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Paper Citation Record · LEDGER

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents

As of 7 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2511.00802.

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

pith.paper-citation-record.v1
2511.00802 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T00:30:42.751522Z

measured 39 of 39 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 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

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved39
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70231c84-37df-4e64-b3fb-8bad45e78c76 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 1

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no resolver link, observed 2026-08-04T00:30:37.891373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:37.891373Z digest=sha256:05b1c69f877e1faa690dce1d42c087d0f8b50ce1857009c81722daf8ae7229ad

Observation 5747f842-69ac-4758-bf2a-329578ac5405 · outbound

This paper cites Program Synthesis with Large Language Models.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Program Synthesis with Large Language Models

Reference 2

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source=pdf_text observed=2026-08-04T00:30:38.025346Z digest=sha256:e890e87157b575d0ec600747a6844319e3ff59bf271bb79ab7f7245c6397be96

Observation d0929453-0725-4f45-97af-0e5499f6c402 · outbound

This paper cites Never Give Up: Learning Directed Exploration Strategies.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Never Give Up: Learning Directed Exploration Strategies

Reference 3

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:38.113645Z digest=sha256:942b1ac8fead1bddff32a8fe7c9e4bf62b353590850d84805d4ecc87c006351f

Observation 414fb8ab-1696-4d62-97fa-ceff306e0829 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 4

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:38.222761Z digest=sha256:7a28ae7b345bb92293cb3f64a39f9f2a0dfbe3cb2c88bb1db2e79ded853f3a02

Observation 626cc5ce-a372-4ce3-b23f-9b052cccf386 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 5

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source=pdf_text observed=2026-08-04T00:30:38.324453Z digest=sha256:dde41354be58456b3cecda57708c958a4d14b3c31802f39ac5bdac3d292424ea

Observation d9bf3ec2-fbf0-4651-ae79-ad3fa87a46f7 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:38.465167Z digest=sha256:d05fef15535852c87abacbadf45b9c6ffab9a602d783230aa80d0156bff0dc08

Observation bcfa4aad-4bb1-4926-a85d-54ac012cb722 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Evaluating Large Language Models Trained on Code

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:38.619646Z digest=sha256:18af34e47aaeb9cef80cb7a12b414ee97beaa8c7d127f75e11e28b3837d11e7e

Observation 06bbab86-ce7f-4452-bb52-1c7967754f44 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-04T00:30:38.821160Z digest=sha256:40230fcd9fb3c3f2cbc6465843c4640cad52c2892014ff708cbef3fb924646eb

Observation a0528a24-8811-41d9-a073-4e4d45366ec7 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 9

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source=pdf_text observed=2026-08-04T00:30:38.991538Z digest=sha256:6c8ac6cfa1bf6a6cb59bbe56bdc8cb7c1c49375343d75efe7b6d0b21d15b8b6f

Observation c11a8765-583a-4c1b-b023-2ba0dd4edc54 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 10

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source=pdf_text observed=2026-08-04T00:30:39.129248Z digest=sha256:05d23d7d5b24be242d03935b3184621945e7819bc29e361c014084862527811d

Observation 4241ee22-d3f3-4092-b22e-7416d9127eda · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 11

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source=pdf_text observed=2026-08-04T00:30:39.300674Z digest=sha256:913516d5d38fcc6ef6990231f3b97900e4db1d5134a93e1c4904d326be3e0f1c

Observation 7f1bf5b1-076c-47ba-b818-0ac6adc166ec · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-04T00:30:39.491529Z digest=sha256:7cbbdf8fc8bfbfb9f6928ba4d5ebcc5d97fdfafb843528cd4efb8ace44859d9f

Observation 50c2ab46-44d4-45cb-91df-da9e9761d085 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 13

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source=pdf_text observed=2026-08-04T00:30:39.621961Z digest=sha256:1e854992bb58ebfead715f4e5830462cc703721864a5fc352de8f27d54cd06f2

Observation 97d766ee-0e8c-4e3d-99f4-56a1747273c2 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:39.792993Z digest=sha256:1101ebd6c58a20f4dfd411d2650a8d4a3b05999fdb3c9993460271e1dc6d69c3

Observation 4c065214-9835-4c31-b0d8-53d82709a5b5 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:39.980233Z digest=sha256:60f4057578bc5dcb58e4dce472ffe278dac6b2735f7abcfa963bdfb1218366ce

Observation 04e9f87e-b93f-4a7f-b592-cc28b738610b · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 16

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source=pdf_text observed=2026-08-04T00:30:40.162273Z digest=sha256:aceb1f9933124b9b63205d506069e37befd4afa96ade9e7608e35d181f1e3e30

Observation 3a9dfbad-3d5c-4c91-86a8-6fbe11742e78 · outbound

This paper cites How Effective are Large Language Models in Generating Software Specifications?.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents How Effective are Large Language Models in Generating Software Specifications?

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:40.301164Z digest=sha256:b2d963dbdd1a36aa05e66ce14c2b0b6ef1f2b8f99d597cb4ac595404fa711cf0

Observation 3bac3897-a42f-4e72-91d5-57bf21784367 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 18

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:40.432408Z digest=sha256:1c2902cf02151da02af37d15a59e60d37fa0e2696ed63550ce20be65cfd9b119

Observation 4967cf59-4a28-4558-9941-94123a3fa61f · outbound

This paper cites SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation

Reference 19

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source=pdf_text observed=2026-08-04T00:30:40.618251Z digest=sha256:01de2ada8310c6d8c72e7bd33bb122d58c6f860385fff62dccbf122614e866a5

Observation 9979a6ff-0f27-48e9-8c34-df3f628233c3 · outbound

This paper cites 2020.Trustworthy online controlled experiments: A practical guide to a/b testing.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents 2020.Trustworthy online controlled experiments: A practical guide to a/b testing

Reference 20

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:40.788999Z digest=sha256:8fe2663bd36bf0dfe06a31dd9bc92a53f219ed60c1fd893345333355ba7251b2

Observation 1704cd98-4b45-4483-a347-ec602e689fd1 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 21

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source=pdf_text observed=2026-08-04T00:30:40.877999Z digest=sha256:eb730407990d72c775bac803e4d926aae00665015f674e6942d78df3daec1595

Observation b42d5b78-5e46-41d5-a060-6f9ad7657bb0 · outbound

This paper cites RAPGen: An Approach for Fixing Code Inefficiencies in Zero-Shot.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents RAPGen: An Approach for Fixing Code Inefficiencies in Zero-Shot

Reference 22

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source=pdf_text observed=2026-08-04T00:30:40.984672Z digest=sha256:08e0477195680e3faa9b0bc53af00eef06a369cb2ee65966a383d5a912bae51e

Observation 4088c6a1-3169-4adb-aaaf-8b1aa0beda0b · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.105537Z digest=sha256:4708eb764aa21bc1b9d40413f069fbeec6a1d61871698edd69ff08334b31c780

Observation 2ee537c8-2e0e-4168-8ecb-674668b993a6 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-04T00:30:41.210172Z digest=sha256:52c0071f7d06d582f27842dabf16628de9a773496976ac5d2d504efffee70edb

Observation 33beb4b8-eb0c-4abc-89c0-6f52516c4833 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 25

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source=pdf_text observed=2026-08-04T00:30:41.342531Z digest=sha256:f6b3fd52478d4055329ad52b54c6668b432d8d9b87e67d3c925b24ae0096c099

Observation 48b08b01-d849-4060-aa5e-92c330ce0668 · outbound

This paper cites Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.466085Z digest=sha256:592c2fb1a5b0e0ffce9f5d34f3583712b00c3daa6a72fbee9e619cb47704e099

Observation 6965ce0c-b5ef-4115-9026-3321ca29bbf9 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 27

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source=pdf_text observed=2026-08-04T00:30:41.546154Z digest=sha256:2d0620d2ed8dfb9eeabaf903f95e23aa25eba2222ab7883de72f5b5a0088e4eb

Observation 557ef91f-ecba-4fcc-9186-411961897337 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-04T00:30:41.674958Z digest=sha256:88f5113c3d05d9a73a2ce576382c5ce4954e717672fb4a9e2d1641007d72a90e

Observation 5557b768-d6b3-4a6b-8d75-43362034afbc · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 29

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source=pdf_text observed=2026-08-04T00:30:41.762114Z digest=sha256:4578705ef0aba7b278708c3b036f498d01b69cef474e0d5542b43b5cd7c38ac7

Observation a16c939b-bb9b-4a0c-b73d-e7a4d317a144 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 30

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source=pdf_text observed=2026-08-04T00:30:41.772882Z digest=sha256:11a3154a5d63cdc42eb8c3b6501484d72ccf23bb48f9e116fbeb4e0071d80ab6

Observation 90299fa1-b76e-48b7-bc0b-5c202c8148f9 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 31

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.865812Z digest=sha256:faa6e11b39a626e3c9a76d31bfd46f63dd9b71231954390bf15a033c1340b462

Observation da94cf37-8f8e-4aee-9433-17f0d29addaa · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.987578Z digest=sha256:de51fb5750edf16b9bd5f33ee61009b983053e384b3bcbf25a731297f41ad697

Observation fcb417b0-945c-4f23-a185-22671bba7419 · outbound

This paper cites A Review of Off-Policy Evaluation in Reinforcement Learning.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents A Review of Off-Policy Evaluation in Reinforcement Learning

Reference 33

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source=pdf_text observed=2026-08-04T00:30:42.106294Z digest=sha256:16fff41084fb228200d636aefbbabf23abf0802dfa931f9d5b20426d6e8b137b

Observation 4e540948-308f-4fb1-aded-0ff8aadd45aa · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.201322Z digest=sha256:2cf3d276b9b46655b3ad975c29f455dd665a216675cf7ca5971d50ebf95df877

Observation c5817083-e42e-431b-8158-0c4f51e649ee · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 35

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.237186Z digest=sha256:8eace523692ca7e6b61081a079eef5bbaee62a8b41bd3e0daed2bb5c4beb33da

Observation 3178c37c-46fb-49de-a895-a14fdec12075 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.330454Z digest=sha256:4e976649abc18c3ebbd8477a3d9ebbddfcf9fa604e7c86b3db83fa4b9d99add4

Observation 9954aec3-8bd2-472e-8888-7f0afed41f82 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 37

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no resolver link, observed 2026-08-04T00:30:42.438177Z

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source=pdf_text observed=2026-08-04T00:30:42.438177Z digest=sha256:0648f23fdbd14f783821fb6d29c50acd279efeafe866d3cf29cd17bb85aa0945

Observation 713e1c19-5162-4849-95eb-c1221ed71520 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.585562Z digest=sha256:9253dcae91a615d10df86865068ec496516af5c28c9b1cf8ab3982da5247c3de

Observation 3cb9d77d-11dd-4039-976c-d8942339e669 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 39

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no resolver link, observed 2026-08-04T00:30:42.751522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.751522Z digest=sha256:02e096e23a00c59ffe6726160d78e19ac963a754b96337518dfe337753f65c86

Pith citing papers

No inbound Pith citation observations are available.