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Paper Citation Record · LEDGER

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing

As of 23 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2608.07437.

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

pith.paper-citation-record.v1
2608.07437 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:39:03.692877Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

  • verified exact0
  • verified fuzzy21
  • unresolved39
  • parse uncertain1
  • malformed identifier0
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External citation measurements

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Outbound references

Observation 02ee2bb2-7fe8-4c06-b2ee-ce4641c13f46 · outbound

This paper cites Stability analysis of fluid flows using Lagrangian Perturbation Theory (LPT): application to the plane Couette flow.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Stability analysis of fluid flows using Lagrangian Perturbation Theory (LPT): application to the plane Couette flow

Reference 1

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Observation f153cbbe-5435-4fe6-bc70-a6848ac07d3b · outbound

This paper cites Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow

Reference 2

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source=pdf_text observed=2026-08-10T04:39:03.405648Z digest=sha256:885e7e731c57a49162b2b7b34f3010aa8a4038816c2d1c340b27d416023cebeb

Observation 0d367f4e-3feb-4514-9909-6a82962ea663 · outbound

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

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Deepanalyze: Agentic large language models for autonomous data science.arXiv preprint arXiv:2510.16872, 2025

Reference 3

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source=pdf_text observed=2026-08-10T04:39:03.410767Z digest=sha256:0ef52e1c8c02af17e4868cba34e5f3255c601389b140668e00d477258964a8eb

Observation bb3088c0-b3fa-4f21-b3ac-6010955f896f · outbound

This paper cites Data interpreter: An llm agent for data science.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Data interpreter: An llm agent for data science

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.415655Z digest=sha256:bcc6fb111e8aff6be66ea693331b9ca55bf77781c33db0f839caf3766b62c382

Observation 3688e365-d990-471c-8239-cf1a285070ff · outbound

This paper cites Infiagent-dabench: Evaluating agents on data analysis tasks,.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Infiagent-dabench: Evaluating agents on data analysis tasks,

Reference 5

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.420634Z digest=sha256:b92289d11b7d32057f35e227c81153f6df4508df1b9b62764d2f0b6714c7c450

Observation 644faab7-ad14-4c37-b046-38a7b75ab743 · outbound

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

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing DABstep: Data Agent Benchmark for Multi-step Reasoning

Reference 6

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source=pdf_text observed=2026-08-10T04:39:03.430946Z digest=sha256:b4e4aecf724e353ec64f1bcc819b154a8f6bfc90d6b73b890ba5ee4a93d2687a

Observation d847d5b0-9d18-44da-930c-7c95e024f0b1 · outbound

This paper cites DA-code: Agent data science code gen- eration benchmark for large language models.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing DA-code: Agent data science code gen- eration benchmark for large language models

Reference 7

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source=pdf_text observed=2026-08-10T04:39:03.436223Z digest=sha256:44909162ef282ddcc374335cc1d879cc8039ee4cd7f917e6a29941ac5785b4f9

Observation 0a10aadc-bd13-43fb-ab13-3168d2574294 · outbound

This paper cites Are large language models good statisticians?Advances in Neural Information Processing Systems, 37:62697–62731, 2024.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Are large language models good statisticians?Advances in Neural Information Processing Systems, 37:62697–62731, 2024

Reference 8

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source=pdf_text observed=2026-08-10T04:39:03.441812Z digest=sha256:8a758d5776a31c8bf838a6c22622112adf50b5e6ec7b154adc0a1ce14da6e781

Observation 9ff204ad-749c-48ef-a97b-da696b13364a · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing ReAct: Synergizing Reasoning and Acting in Language Models

Reference 9

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source=pdf_text observed=2026-08-10T04:39:03.446928Z digest=sha256:8e3af96e5013ac1c03d201d80dfa401025614705cbede14757bd59766add6b8f

Observation 4ebded3c-7ce2-497e-a8ad-eeff6bf9b079 · outbound

This paper cites Ds-1000: A natural and reliable benchmark for 12 data science code generation.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Ds-1000: A natural and reliable benchmark for 12 data science code generation

Reference 10

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source=pdf_text observed=2026-08-10T04:39:03.452234Z digest=sha256:f33b91fd6451c7a79a2f0b3c823cbb2b1076ee923794bccd0192e8c730131d61

Observation c9f45c4b-e365-44ce-94b6-d9d21dcce73d · outbound

This paper cites InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks

Reference 11

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source=pdf_text observed=2026-08-10T04:39:03.457120Z digest=sha256:6ee3afc711ccd3390f49fc8d665841adcb64f145f836aeeb9e3a9203ea2cded8

Observation b7b4fe64-9111-4aac-8e71-5a507dd9ac22 · outbound

This paper cites DataSciBench: An LLM Agent Benchmark for Data Science.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing DataSciBench: An LLM Agent Benchmark for Data Science

Reference 12

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source=pdf_text observed=2026-08-10T04:39:03.461634Z digest=sha256:f468cab1059ec4a523fb88356356c7c31189e41d9a9d22e0d518a765d23f79bd

Observation c1557f8b-cbf6-4f32-a05c-31576141a4ab · outbound

This paper cites MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 13

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source=pdf_text observed=2026-08-10T04:39:03.466801Z digest=sha256:4eabf6da71a147f6938be790f5b4abfcbcdc57537b0d4d25e58dcd90c5f96ee9

Observation 9a176489-9d48-4993-bd21-04ab319deee1 · outbound

This paper cites Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents

Reference 14

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source=pdf_text observed=2026-08-10T04:39:03.471639Z digest=sha256:4dfb657875f635d1bb65e482cdeca419ff20d23e57628ee6eb04871c56816eef

Observation 8837324d-564e-4c35-8c3a-42f6175dc1af · outbound

This paper cites IDA-Bench: Evaluating LLMs on Interactive Guided Data Analysis.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing IDA-Bench: Evaluating LLMs on Interactive Guided Data Analysis

Reference 15

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source=pdf_text observed=2026-08-10T04:39:03.476630Z digest=sha256:4b61c3a049a75969258e1335a44dd19d90880c50fa902226893aa13c70d618c4

Observation 30637093-fa4e-4b87-9771-5515245c4045 · outbound

This paper cites Fact or fiction: Verifying scientific claims.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Fact or fiction: Verifying scientific claims

Reference 16

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source=pdf_text observed=2026-08-10T04:39:03.481558Z digest=sha256:6e48ce960c14561741264c705d0e46dc29d06212280ce53cf0ecf23cb4c453d0

Observation d8348684-9385-4de9-a54d-6444071f1631 · outbound

This paper cites Sciclaimhunt: A large dataset for evidence-based scientific claim verification.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Sciclaimhunt: A large dataset for evidence-based scientific claim verification

Reference 17

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source=pdf_text observed=2026-08-10T04:39:03.486856Z digest=sha256:66e464ce0bfd126fad62c0dc0c7f94af5ae9b5a9e0572db807144365177ad0fe

Observation 967c7018-a6b1-49aa-9c25-6282fef5ebaf · outbound

This paper cites Musciclaims: Multimodal scientific claim verifi- cation.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Musciclaims: Multimodal scientific claim verifi- cation

Reference 18

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source=pdf_text observed=2026-08-10T04:39:03.491749Z digest=sha256:1345b50b06b4beadd8b23d4dc32b5b8556bc0e82943ec24a8859296fc86fda50

Observation 75554491-30c5-42cb-bed5-39805595e3d7 · outbound

This paper cites Investi- gating the reproducibility of the social and behavioural sciences.Nature, 652(8108):126–134, 2026.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Investi- gating the reproducibility of the social and behavioural sciences.Nature, 652(8108):126–134, 2026

Reference 19

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source=pdf_text observed=2026-08-10T04:39:03.496445Z digest=sha256:0d2b3d9bf4e02d4f29dc81c11c7dbf9c2cc971813436ccebb42bf6771602fbaa

Observation 2e9418d9-cd96-49f7-b8f7-bbdd9163863e · outbound

This paper cites Towards end-to-end automation of ai research.Nature, 651(8107):914–919, 2026.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Towards end-to-end automation of ai research.Nature, 651(8107):914–919, 2026

Reference 20

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source=pdf_text observed=2026-08-10T04:39:03.500807Z digest=sha256:7b673caa5a1080420f54fc1e8148228f87ef80a4c38abacb4bf17bad7972aa3f

Observation bb557469-8e70-4498-822e-5276a4c060ee · outbound

This paper cites AI-Researcher: Autonomous Scientific Innovation.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing AI-Researcher: Autonomous Scientific Innovation

Reference 21

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source=pdf_text observed=2026-08-10T04:39:03.505323Z digest=sha256:db182622040660f11caf9c1f8670b9423a7514f329cf2367bef48640678dbbe4

Observation 2e96c553-6fcf-4e65-aa12-39d281943fde · outbound

This paper cites The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

Reference 22

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source=pdf_text observed=2026-08-10T04:39:03.509944Z digest=sha256:27f6f88a848264b62276c5662459b3521c25e58090b657f469ec87d1635d21c4

Observation 7097c805-7d63-451c-8122-a5b98befa13a · outbound

This paper cites Development economics field experiments (dfeep).

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Development economics field experiments (dfeep)

Reference 23

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source=pdf_text observed=2026-08-10T04:39:03.514880Z digest=sha256:2506e7d5e60db205d05259f3439a2d32035c36d08e7fa905284f650f9075dfa0

Observation 7af7ec38-d793-45e9-ade6-72a95d998e44 · outbound

This paper cites The cbio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.Cancer discovery, 2(5):401–404, 2012.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing The cbio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.Cancer discovery, 2(5):401–404, 2012

Reference 24

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source=pdf_text observed=2026-08-10T04:39:03.519472Z digest=sha256:3f99e05fb7ee82bae7662ef7948f90b07ea55af0828df164ece52211c30858b4

Observation ba341f71-2d39-4448-8fd2-9d69c49fc373 · outbound

This paper cites Integrative analysis of complex cancer genomics and clinical profiles using the cbioportal.Science signal- ing, 6(269):pl1–pl1, 2013.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Integrative analysis of complex cancer genomics and clinical profiles using the cbioportal.Science signal- ing, 6(269):pl1–pl1, 2013

Reference 25

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source=pdf_text observed=2026-08-10T04:39:03.524397Z digest=sha256:f4eebcaf80c7873b0809759537d6532737b3bad8a2e7b5b9f8eabad7f1543257

Observation 5b5ffc14-a414-42a7-b78d-11cf301e6476 · outbound

This paper cites BioDSA-1K: Benchmarking Data Science Agents for Biomedical Research.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing BioDSA-1K: Benchmarking Data Science Agents for Biomedical Research

Reference 26

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source=pdf_text observed=2026-08-10T04:39:03.528813Z digest=sha256:032507cfd2eed82d5a7441fcd165f8df3667987a1b6260c1b13f58feb205a8cd

Observation 06e28d36-989a-43de-885b-022acebdf441 · outbound

This paper cites an unresolved cited work.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Unresolved cited work

Reference 27

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source=pdf_text observed=2026-08-10T04:39:03.533331Z digest=sha256:8cfaf1cbd1fad6a57198f84afa9418d694dea07e4066b81beb7190dc39a8a005

Observation 3509a304-b336-450a-a2e1-85062991a107 · outbound

This paper cites Introducing claude sonnet 4.6.https://www.anthropic.com/news/ claude-sonnet-4-6, February 2026.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Introducing claude sonnet 4.6.https://www.anthropic.com/news/ claude-sonnet-4-6, February 2026

Reference 28

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source=pdf_text observed=2026-08-10T04:39:03.537708Z digest=sha256:2dc1576ba85e8a64ef54bbca0554c906a645124a48ff7e3455ce781dee0b79bd

Observation d71be0a8-203a-4c60-a02d-d6a67a1c3ce9 · outbound

This paper cites Executable code actions elicit better llm agents.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Executable code actions elicit better llm agents

Reference 29

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source=pdf_text observed=2026-08-10T04:39:03.542160Z digest=sha256:c288afd82d563629bba5e527906df0edc53b6be31aea29ce43596904f9ada3f4

Observation 50d4aaaa-401c-49ae-be49-6e26115c50f2 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 30

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source=pdf_text observed=2026-08-10T04:39:03.546532Z digest=sha256:277383e654fae99be583d5cc7bd16406a63dfe85953cebd7dc9954fb3b890836

Observation da19215c-905d-4a00-b296-589b5f48acdf · outbound

This paper cites Qwen2.5-Coder Technical Report.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Qwen2.5-Coder Technical Report

Reference 31

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source=pdf_text observed=2026-08-10T04:39:03.550965Z digest=sha256:88819749b137d2a6f034c0e8767ea52da7f9d815136e80e7feab837197dec302

Observation 26ec706c-2bf8-4b48-8181-2fbbf363f3cb · outbound

This paper cites Introducing gpt-5.4.https://openai.com/index/introducing-gpt-5-4/, March.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Introducing gpt-5.4.https://openai.com/index/introducing-gpt-5-4/, March

Reference 32

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source=pdf_text observed=2026-08-10T04:39:03.555768Z digest=sha256:8cd56138d264aafbf77fae6a534012cbabf95c2dc55aebab5fa57277cc4ab93a

Observation 71e73ab9-e116-4aed-86a6-0400ae6b77c6 · outbound

This paper cites Deepseek-v4: Towards highly efficient million-token context intelligence.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Deepseek-v4: Towards highly efficient million-token context intelligence

Reference 33

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.564690Z digest=sha256:decd4375b01ae288a6bd80dc3bed0df29e78b9b287b0f60a77e93d052ca27dab

Observation 8c37b627-0242-4fa6-a6dc-129a9b438cbd · outbound

This paper cites Introducing gpt-oss.https://openai.com/index/introducing-gpt-oss/, 2025.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Introducing gpt-oss.https://openai.com/index/introducing-gpt-oss/, 2025

Reference 34

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.569100Z digest=sha256:a958915db80145ebd3075369378728f979270eb5a54df3cb13aeb1633661e6a9

Observation 6402fc39-cc60-48fe-9bb9-27fbc343b7b8 · outbound

This paper cites Qwen3-coder-30b-a3b-instruct.https://huggingface.co/Qwen/ Qwen3-Coder-30B-A3B-Instruct, 2025.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Qwen3-coder-30b-a3b-instruct.https://huggingface.co/Qwen/ Qwen3-Coder-30B-A3B-Instruct, 2025

Reference 35

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raw_fallback, observed 2026-08-10T04:39:04.480535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.573317Z digest=sha256:73a9847457ce213f17b867dbf9eac524b60fd0c97c7b48f194302f90454c8bdb

Observation df0caddc-0ea6-49f8-8c9c-80b35a7704a1 · outbound

This paper cites Qwen3 Technical Report.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Qwen3 Technical Report

Reference 36

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no resolver link, observed 2026-08-10T04:39:03.577579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.577579Z digest=sha256:45088bda68da168cbb4bae75f4dc416074e6cc98e534fe92848d4dfbeb7ba782

Observation 38312006-f686-462e-ae24-0e77b00ab9de · outbound

This paper cites Scaling generalist data- analytic agents, 2026.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Scaling generalist data- analytic agents, 2026

Reference 37

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no resolver link, observed 2026-08-10T04:39:03.582193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.582193Z digest=sha256:c14e03120b3f6172995da6178b01cfad67689ee0cccf4641b9f94094a32973f0

Observation c8b03bf1-d1ee-4461-a21f-d5d7b661b266 · outbound

This paper cites Accessed: 2026-05-06.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Accessed: 2026-05-06

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-10T04:39:04.465596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.586686Z digest=sha256:87b2dff4b79271ef1a38a6e693eb19d61760e195304d726d48c082869889ad0f

Observation e7de4fcd-e169-406b-91ea-3254483e4b57 · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Self-Refine: Iterative Refinement with Self-Feedback

Reference 39

Resolution
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no resolver link, observed 2026-08-10T04:39:03.591340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.591340Z digest=sha256:575017752e47e24fc6106a8737bbeef4a5d76abc0383ec73921955d2584dc25b

Observation c44e2879-0050-436a-96b8-0081c40c9409 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.Advances in neural informa- tion processing systems, 36:8634–8652, 2023.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Reflexion: Language agents with verbal reinforcement learning.Advances in neural informa- tion processing systems, 36:8634–8652, 2023

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:39:04.450651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.596337Z digest=sha256:8e90407fe354b5426e1f0a2c37c8ae8a3c93a609236948a3e4e8a82d081c701b

Observation d7ab10fe-dee9-4e4b-be02-276bb43b150b · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 41

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no resolver link, observed 2026-08-10T04:39:03.600566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.600566Z digest=sha256:6b3414d23570e7afc6a18d330dfdb46428a4dbd800d90d3f4d52e5d59411bdd6

Observation c65ef131-db0a-42f3-ae75-2e46db8a5d69 · outbound

This paper cites Swe-agent: Agent-computer interfaces enable automated soft- ware engineering.Advances in Neural Information Processing Systems, 37:50528–50652, 2024.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Swe-agent: Agent-computer interfaces enable automated soft- ware engineering.Advances in Neural Information Processing Systems, 37:50528–50652, 2024

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-10T04:39:04.434898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.605328Z digest=sha256:5c3d9fe61c03cd6668684f480b07e1ce8de0eba38e0297d7fd2878b713c2c77e

Observation 000e14c4-7303-4d23-bcd9-1596e22aecd7 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Proximal Policy Optimization Algorithms

Reference 43

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no resolver link, observed 2026-08-10T04:39:03.609725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.609725Z digest=sha256:203b4925992a26fdf5cf7ccdff17f5ae7fcfe571d72d648343a570cecbcef53e

Observation c488ede0-f512-4ae6-9050-0a36aa648941 · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T04:39:03.614383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.614383Z digest=sha256:4c141640533d4be6f43ccfc6c3d5d431aee00aafaffcbfaaa31fdf3bf517e1b8

Observation aaa26ca6-40be-4162-acf0-908c80fce4d3 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.Advances in neural information processing systems, 36:53728–53741, 2023.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Direct preference optimization: Your language model is secretly a reward model.Advances in neural information processing systems, 36:53728–53741, 2023

Reference 45

Resolution
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no resolver link, observed 2026-08-10T04:39:03.618872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.618872Z digest=sha256:68665f40468cd1cf7612a2c982f158b0d8a9bf4b0e8e83841c24ff00d41d69ca

Observation ba795ca9-c6bf-41fb-af74-c838cfb26782 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T04:39:03.623408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.623408Z digest=sha256:6e0a7901be6b3c5f807e280f6fcdccb92ab2799a138ba6b8e68b072ea3e007ea

Observation 53f52013-4298-4d13-9832-06e4463ba865 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T04:39:03.628209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.628209Z digest=sha256:764a21ed1ba25eda27d26babd978bf07b2291e7f5ac97255645f9255e781e8bd

Observation 3c61b79c-030c-42a0-88ff-cbac19d0b4fb · outbound

This paper cites ToRL: Scaling Tool-Integrated RL.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing ToRL: Scaling Tool-Integrated RL

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T04:39:03.633077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.633077Z digest=sha256:d6688cfc75f421e019ea97db7f14056e2c9bd1d833f76cf0cccf388babb7251c

Observation e6ce7ab3-ca53-44a0-960d-951f42109cd4 · outbound

This paper cites ReTool: Reinforcement Learning for Strategic Tool Use in LLMs.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing ReTool: Reinforcement Learning for Strategic Tool Use in LLMs

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-10T04:39:03.637815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.637815Z digest=sha256:354463333f7dd822548b875142889029eb420b5b6ce556bdb512b5541affe551

Observation 3a6b4ba9-845b-4056-be59-28eb4a5da243 · outbound

This paper cites ToolRL: Reward is All Tool Learning Needs.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing ToolRL: Reward is All Tool Learning Needs

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T04:39:03.642514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.642514Z digest=sha256:adce47080b7f80e9482700e345022e082b62574934bcbdcc151d5795c9af864f

Observation ca4ee6f6-5d92-472b-95e6-2c5810b604f1 · outbound

This paper cites Agent-RLVR: Training Software Engineering Agents via Guidance and Environment Rewards.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Agent-RLVR: Training Software Engineering Agents via Guidance and Environment Rewards

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T04:39:03.647525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.647525Z digest=sha256:c89e974c2ab4e753bf4b0fe4ab5bdf1087599fc3f71bea860ecb553f0cd975b5

Observation 65e2fbaa-1e39-42b7-8721-101cae37630c · outbound

This paper cites Effects of cognitive behavioral therapy and cash transfers on older persons living alone in india: a randomized trial.Annals of internal medicine, 176(5):632–641, 2023.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Effects of cognitive behavioral therapy and cash transfers on older persons living alone in india: a randomized trial.Annals of internal medicine, 176(5):632–641, 2023

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:39:04.399794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.652822Z digest=sha256:dfdd57a10cf3870b5fc995ff177584890dad9f5f382679bcd04bcf59e1deb859

Observation 5b30023b-5725-4082-80ba-ac74832d7b4f · outbound

This paper cites Genomic characterization of metastatic patterns from prospective clinical sequenc- ing of 25,000 patients.Cell, 185(3):563–575, 2022.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Genomic characterization of metastatic patterns from prospective clinical sequenc- ing of 25,000 patients.Cell, 185(3):563–575, 2022

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:39:04.384842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.657534Z digest=sha256:fdabdc5e32f5b6059e9662c893a819a98e3c98a4b4e0bd00448f3a55f0333fbf

Observation 5254a881-e8a1-488e-9cd5-2826d602f635 · outbound

This paper cites The support prognostic model: Objective estimates of survival for seriously ill hospitalized adults.Annals of internal medicine, 122(3):191–203, 1995.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing The support prognostic model: Objective estimates of survival for seriously ill hospitalized adults.Annals of internal medicine, 122(3):191–203, 1995

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:39:04.369442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.662098Z digest=sha256:c1834909768a6fd31d84ec6bfe1e5a048c2915dd55c621e6bdf6ab80a7223ec0

Observation f15cf1cd-b341-43da-b393-5e0ccc2186a6 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T04:39:03.667845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.667845Z digest=sha256:dcaefd781336644d4b83bdc23a044a7be0916500adb48993f4f4a6bf2dd981f3

Observation 8c18f6e8-df20-41d5-b0d1-6c30635501c6 · outbound

This paper cites claim”: “drug improves patient outcome.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing claim”: “drug improves patient outcome

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:39:04.353710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.672908Z digest=sha256:324c1ad11539345c4af27ba04011a59e5b4048a559ddf78649444ef2654ae291

Observation adbe0b92-7e51-427f-8525-b05ec970620f · outbound

This paper cites an unresolved cited work.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:39:04.336736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.678589Z digest=sha256:45df7e77d5de82d80a2f7a33891e247562b02537b2947121aa7a7a4af62b1c14

Observation ddf3d3cd-3bf0-42c1-b65d-4b12483816bc · outbound

This paper cites an unresolved cited work.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:39:04.322049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.683802Z digest=sha256:bf5cc810dde2602d1c23d8fca10516d645dcf43c56e35576d67e262bb8bdbc31

Observation 93bd0286-2b0f-47e0-8e6b-13789a89d806 · outbound

This paper cites an unresolved cited work.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:39:04.306832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.688424Z digest=sha256:6fe0d01ce1dfa10ced4fea369f194491248799a28011879ea6701a2922abae03

Observation 507ce3fc-5327-40f6-b266-2abf02d2f7e1 · outbound

This paper cites an unresolved cited work.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Unresolved cited work

Reference 62

Resolution
unresolved
raw_fallback, observed 2026-08-10T04:39:04.290784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T04:39:03.692877Z digest=sha256:6110cb63b0912e6708835c055fad6ac1d1837e92be68b2620d8075e3cefeaeda

Observation 163b0ec8-d481-4081-8989-a5e184270d91 · outbound

This paper cites an unresolved cited work.

Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing Unresolved cited work

Reference 2026

Resolution
parse uncertain
no resolver link, observed 2026-08-10T04:39:03.560376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:39:03.560376Z digest=sha256:292d73a9db97df0a8b5682f43a14e1551181350016dd8b3ecbdd4e34e2224837

Pith citing papers

No inbound Pith citation observations are available.