor: Deep Scientific Data Exploring BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science

Reference 23

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source=pdf_text observed=2026-08-01T15:02:37.658747Z digest=sha256:7cfa04526a7da59ba08bf6a2d226d7f7f484f16be7c172d45d3e2ecad51a545d

Observation e7b4557f-3ebc-4c7f-bc97-fcf3412c662e · outbound

This paper cites Curie: Evaluating llms on multitask scientific long context understanding and reasoning.International Conference on Learning Representations, 2025.

SciDataSailor: Deep Scientific Data Exploring Curie: Evaluating llms on multitask scientific long context understanding and reasoning.International Conference on Learning Representations, 2025

Reference 24

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source=pdf_text observed=2026-08-01T15:02:37.751577Z digest=sha256:0c58b79c95aa13cdd27e0b867f557517d48eb64a6cae9d81e2c8ff10330cc36a

Observation 487e51cc-4ac0-47cd-a22e-49062cd04b05 · outbound

This paper cites ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery.

SciDataSailor: Deep Scientific Data Exploring ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery

Reference 25

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source=pdf_text observed=2026-08-01T15:02:37.896688Z digest=sha256:ad212a82aa511b7943d53ae5eff702a8da05df38cdb548afbd485bd06fd70341

Observation 927f9d1a-8d22-4c19-b73e-2f7e708f489b · outbound

This paper cites Bixbench: a comprehensive bench- mark for llm-based agents in computational biology.arXiv preprint arXiv:2503.00096, 2025.

SciDataSailor: Deep Scientific Data Exploring Bixbench: a comprehensive bench- mark for llm-based agents in computational biology.arXiv preprint arXiv:2503.00096, 2025

Reference 26

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source=pdf_text observed=2026-08-01T15:02:38.016857Z digest=sha256:52acf5c3af4663d47e02f7dc212bcb4b9b9e3c935cda1cf99534afd37851164c

Observation 6f8118cb-6446-403b-82b9-e8936a1bbc74 · outbound

This paper cites BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics.

SciDataSailor: Deep Scientific Data Exploring BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Reference 27

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source=pdf_text observed=2026-08-01T15:02:38.129421Z digest=sha256:4b5104a11da9c31a80c02105a4794951d63e22dc5dfb244c2e9974b05e1676a7

Observation 0f3c4954-f2f3-4642-97b1-16ba229cbb8b · outbound

This paper cites MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery.

SciDataSailor: Deep Scientific Data Exploring MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery

Reference 28

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source=pdf_text observed=2026-08-01T15:02:38.278796Z digest=sha256:429e1b482775f232caaf30736add07213f25d3887309d20c3fbd22c3b0940741

Observation 22c622a3-1801-4f22-a4bc-fbbf7305bf7e · outbound

This paper cites Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists.

SciDataSailor: Deep Scientific Data Exploring Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists

Reference 29

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source=pdf_text observed=2026-08-01T15:02:38.393054Z digest=sha256:ee39887d31961b1bafe0dc3c0c46a7adfe503fb3472c615b0678c47cab734a2b

Observation b70495ab-7b58-4906-889c-94aea9c22478 · outbound

This paper cites SWE-Explore: Benchmarking How Coding Agents Explore Repositories.

SciDataSailor: Deep Scientific Data Exploring SWE-Explore: Benchmarking How Coding Agents Explore Repositories

Reference 30

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source=pdf_text observed=2026-08-01T15:02:38.513880Z digest=sha256:b2e71bddcdcc5fd605e74873bd408accdb2ec94dd9e39a7e3bc4efbe634c6cc5

Observation 9a2e081d-61bc-4ecf-9afe-d7630047f9dd · outbound

This paper cites Scaling generalist data-analytic agents.International Conference on Learning Representations, 2026.

SciDataSailor: Deep Scientific Data Exploring Scaling generalist data-analytic agents.International Conference on Learning Representations, 2026

Reference 31

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source=pdf_text observed=2026-08-01T15:02:38.621060Z digest=sha256:611bc514f40b70dbda6caf97f156d7cb9a5ee79d77424747feb8d3b577f9cd53

Observation 89f7c97b-322e-4f41-994b-dd5f3834f45c · outbound

This paper cites Agentic reinforced policy optimization.

SciDataSailor: Deep Scientific Data Exploring Agentic reinforced policy optimization

Reference 32

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source=pdf_text observed=2026-08-01T15:02:38.710415Z digest=sha256:fb2e52dbfd00c1d88e0906741a5729f44791ee4f2e09aec18c2c53ad2888cef7

Observation ff0148fc-781d-433e-b683-d9cb28c8e644 · outbound

This paper cites Deepanalyze: Agentic large language models for autonomous data science.arXiv preprint arXiv:2510.16872, 2025.

SciDataSailor: Deep Scientific Data Exploring Deepanalyze: Agentic large language models for autonomous data science.arXiv preprint arXiv:2510.16872, 2025

Reference 33

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source=pdf_text observed=2026-08-01T15:02:38.798190Z digest=sha256:78591dd5a47aeb6e81acb61ea609c437e6953a1bec32a755cdd23e0bf359c432

Observation 6c5f74a3-41da-416e-8a97-0266af65f451 · outbound

This paper cites Dataflow: An llm-driven framework for unified data preparation and workflow automation in the era of data-centric ai.arXiv preprint arXiv:2512.16676, 2025.

SciDataSailor: Deep Scientific Data Exploring Dataflow: An llm-driven framework for unified data preparation and workflow automation in the era of data-centric ai.arXiv preprint arXiv:2512.16676, 2025

Reference 34

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source=pdf_text observed=2026-08-01T15:02:38.962537Z digest=sha256:248c5ac5936f99db72636ee1e2d6bcfc43d87352b7cb5dcc482271ea2e9ef111

Observation 3a998933-480d-4128-918e-89506824d753 · outbound

This paper cites Dataflex: A unified framework for data-centric dynamic training of large language models.arXiv preprint arXiv:2603.26164, 2026.

SciDataSailor: Deep Scientific Data Exploring Dataflex: A unified framework for data-centric dynamic training of large language models.arXiv preprint arXiv:2603.26164, 2026

Reference 35

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source=pdf_text observed=2026-08-01T15:02:39.049102Z digest=sha256:d29582961299876c8a94fbdada24a94425a1163e614157495b2ca901233c8ef5

Observation bf1f76ed-b351-47be-98a6-7940aa98e746 · outbound

This paper cites Agentflow: Unified agent data synthesis framework.

SciDataSailor: Deep Scientific Data Exploring Agentflow: Unified agent data synthesis framework

Reference 36

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Observation 6a68402e-9a60-42d6-a6e7-32c2b3f9049e · outbound

This paper cites Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent.

SciDataSailor: Deep Scientific Data Exploring Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent

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source=pdf_text observed=2026-08-01T15:02:39.316443Z digest=sha256:4092e34528df1ea27b0a66528cf157f7e57b5764b0b7a8b8fece97c9a580a6fa

Observation b0a5e653-bbb4-43ac-b956-20349b224f00 · outbound

This paper cites I-mcts: Enhancing agentic automl via introspective monte carlo tree search.Association for Computational Linguistics, 2026.

SciDataSailor: Deep Scientific Data Exploring I-mcts: Enhancing agentic automl via introspective monte carlo tree search.Association for Computational Linguistics, 2026

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source=pdf_text observed=2026-08-01T15:02:39.449995Z digest=sha256:e7a6d40d2914f55a5831060a5b48a5120a09605ebffda840cb5cd3117b67f3a5

Observation eb495bf5-7b67-421e-8c1c-4cf07baef179 · outbound

This paper cites Treerl: Llm reinforcement learning with on-policy tree search.

SciDataSailor: Deep Scientific Data Exploring Treerl: Llm reinforcement learning with on-policy tree search

Reference 39

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source=pdf_text observed=2026-08-01T15:02:39.555595Z digest=sha256:2673310bb018cb45ee0b1f10d386fa66a2aacb99b206626aea4eb359473d09e7

Observation 17ae53a5-edad-4b56-affe-6af51e73bca0 · outbound

This paper cites Tooltree: Efficient llm agent tool planning via dual-feedback monte carlo tree search and bidirectional pruning.

SciDataSailor: Deep Scientific Data Exploring Tooltree: Efficient llm agent tool planning via dual-feedback monte carlo tree search and bidirectional pruning

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source=pdf_text observed=2026-08-01T15:02:39.669378Z digest=sha256:434dd299da22de7c822777195af0ec64782eaad966353933ffc09ed14b302f39

Observation 394571eb-4e9b-4a67-8f89-8355090c7d86 · outbound

This paper cites The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey.

SciDataSailor: Deep Scientific Data Exploring The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey

Reference 41

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source=pdf_text observed=2026-08-01T15:02:39.738393Z digest=sha256:808e3f7cbbf6372d0e66be8b7a953db19952ff9bb36e4f823800c73326dfb4d6

Observation db9ffb9c-b92f-4c91-9959-bd768c2d360c · outbound

This paper cites Menti: Bridging medical calculator and llm agent with nested tool calling.

SciDataSailor: Deep Scientific Data Exploring Menti: Bridging medical calculator and llm agent with nested tool calling

Reference 42

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source=pdf_text observed=2026-08-01T15:02:39.810309Z digest=sha256:3541c7d7497671ede9f3694a2488ac78ede6d94cc920d5f55ff26774fde167aa

Observation 36eca45c-45be-4f45-9f20-89aaabf7c07e · outbound

This paper cites Re- act: Synergizing reasoning and acting in language models.

SciDataSailor: Deep Scientific Data Exploring Re- act: Synergizing reasoning and acting in language models

Reference 43

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source=pdf_text observed=2026-08-01T15:02:39.883154Z digest=sha256:f067ce7c2d373c4159c5a184b74cefdb236eacd0e7ecdf87ea91c3825737afaa

Observation 2ae56f04-92bb-42f4-ba89-2ab9abc1db7f · outbound

This paper cites Jaap van den Herik, Paolo Ciancarini, and H.

SciDataSailor: Deep Scientific Data Exploring Jaap van den Herik, Paolo Ciancarini, and H

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source=pdf_text observed=2026-08-01T15:02:39.940861Z digest=sha256:71955f33cf1d41ff0eab97e412e9371b252edf3c96cd45129661b191d79882e1

Observation ded15bb1-b35f-4e22-bb2a-fcf7a7072e3d · outbound

This paper cites Executable code actions elicit better llm agents.

SciDataSailor: Deep Scientific Data Exploring Executable code actions elicit better llm agents

Reference 45

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source=pdf_text observed=2026-08-01T15:02:39.992441Z digest=sha256:961aa8676c55194f935e81faad05f3807022409fc9be76352cd0a799e58fa25e

Observation 724cee80-1251-4f88-af66-3fbf7e395304 · outbound

This paper cites Gpt-5.4 thinking system card.

SciDataSailor: Deep Scientific Data Exploring Gpt-5.4 thinking system card

Reference 46

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source=pdf_text observed=2026-08-01T15:02:40.077490Z digest=sha256:b15e91226d0386b6f832254b179b4eef5c27ffd4e7a3a86f770d5dde276dc4e7

Observation ebcc6646-bafd-42c4-a284-f525c3e267e7 · outbound

This paper cites Gemini 3.1 pro model card.

SciDataSailor: Deep Scientific Data Exploring Gemini 3.1 pro model card

Reference 47

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source=pdf_text observed=2026-08-01T15:02:40.179936Z digest=sha256:92ab339eef2a9aff5196b4566f72143266b5791a8d81a60dd56997c575543e10

Observation e3d1ff6d-4199-4597-af6f-01e0fb270b91 · outbound

This paper cites System card: Claude opus 4.7.

SciDataSailor: Deep Scientific Data Exploring System card: Claude opus 4.7

Reference 48

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source=pdf_text observed=2026-08-01T15:02:40.260007Z digest=sha256:bfc2bc8b8a229b8996e597c445d405024dbce51e1f0c08a428022fe08cbe94e9

Observation dab12d05-e896-4429-aef9-324c2d7d3b36 · outbound

This paper cites GLM-5: from Vibe Coding to Agentic Engineering.

SciDataSailor: Deep Scientific Data Exploring GLM-5: from Vibe Coding to Agentic Engineering

Reference 49

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source=pdf_text observed=2026-08-01T15:02:40.321830Z digest=sha256:4f92549a9681b1443fd9646fe0fcb4367a39b4d3cb7fedfdedda70f1c088a21e

Observation 28e413a7-509a-4dce-a491-7dc0507c5a9d · outbound

This paper cites Kimi k2.6 model card.https://www.kimi.com/blog/kimi-k2-6, 2026.

SciDataSailor: Deep Scientific Data Exploring Kimi k2.6 model card.https://www.kimi.com/blog/kimi-k2-6, 2026

Reference 50

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source=pdf_text observed=2026-08-01T15:02:40.409897Z digest=sha256:7e88fc568ac9d6f9921f54486cec20d335c75fbd231d54160499effa941c0cb0

Observation 97a3612a-aa25-4281-9852-244bcbac5897 · outbound

This paper cites Deepseek-v4: Towards highly efficient million-token context intelligence.arXiv preprint arXiv:2606.19348, 2026.

SciDataSailor: Deep Scientific Data Exploring Deepseek-v4: Towards highly efficient million-token context intelligence.arXiv preprint arXiv:2606.19348, 2026

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source=pdf_text observed=2026-08-01T15:02:40.465430Z digest=sha256:ffb4e5f228561f231eda259f1454e6f936fb57047f345e277064631f67fedcc4

Observation 97d29354-c353-4edc-8238-27092a2efa3d · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

SciDataSailor: Deep Scientific Data Exploring gpt-oss-120b & gpt-oss-20b Model Card

Reference 52

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source=pdf_text observed=2026-08-01T15:02:40.532302Z digest=sha256:f634a3809187c3ec48ca64b334a868475f2b52799d034aeb54c1650f3c613f37

Observation 75e42885-91e0-403a-9939-d89ef5d1f780 · outbound

This paper cites Qwen3 Technical Report.

SciDataSailor: Deep Scientific Data Exploring Qwen3 Technical Report

Reference 53

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source=pdf_text observed=2026-08-01T15:02:40.614959Z digest=sha256:19a3e0f5d989499300d677f1f49ea24fecf6645a3b7a178a42e6f85d09671f04

Observation 65096b18-990f-4d77-90a6-b228e5225496 · outbound

This paper cites Qwen3.5: Towards native multimodal agents.https://qwen.ai/blog?id=qwen3.5,.

SciDataSailor: Deep Scientific Data Exploring Qwen3.5: Towards native multimodal agents.https://qwen.ai/blog?id=qwen3.5,

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source=pdf_text observed=2026-08-01T15:02:40.691981Z digest=sha256:4d25a7ca9663d1df3b8c2e2e85ac63d0841be20f3c56bd102e8d428ebfa6b21b

Observation e7700bf8-dc75-461f-bd4b-99226b44a351 · outbound

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

SciDataSailor: Deep Scientific Data Exploring Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 55

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source=pdf_text observed=2026-08-01T15:02:40.858638Z digest=sha256:aef457eb4aa56ae0ddb2fb52fb1218460d5937a07b8433be74e1fd384e5a63da

Observation a095b0a8-a5a0-434d-af22-9b6e6a1f942d · outbound

This paper cites Llamafactory: Unified efficient fine-tuning of 100+ language models.

SciDataSailor: Deep Scientific Data Exploring Llamafactory: Unified efficient fine-tuning of 100+ language models

Reference 56

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source=pdf_text observed=2026-08-01T15:02:40.905909Z digest=sha256:d8401000ca6162c7b7e640834479c23a9340a34c574eea5c8e3014ca370a4b82

Observation da16be69-7765-4c09-ac29-a496362b4c11 · outbound

This paper cites Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters.

SciDataSailor: Deep Scientific Data Exploring Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters

Reference 57

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source=pdf_text observed=2026-08-01T15:02:40.963041Z digest=sha256:3b261bb456f6600da5d568080e1f479499be72a7d87a088531e732bdc3dbbda5

Observation c08e3cd1-8f54-4c3e-b768-3a5bc103f18b · outbound

This paper cites content":.

SciDataSailor: Deep Scientific Data Exploring content":

Reference 58

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source=pdf_text observed=2026-08-01T15:02:41.048192Z digest=sha256:52e16adb6f903ccf2f6cdb4cea41e43811eeb59b48818130b848ac9049cba478

Observation b4b7bf5b-8f9d-4b06-b7ae-f2edea20812e · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 411

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source=pdf_text observed=2026-08-01T15:02:41.571899Z digest=sha256:24da562ec868aa39de46e53da79af7c59ba063d1242638db64d7a442da00afde

Observation 09d45381-d402-4d37-a493-15ebd6958ecf · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 422

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source=pdf_text observed=2026-08-01T15:02:41.662003Z digest=sha256:492972dc4c103099e97b3954b1a97449027152627d5405e20772868246831b54

Observation 007837b8-6fa4-4e8d-803b-fc46553c99c2 · outbound

This paper cites {DATASET_ROOT}.

SciDataSailor: Deep Scientific Data Exploring {DATASET_ROOT}

Reference 433

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source=pdf_text observed=2026-08-01T15:02:41.755833Z digest=sha256:70c68071020c1062dc5eae3ffb1b754a64378893ab8f4d35fb42c82d3ddf09fa

Observation 7650578f-cf92-4792-88e7-7fb4f2911628 · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 2026

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source=pdf_text observed=2026-08-01T15:02:40.775819Z digest=sha256:c8ed78e5796d87e0a2db767d190b14cd0c4427f5e9aa04a36fec0b176af5ed6d

Observation 1158ceb2-5565-4885-b46f-93b59ba4fc63 · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 5421

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source=pdf_text observed=2026-08-01T15:02:41.110043Z digest=sha256:a0528629ce381e713b56c1ced2436507562ba3953057a0aa7bc3f4a6b96ae7ce

Observation 93b269f6-93d0-4e26-90cf-712983321096 · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 5452

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source=pdf_text observed=2026-08-01T15:02:41.212988Z digest=sha256:b643d8281d0aa7e2805736b16f94bd7f5e644329269b12bf2a03256667ae25a4

Observation f531384d-d9f2-46e6-bebd-de70ad3f913e · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 5483

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source=pdf_text observed=2026-08-01T15:02:41.258878Z digest=sha256:afe8b6b16c8e189265eec6cc05df81e8e6151e6e9c3fba42be95efd8133dea92

Observation 4b797739-42f9-4084-8dfd-9a20803d96b8 · outbound

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SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 5514

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source=pdf_text observed=2026-08-01T15:02:41.261124Z digest=sha256:c4f461cad184db4d86626706ed9bd270648c805549f40be079f5437ae7f0bb52

Observation 3666fa9c-b3ff-4bed-9c32-73a426d874ad · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 5555

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source=pdf_text observed=2026-08-01T15:02:41.326632Z digest=sha256:5016d10ce9598ef75ae3d1b9662894ce88b419b06848744d34710f91aacd4935

Observation 1cbf2e34-2430-4b2c-ba7f-456cd05347cb · outbound

This paper cites {DATASET_ROOT}.

SciDataSailor: Deep Scientific Data Exploring {DATASET_ROOT}

Reference 5586

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source=pdf_text observed=2026-08-01T15:02:41.449235Z digest=sha256:0303e9a71424edabb0f55c4fe6a0c2d9f40e84890d9afacb37d770c608ff50fe

Observation 53d4d444-727b-4ad1-96a2-98546e234e86 · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 7281

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source=pdf_text observed=2026-08-01T15:02:41.842336Z digest=sha256:dc7dc251526bcefe6f57efa83e82f8fbcd55a89fdaa1e7a2ae13d0c41320981c

Observation e40381c5-1824-4989-a581-4bad1c1132a9 · outbound

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SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 7292

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source=pdf_text observed=2026-08-01T15:02:41.933027Z digest=sha256:f4ae39abe03be8f583fd74e169009f1ddc237326e924655540e4f95bc07c0aa2

Observation 48208cdc-ae67-41b9-83bc-a6b8f42f417d · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 7303

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source=pdf_text observed=2026-08-01T15:02:41.992951Z digest=sha256:5f282d5048b8642467b00b2930ebec4cc2f60fa0356cb9879118518772f7f110

Observation c1ae4073-91ce-4ef9-872b-211b48207d54 · outbound

This paper cites {DATASET_ROOT}.

SciDataSailor: Deep Scientific Data Exploring {DATASET_ROOT}

Reference 7314

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source=pdf_text observed=2026-08-01T15:02:42.057873Z digest=sha256:021203c1481567c65da9a6571574193295e15dd59d5deb2a633aed32355d04fe

Observation a2af5b93-3d96-4244-97d4-6e26e3f9550a · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 8051

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source=pdf_text observed=2026-08-01T15:02:42.100521Z digest=sha256:333c3f2bd3c2f0e71866889bc33e1a74a52352f4ff49c9f6882e93e7f4518022

Observation 4cf1bc8d-b962-4b27-b612-fecef74fca63 · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 8062

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source=pdf_text observed=2026-08-01T15:02:42.188802Z digest=sha256:3d760150d6fe049364422ebc4bc094a20780c8a2fe8cc9761d8fd3b0896eda1a

Observation 09b00c8b-cac0-4990-8635-c06d0103a0df · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 8073

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source=pdf_text observed=2026-08-01T15:02:42.327211Z digest=sha256:91675d90a74b142249c06e2eb1d63cde20075b196321fdded2e0eeffe2611246

Observation 5ede7e60-10df-4c14-b3da-da9e2e4d8af1 · outbound

This paper cites an unresolved cited work.

SciDataSailor: Deep Scientific Data Exploring Unresolved cited work

Reference 8084

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source=pdf_text observed=2026-08-01T15:02:42.478631Z digest=sha256:f8a766af05afe1a6b993919c854d896e0ecb37f8eb29ef626e5263ccdbefa4d4

Observation 51a496ac-e36a-491f-81e9-32f7b1b9df07 · outbound

This paper cites {DATASET_ROOT}.

SciDataSailor: Deep Scientific Data Exploring {DATASET_ROOT}

Reference 8155

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no resolver link, observed 2026-08-01T15:02:42.604007Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T15:02:42.604007Z digest=sha256:8260c78a8f53474dc921e9bf0834186fbe7ad8f09d82d8e91701c60780983788

Pith citing papers

Observation 4ccd97be-210c-4f91-b4c8-c61fdbf9ce07 · inbound

EasyBCI Agent: Towards Universal Neural Data Preprocessing for Brain-Computer Interfaces cites this paper.

EasyBCI Agent: Towards Universal Neural Data Preprocessing for Brain-Computer Interfaces SciDataSailor: Deep Scientific Data Exploring

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-03T15:35:12.134758Z

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source=pdf_text observed=2026-08-03T15:35:12.134758Z digest=sha256:60e3da521dc9d6d992607440f731e9888385ca5b0ff3ea25cb703e6b60a3b271

Observation 7f5b0f28-ec26-4c02-8612-193b05ee8d99 · inbound

EasyBCI Agent: Towards Universal Neural Data Preprocessing for Brain-Computer Interfaces cites this paper.

EasyBCI Agent: Towards Universal Neural Data Preprocessing for Brain-Computer Interfaces SciDataSailor: Deep Scientific Data Exploring

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T03:20:50.048642Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T03:20:50.048642Z digest=sha256:f65b8eb94d2c08c346b03197f150713b91004d325d27f9de23adc1460ec72839