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Paper Citation Record · LEDGER

SciDataSailor: Deep Scientific Data Exploring

As of 15 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 2026-08-15T06:32:42.880941+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=sha256:78d821346c7b89c1be9dd31817f4fafa5da398b620ce6b8b141bb1b5cf9ad984

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:e010ebba15bd5d75fba0ebd5b670700a39c3c7aef55b8322cb6cc93a028b34a9

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=sha256:3a7d27622245075bbeaee76c865b38dcfe671ec1760d8d779cb2091c59d5ea6a

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=sha256:84c376801b60ed28399fbc4bc73a51ebc087a5832cf89a9beeb6d1056c790f69

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=sha256:662912460894977b7af12c1370391214417057bcc4a87d095017c7b57b264f3a

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=sha256:09ccc8417bcb74893ca98e6212ab9e14c3d93f770035bee16d6093821ce87eb6

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=sha256:6d3cf788ba83d4b5f7b9f52e8cd574a8e81c8ea0d4db6509e715439e78699ded

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:d6b19116acacbf3e75d2ff7898acf2555360cd3e349bd4e0c73e50dc293203a9

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=sha256:0b68e0d1d2a4d0dea8fc0289f050e1c6b9d63d4aa0c1fff2a2687992d28cdf38

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=sha256:5d8073e63dbd24e654374c405584573cb24065fc818723b2828520a979f50f52

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=sha256:3bfbe2e4d5cfbd4c6b507303831ae31ad44e74695fd60309e5fce779d294afbf

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:cb0f36e5f4b43217ff2a0682b1213418c12790544f9ab71abaa8bcb60308327c

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=sha256:0e9de5f5a346748117edc9fa7115fedb21cab90bc0aeadfa186a0c40c81b2abc

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:e5e10a776dcf0b898033b9caddffc38a55dd81d8a1257d0e5a0bbb6f1a3163cc

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=sha256:4b63ce2aa9a16672e9b5a9a24d4cb9e3b559f99acede74d7adc424e046a44ec8

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=sha256:06aac3dee50e0bee1f4e889fd08302b5ba14c820ff74a8d254d0cb81424f5999

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=sha256:51100272c5d227d5b6ebc31a7f9314ead75ff845fc2e0d95e063ccaea51a67a7

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:ef2b3b6aaa58ddea1f9c47df89ac1a224cf0b7d6dd84c4903e8e18168185e82d

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:ddf4ec70c91f8d6069b653657c79ec7924efbb0c57e97dfa350537b75a36e286

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=sha256:512b7aefbc56cf21681941c2a99b2d383d35d2349422da1c9c43be1a619764b0

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=sha256:2c2449efbc30035fced0de804a916366e2e9a961306ef36da6dda733303170fa

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:e9282e088ef91ab4f1d45c6d37bc41119da5fcee2f1b0b6fa2df398047b7e371

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:f073b717309a885c94ce19ed1809cfced36ab5ed55eff96c330089da2a576513

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:d329a9a33e38941cb9522a7a5a4b397b90458fbaa830e5dabfe95d7f14adf744

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=sha256:353b1ac4d08f4fb89272f8192d1b77542deb57cbc4b46cedc7b87047950edec1

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=sha256:3b6ba9d7259f21ddaeff7d2a77ac6da47f041d77d7fb2775aef58d3d1b72cc6b

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=sha256:1ec0c70fa0e1c9a6d1bf5a0ffc965f81c10bf1e1b312f0ed9099f454a332a18f

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=sha256:3396bfb0ecff62892b859abbbb8305dae52c99138bfdaa51d07a9f2d32cb4e94

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:d879baa1feb241a855ce10cddda493adaae68f6bb01a19085e1b305b1d7f2d45

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:dc47f6e4565b68c1959ca5644527b271f8c0cabc2d5576832ee7cd414bac871e

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=sha256:5a7422944db1d3f738b32305b386200f5eb43f9f619a621b761674800853ca6d

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:dff5b6181f9498178f5d784dd59572963dd5e783f3c0b9ab0b9cccf94b213237

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:ab79be672ecdbbd4c6f5563b19ab6143112f64f3bb2d850474a1f5615fa01497

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=sha256:854e08de0c6a09fce5cf7c354a3b4571e2ace9ca6608b1626db316edf2936e67

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:d773261114dabba4b72c6ea517aec09ef8c61ff22f534d0a86d95e19674f8847

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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source=pdf_text observed=2026-08-01T15:02:39.195033Z digest=sha256:14dbc1c251995ada501bacde2a7cde04767a7a801afb25cc053500a9bf7f81a0

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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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:def2183addf47a6ee41d4708a6840512029f2c642498cff5f9ea1970c8c6c1d6

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

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source=pdf_text observed=2026-08-01T15:02:39.555595Z digest=sha256:6027a50aa5bfe6288cc11cdb61f08104458d158226cc2015c0d58a1e0a59dd42

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=sha256:59b3a1ea00547297cb244ee06bde5c97294819776ce8302c7a795c9af94eca36

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=sha256:6d6fb031300e8623422d962a1279fe262aff46b992fd297d8aeba70b5bae9b93

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=sha256:7ef33e8e709e12373ade010e4c684d85010e793bfa9c50fdac30e5d798c7aab3

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=sha256:5f175035f7d3fc009c32af9114c425e3ecb5e8b9569686d7557430a56aa421a9

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=sha256:1e86610c2930c91ceec6f437191108b35cfa99cc94b0f6b7c0d516d28076af6f

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=sha256:0b9afe18d1ab9db3f0f61a30bc5d9253023fb2ada8367fb36efb2f04a1e91fb7

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=sha256:41204c05c015b8589e16e7d4e36969e1d3429d528133644da0f2354670af9cf6

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=sha256:05e3fa71a7706473c726ebaa76160c0c14b6a69a8ddea4a840f0a61461e1e289

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=sha256:188f24c39ee4b0f9384fd5323f6ae14561a783d4b98760ab50bc79fda4b9c97f

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=sha256:379fd76dcbf2ef299131a52bb85ca7bf99bc32bfc34deceff94d564053e8f825

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

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source=pdf_text observed=2026-08-01T15:02:40.409897Z digest=sha256:89de00915599744cfad2bf676169155e2f84f4a64f92a81f7eaff8c9a2c129ae

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=sha256:2d5f39f117f7181c3fe7006e02861dad9c2c0b453f85030d1fd93db4a9180387

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=sha256:660074e8d59005357900889e8ca1c7c7fc57652fd6163ca1eb7b01f6e0287aa1

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:f9f7b152b20bd24c8f213c84e0e929781baf23c9a4e2e5eb576f5ed13f7535ee

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:a52b501265b5947aaeefc736a8b491f3609f8d91152260387efcb6c9d4ca24e3

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=sha256:25a27a8c29be2f222b841feb00aade4536abc2d95c8b7c9dac40eba49179e99d

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=sha256:72efc5c2f28a75817acc8c2b3eea3bd47630f29541bcb550a92de1a80ecd80f5

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

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source=pdf_text observed=2026-08-01T15:02:40.963041Z digest=sha256:a6aeb9ba2b96f4d5ce553c75bc4736fae01b65f32ff2018bba2fa7425b91e9ab

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

This paper cites content":.

SciDataSailor: Deep Scientific Data Exploring content":

Reference 58

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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:eb4521ea42729bf4ad6b265a4c73e6512fb65aff40fff3042984acdeb92f2267

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=sha256:0945b1ac10f744fae46648cc75f9f5dd182a310597173874fa415864777c819d

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=sha256:259d75125ac4bd3e23afcc8523749389782c5bbb0e1e99ae769b4aa4b2125ad9

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:e693af303614a3192ce66a51a42a1ef2cde3b9e55d73347402714335ce259242

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

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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=sha256:62a771ffc27b38606d00bb791077d748002fb7f9fafcb2d7a19f57193585f893

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

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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:a0db50c76b46eebd965efcd7e20af41c527248cf1d582aa8f35e8da914135b83

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

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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=sha256:23238bb3f8a8b147436d516bfb794e524091d6c82a61abcb16c6160aaacbb414

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=sha256:3c0211e19fe5685633356b06362379e809db44e14aae5550f8334c5e9679214c

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=sha256:9261fe3ca74e9592a285191b37d41925af85b5a50e2476e20fdfb9cf4d58a54c

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=sha256:701856ad1b1bffd5e83b0a331eaec3b7abd63da256f021015c522e765462e5f2

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

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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=sha256:741df86e623a6172268c74e66648e1073e3a8d6e92a6940393f5b70ab5a655dd

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=sha256:6db02c235d78edbb4201c06b75b19c200f55827cb798623a016a9c8624622f8c

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

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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=sha256:61bd52159b83d2bc49460fecd73101ae446118b25ce21d27823b8585973bc9e5

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:dc0849d1fb86d4a7ac15bb3ebc186a183700be16335739a1eb8d5c2fe9088a3a

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

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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=sha256:4f4cffbb06692f3eded63257a20decbabc979fc7c6104fd4af8d015af987168b

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

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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=sha256:8e395a4998747b521b5cc6c0bab36af237aa0cdac36d4e1ebd10c847c0334118

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

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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=sha256:84d7126acb9bff45741d522c01c220ef3413caccc57a9fd8b8a42e10d0d4e951

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=sha256:206d55efa6fdc6c021466b0894ee3fe61260f51b7f4336245187d21885bbb41f

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T15:02:42.604007Z digest=sha256:d0f088283be82cc8afd89b590151fdcf7e99bdb6522b1fb99d64a3b6327d9a9f

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

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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=sha256:1154c16570b1ac641e99f7572eca5a6dd073ca46004b01cabb163427d93e3959

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

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source=pdf_text observed=2026-08-04T03:20:50.048642Z digest=sha256:d1c5ca7b167dc62604e9ab3d8111c729ecc156fe15bd524a041f31b0af4fb936