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Paper Citation Record · LEDGER

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects

As of 17 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2412.06294.

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

pith.paper-citation-record.v1
2412.06294 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:53:24.061379Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T22:21:20.701934Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

  • verified exact1
  • verified fuzzy14
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4d6a108e-059e-48b9-bd4a-3f7295767387 · outbound

This paper cites At- tention is all you need,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects At- tention is all you need,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 7903fd20-f63e-4b47-b279-566acf297b1c · outbound

This paper cites Emergent abilities of large language models,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Emergent abilities of large language models,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:23.956941Z digest=sha256:20d37cfdb5b1e281fe7d4461134fec2957bfade5eba1c5da64dd2536e66d00f6

Observation 1b9e05cd-2f9d-47e3-b63d-9134803fc506 · outbound

This paper cites Lan- guage models are few-shot learners,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Lan- guage models are few-shot learners,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:23.960369Z digest=sha256:cd720663b7a64eafabfe026bf0227fdc6a2005dca5326a9377117826e706a0fd

Observation 562486f0-2c0f-4d9f-b039-4b9ad10252f5 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Evaluating Large Language Models Trained on Code

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:53:23.963905Z digest=sha256:429885941931e6dc6bb794cdcdca9804c868555d24309f28bee435a7214d1fff

Observation f136980b-92db-4751-842f-5a0a8d9d31c3 · outbound

This paper cites Large language models for software engineering: Survey and open problems,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Large language models for software engineering: Survey and open problems,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:23.967556Z digest=sha256:ce221964b2efcdc82eaed7b602a5e97c9bcaed682ae5b77122f1f0fa81fd9205

Observation 263d1779-a13b-4717-8b5b-8893e9f7844c · outbound

This paper cites Fuzz4all: Universal fuzzing with large language models,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Fuzz4all: Universal fuzzing with large language models,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:23.970832Z digest=sha256:67aceffefceadae070105c2a84b2920e1b640b1a4d0d8fbb7a92e069cea76705

Observation b642ecc1-9bae-4d2b-b363-0d1dc88dc7d8 · outbound

This paper cites Codamosa: Escaping coverage plateaus in test generation with pre-trained large language models,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Codamosa: Escaping coverage plateaus in test generation with pre-trained large language models,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:23.977228Z digest=sha256:65b949ea5456b2082e357a9ac146510b44b73288266235400fb2025e86a885b0

Observation ebb7020c-1367-4dac-ae6c-145b2b1dca6d · outbound

This paper cites Less training, more repairing please: revisiting automated program repair via zero-shot learning,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Less training, more repairing please: revisiting automated program repair via zero-shot learning,

Reference 8

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T19:53:23.980689Z digest=sha256:d8607ea219a24c253c2edbda7f455c86803c92ceabc263237ec2df81276a2f10

Observation 4c7e45a5-c0b6-420e-a119-8d8aa9ae1fca · outbound

This paper cites A Comprehensive Overview of Large Language Models.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects A Comprehensive Overview of Large Language Models

Reference 9

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T19:53:23.983838Z digest=sha256:66f1c86ffc7aee0f6e3cf9e13d5201095409985d0a97efb97cf86707dcc32d63

Observation 6eb09d85-e14f-420a-9a9f-a07f8a5f923f · outbound

This paper cites Chain-of- thought prompting elicits reasoning in large language models,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Chain-of- thought prompting elicits reasoning in large language models,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:23.987535Z digest=sha256:e077dd9336913adae489d665e845463302e8a5f36d5b62ebafdc3600b91fcbf7

Observation 412f62ed-d2bc-4840-84ac-088ce956c3f4 · outbound

This paper cites React: Synergizing reasoning and acting in language models,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects React: Synergizing reasoning and acting in language models,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:23.990760Z digest=sha256:d357e475106dc3517788448352c6907c3c7d018701f8897df378a7afe5eef49f

Observation 4fa8babf-f688-4229-9f2c-85af15c6b253 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:53:23.993940Z digest=sha256:ed04d1b6f164ea5330b036467d59a8de0fc92aeec56bd01abf716160bea168f0

Observation 31d7d0e3-4e3c-4d3d-a9ec-37bd1f0564d3 · outbound

This paper cites A quantitative and qualitative evaluation of llm-based explainable fault localization,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects A quantitative and qualitative evaluation of llm-based explainable fault localization,

Reference 13

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:53:23.997545Z digest=sha256:abeb2c32dfe01ab238f9410ba6e738344f6bbcad089048486c113cf071dd586b

Observation 492b184e-6e59-4838-9428-2cab35539757 · outbound

This paper cites Intent-driven mobile gui testing with autonomous large language model agents,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Intent-driven mobile gui testing with autonomous large language model agents,

Reference 14

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raw_fallback, observed 2026-08-11T19:53:24.406652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:24.000589Z digest=sha256:9ba05df74ef4d97280f8cc322f9442cac721ba221aad16a1aca02287695b2c95

Observation ae305dab-1e25-4905-a384-d31b7b278f3b · outbound

This paper cites MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution

Reference 15

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source=pdf_text observed=2026-08-11T19:53:24.003640Z digest=sha256:d3657f71b2ba057777ff2438b13d3c2ee3b98df9cb79d9e89e2ea7932fe92498

Observation 7166b5cb-0d95-4f34-8fbc-398704fecf65 · outbound

This paper cites Code- plan: Repository-level coding using llms and planning,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Code- plan: Repository-level coding using llms and planning,

Reference 16

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raw_fallback, observed 2026-08-11T19:53:24.395312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:24.007120Z digest=sha256:18d33a722dcda80726ba38db49ef6e0d32270713097c665cfa574a8d349af863

Observation 5caf4efd-d339-444c-9c29-4900c2ec5744 · outbound

This paper cites Teaching Code LLMs to Use Autocompletion Tools in Repository-Level Code Generation.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Teaching Code LLMs to Use Autocompletion Tools in Repository-Level Code Generation

Reference 17

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source=pdf_text observed=2026-08-11T19:53:24.010107Z digest=sha256:eb38afaa14a4057be7e3c3f3718dd18c176260cf95a227deba220757e34e0318

Observation 9f70c040-d58c-48fb-b548-ad2bc8ed32a8 · outbound

This paper cites Software documentation: the practitioners’ perspective,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Software documentation: the practitioners’ perspective,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:24.013602Z digest=sha256:a4f7b8ed54a9e627fa24f9bee4fc91257e3d1a0e0fa9fd0cf33fbbe6451ac65c

Observation fa0013e9-6455-4dee-ad3b-dc6b6d4ce850 · outbound

This paper cites Language Models are Few-Shot Learners.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Language Models are Few-Shot Learners

Reference 19

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source=pdf_text observed=2026-08-11T19:53:24.016957Z digest=sha256:ba520b99f054453276ce21decf2d2ed7805478404527e1c0c547e3097e4a6b91

Observation 566b7aac-fadf-4440-844d-bf1ad536e6fe · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 20

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source=pdf_text observed=2026-08-11T19:53:24.020314Z digest=sha256:380d66837b88f4c7d7bdbeacd26847d65580069f2af775874d3815cb65782458

Observation 98232b3f-79ef-45b0-94f1-36c688649523 · outbound

This paper cites Explainable Automated Debugging via Large Language Model-driven Scientific Debugging.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Explainable Automated Debugging via Large Language Model-driven Scientific Debugging

Reference 21

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source=pdf_text observed=2026-08-11T19:53:24.023545Z digest=sha256:0b50b8b2b8614e93e89b0b27f19fad6a03d0dd508af776c1ee026530d5a2da8f

Observation cabc6483-5da3-4188-b080-cf2494e6b74b · outbound

This paper cites Amati, BM25.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Amati, BM25

Reference 22

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source=pdf_text observed=2026-08-11T19:53:24.026777Z digest=sha256:f7d538916f408f0ac65028d8a4268dcbb99cf1fb2d651cfab873ff71f914a6d8

Observation 1baf589b-0d76-4e77-aff9-75cb540383ab · outbound

This paper cites Neural Models for Information Retrieval.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Neural Models for Information Retrieval

Reference 23

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source=pdf_text observed=2026-08-11T19:53:24.029845Z digest=sha256:6b5ed959d930dbc9c1678b003dec51f4e4eddd430cd024c8c4de3bbdfec62d2c

Observation 2bb93993-b18e-45b7-ae78-47407abe09db · outbound

This paper cites RepairAgent: An Autonomous, LLM-Based Agent for Program Repair.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects RepairAgent: An Autonomous, LLM-Based Agent for Program Repair

Reference 24

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source=pdf_text observed=2026-08-11T19:53:24.033136Z digest=sha256:90bd289f6b15317f96eaea0201e13da77900f209b89ad54569ed4fa296fc919d

Observation 8044b6b7-5b7b-477b-873b-b316433bb62b · outbound

This paper cites Lost in the middle: How language models use long contexts,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Lost in the middle: How language models use long contexts,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 42ad0505-52aa-4c9f-8d2c-d3fd45035a2f · outbound

This paper cites Can GPT-4 Replicate Empirical Software Engineering Research?.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Can GPT-4 Replicate Empirical Software Engineering Research?

Reference 26

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local_arxiv, observed 2026-08-11T19:53:24.138277Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 898ba6c5-1c9e-4424-97d1-90045f3ba361 · outbound

This paper cites Long-context LLMs Struggle with Long In-context Learning.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Long-context LLMs Struggle with Long In-context Learning

Reference 27

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source=pdf_text observed=2026-08-11T19:53:24.042744Z digest=sha256:a7ff1238c53b9696874a96c62bbedf213dc35397815860ff6eec63afdf3735ed

Observation 46a9a2be-86eb-4fed-abf5-168da3d1178c · outbound

This paper cites Thread of Thought Unraveling Chaotic Contexts.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Thread of Thought Unraveling Chaotic Contexts

Reference 28

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source=pdf_text observed=2026-08-11T19:53:24.046026Z digest=sha256:b1cd3cb58eed4deef5e1ecefeca092361b5eef3d93cbbae574d1e8c650b09dc1

Observation d49e24e2-e62c-47ef-9d08-523c4792930d · outbound

This paper cites OpenHands: An Open Platform for AI Software Developers as Generalist Agents.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects OpenHands: An Open Platform for AI Software Developers as Generalist Agents

Reference 29

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source=pdf_text observed=2026-08-11T19:53:24.049152Z digest=sha256:37eb093ce6f8535b8981e07d7685e2b2ac6d58eb7009db840d0f3fc9bcaa46fd

Observation 58dffb17-ac53-4cf2-bdd1-c351ff8188e0 · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 30

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source=pdf_text observed=2026-08-11T19:53:24.052330Z digest=sha256:3c671ed495b7d612361069a71c5125ccf98e897f41e870a69f7928bb9356a6db

Observation c14657c1-09cd-4f12-a3a6-2333a0aaaad3 · outbound

This paper cites Automated extraction of research software installation instructions from readme files: An initial analysis,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Automated extraction of research software installation instructions from readme files: An initial analysis,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:24.055280Z digest=sha256:d058b189292cc97f110c4be5eaa25ee7515b84819ebbba8c86ebdad390056ea3

Observation f31aa540-2032-48e7-9664-79b18562d5af · outbound

This paper cites Large Language Models for Software Engineering: A Systematic Literature Review.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Large Language Models for Software Engineering: A Systematic Literature Review

Reference 32

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source=pdf_text observed=2026-08-11T19:53:24.058225Z digest=sha256:72b04f4e82bf6bc66bf93db2b8f9d79c85b4598982ecaf3e744cab0eb99b12f5

Observation 302426fa-fe41-453c-859e-cfa826c68c77 · outbound

This paper cites Automatic detection of five api documentation smells: Practitioners’ perspectives,.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Automatic detection of five api documentation smells: Practitioners’ perspectives,

Reference 33

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raw_fallback, observed 2026-08-11T19:53:24.353545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T19:53:24.061379Z digest=sha256:3934a65dcb43672c15f583325a56d6f57831e2ca2682941d959425cd3e5344d9

Observation 256bd6d1-f03f-4f87-b63e-6a6dd82fca74 · outbound

This paper cites Available: https://doi.org/10.1145/3597503.3639121.

Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects Available: https://doi.org/10.1145/3597503.3639121

Reference 2024

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source=pdf_text observed=2026-08-11T19:53:23.974097Z digest=sha256:f41756d33ad0938ea05b1d0395ebaa1398cc064cd6814103634a72f677729d95

Pith citing papers

Observation 5925d20a-bfb4-4808-be71-0ad4c62fa6fc · inbound

Beyond Accuracy: Behavioral Dynamics of Agentic Multi-Hunk Repair cites this paper.

Beyond Accuracy: Behavioral Dynamics of Agentic Multi-Hunk Repair Beyond pip install: Evaluating LLM Agents for the Automated Installation of Python Projects

Reference 18

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