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Paper Citation Record · LEDGER

Evaluating LLMs on Real-World Software Performance Optimization

As of 10 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2606.25530.

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

pith.paper-citation-record.v1
2606.25530 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-25T20:09:37.551395Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

42 of 42 outbound references displayed

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  • verified fuzzy0
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

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Outbound references

Observation 0848b2fa-d65b-4965-97da-c9532e052142 · outbound

This paper cites SWE-perf: Can language models optimize code performance on real-world repos- itories? InSubmitted to The Fourteenth International Conference on Learning Representations,.

Evaluating LLMs on Real-World Software Performance Optimization SWE-perf: Can language models optimize code performance on real-world repos- itories? InSubmitted to The Fourteenth International Conference on Learning Representations,

Reference 1

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:6e80ebeb5ba44ca29763148b8719871f8b5d0f82702b323a7de8fb5eb3bc3801

Observation b19ef983-16ca-4f05-9b4c-eb01b6ae4f37 · outbound

This paper cites Claude sonnet 4.6.

Evaluating LLMs on Real-World Software Performance Optimization Claude sonnet 4.6

Reference 2

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:5bffb88d933a3316169ffa00d873a0bbcfd1fcd22066840d1be88448f9be9994

Observation b242db89-241e-4966-b494-db5bf5fea3c9 · outbound

This paper cites an unresolved cited work.

Evaluating LLMs on Real-World Software Performance Optimization Unresolved cited work

Reference 3

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:8537ae6394e59a149105a9ac3370cf941e02b5a1126d456d88dc35063e20a0e8

Observation 46d3ccde-352e-4dac-b8d7-ac2d425dfbbb · outbound

This paper cites John Wiley & Sons, Ltd, 2017.

Evaluating LLMs on Real-World Software Performance Optimization John Wiley & Sons, Ltd, 2017

Reference 4

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:9a4e1cde87b6fa1aa26a16fbe5dc6c3276f91384929975505ab12635f8d49d90

Observation 697bdaef-60c2-4e6e-a90c-cb44ba84bce5 · outbound

This paper cites Mercury: a code efficiency benchmark for code large language models.

Evaluating LLMs on Real-World Software Performance Optimization Mercury: a code efficiency benchmark for code large language models

Reference 5

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:a1b73ccf5876f9429c787dca6bf11075c8999a9d3aed4db3bbde7e7c14bb8df7

Observation 746751f9-a8b7-4b93-a726-e690bc2f55cd · outbound

This paper cites Lyu.Search-Based LLMs for Code Optimization, page 578–590.

Evaluating LLMs on Real-World Software Performance Optimization Lyu.Search-Based LLMs for Code Optimization, page 578–590

Reference 6

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:81d42354015017ec568fd91d81a330bb1e991f5f061ec89505f3d203b6a86f99

Observation 1a7beae1-fc5d-4a61-b657-06654699b5b0 · outbound

This paper cites Statistically rigorous java performance evaluation.

Evaluating LLMs on Real-World Software Performance Optimization Statistically rigorous java performance evaluation

Reference 7

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:f3671f8e6190785e8d44666b6c136b199f3486dd1b281283b18bb8fe6cd8f092

Observation a54b55cf-9b54-4b26-81ae-95fdc3a323f3 · outbound

This paper cites Language models for code optimization: Survey, challenges and future directions, 2025.

Evaluating LLMs on Real-World Software Performance Optimization Language models for code optimization: Survey, challenges and future directions, 2025

Reference 8

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:a036b8422285d1fa800ad225b79f6659d5cf8a646828dfd434c8eb6728ace9e4

Observation 7f1afbe2-dde3-4fae-aed9-e2ec63665401 · outbound

This paper cites Gemini 3.1 flash.

Evaluating LLMs on Real-World Software Performance Optimization Gemini 3.1 flash

Reference 9

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:dce4ca2409dfd6fe0eb3f55111661b2e4dd655cc81dbace39ba1ed5445b48f2b

Observation fe06543f-7608-4e20-aa46-8b0e1c4392de · outbound

This paper cites Effibench: Bench- marking the efficiency of automatically generated code.

Evaluating LLMs on Real-World Software Performance Optimization Effibench: Bench- marking the efficiency of automatically generated code

Reference 10

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:6f7b18f76c6e64b1930b8dd970c8b773b3d239066783c8b0acbcb833b2de442a

Observation b401a4df-be9c-4b19-9d17-70bb1ef8524e · outbound

This paper cites Monzurul Amin Ifath and Israat Haque.

Evaluating LLMs on Real-World Software Performance Optimization Monzurul Amin Ifath and Israat Haque

Reference 11

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:6444f4dba4e0b5c9b466afc73cb3b59441fab84a56b2c425581479f1cb1422e3

Observation f281f071-0bcc-49c4-a135-575fc04a14a7 · outbound

This paper cites an unresolved cited work.

Evaluating LLMs on Real-World Software Performance Optimization Unresolved cited work

Reference 12

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:5f23319c2a29fce6b8f7a8f4ab218dc25c66773a3268a01a52564c0a99bbff16

Observation c14eb221-6c72-4b82-ab6f-fb0f093a7ef7 · outbound

This paper cites A survey on large language models for code generation.ACM Trans.

Evaluating LLMs on Real-World Software Performance Optimization A survey on large language models for code generation.ACM Trans

Reference 13

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:8211825c01cb6b5fcd102612cbbfb05bb91ed152cbeb4e10bbdbc19435d3d804

Observation 0a42aa90-e44b-4101-a916-7ebd8e52e3ab · outbound

This paper cites Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik Narasimhan.

Evaluating LLMs on Real-World Software Performance Optimization Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik Narasimhan

Reference 14

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:d047002b17f28f9f2882ea3cc2f747822828211eed11dccafa14b536c5d89cec

Observation d45fcaaa-1943-4fb9-aabd-a7c4a0ee45a6 · outbound

This paper cites Understanding and detecting real-world performance bugs.

Evaluating LLMs on Real-World Software Performance Optimization Understanding and detecting real-world performance bugs

Reference 15

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:f54ea3539326f38d53b8e3c61aaa093f1f9d1fc03a302a235a7c95fb690bc549

Observation ba5090aa-c2f5-45b4-a0f3-c1e368e44a3a · outbound

This paper cites Rigorous benchmarking in reasonable time.

Evaluating LLMs on Real-World Software Performance Optimization Rigorous benchmarking in reasonable time

Reference 16

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:aab9a513b606b00c0c2f7529442a8b788af7288d0913dcdadd43cf2618127d17

Observation d5d145f1-9818-4018-9085-149181e94e9b · outbound

This paper cites Gall, and Philipp Leitner.

Evaluating LLMs on Real-World Software Performance Optimization Gall, and Philipp Leitner

Reference 17

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:9f3e09a706fd9ce8a86a18dd74c2a9e3af26ae7eff2f1dbc8b01d6a70d3cc421

Observation 64b77921-2c8e-4c68-a8d8-e4f1763765f3 · outbound

This paper cites Input sensitivity on the performance of configurable systems an empirical study.Journal of Systems and Software, 201:111671, 2023.

Evaluating LLMs on Real-World Software Performance Optimization Input sensitivity on the performance of configurable systems an empirical study.Journal of Systems and Software, 201:111671, 2023

Reference 18

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:201dae21c5a02553a3736d7d68c168d130f2d2e36f299e10591f58035cfa07ac

Observation 08e51002-92cd-4d61-ab34-b34192e224d9 · outbound

This paper cites Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations.

Evaluating LLMs on Real-World Software Performance Optimization Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations

Reference 19

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arxiv_id, observed 2026-07-04T20:30:07.123394Z

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:d56fc2ee166f1e571384c50b6f4fd2f95b1985211014f4920c66c36db15e34a1

Observation 07b66a8e-ca2d-4007-aa4b-965e857bc9ce · outbound

This paper cites Swe-fficiency: Can language models optimize real-world repositories on real workloads?, 2025.

Evaluating LLMs on Real-World Software Performance Optimization Swe-fficiency: Can language models optimize real-world repositories on real workloads?, 2025

Reference 20

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:85e9212fff15c128e295e21bda732ce26a4d8be4bab25c0929415ff72e5aa331

Observation 7966fdd9-f859-4f68-9d7e-239f674c7d3d · outbound

This paper cites MiniMax M27.https://www.minimax.io/news/minimax-m25, 2026.

Evaluating LLMs on Real-World Software Performance Optimization MiniMax M27.https://www.minimax.io/news/minimax-m25, 2026

Reference 21

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:316328bd397e1e1726052347df75f878331a11311d3f1358cf2e3c7b457f75b4

Observation 0783defb-56b8-49a2-becc-b0218ef4669d · outbound

This paper cites Kimi K2.5.

Evaluating LLMs on Real-World Software Performance Optimization Kimi K2.5

Reference 22

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:7bb54de400946603646b4f836ebd1fb748cb030717b617ecd4e7e03698f382f0

Observation dde4ef08-7ada-40de-8df4-4c6f1dcd9ac0 · outbound

This paper cites Analyzing the impact of workloads on modeling the performance of configurable software systems.

Evaluating LLMs on Real-World Software Performance Optimization Analyzing the impact of workloads on modeling the performance of configurable software systems

Reference 23

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Observation af9ede46-7647-4470-8be3-d903816fb74a · outbound

This paper cites an unresolved cited work.

Evaluating LLMs on Real-World Software Performance Optimization Unresolved cited work

Reference 24

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:f62cfa9afb9cf4198f9d2af6e61ce6337f542abb28456cf23b1e90a8f1b30e13

Observation c1aaa681-e5a8-418e-92d0-be80dc40ade3 · outbound

This paper cites Discovering, reporting, and fixing performance bugs.

Evaluating LLMs on Real-World Software Performance Optimization Discovering, reporting, and fixing performance bugs

Reference 25

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Observation 9b3a2ace-7e7e-497e-abf9-c76017b85403 · outbound

This paper cites Introducing GPT-5.2.

Evaluating LLMs on Real-World Software Performance Optimization Introducing GPT-5.2

Reference 26

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Observation 04e3a7f0-ded9-409e-9c58-26d8e043fba8 · outbound

This paper cites Lyu, Caiming Xiong, Silvio Savarese, and Doyen Sahoo.

Evaluating LLMs on Real-World Software Performance Optimization Lyu, Caiming Xiong, Silvio Savarese, and Doyen Sahoo

Reference 27

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:5faf875396b6e5d23e9b1495b1ecd4eaa5b224efc23cdd306a264e37fed7a1a2

Observation 4cb262f0-4fc3-4e7a-9085-260acda5e8fe · outbound

This paper cites Coffe: A code efficiency benchmark for code generation, 2025.

Evaluating LLMs on Real-World Software Performance Optimization Coffe: A code efficiency benchmark for code generation, 2025

Reference 28

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Observation 9f884374-be46-4515-aa40-b857cd428d71 · outbound

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Evaluating LLMs on Real-World Software Performance Optimization Unresolved cited work

Reference 29

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:419c9f9b3730f92d0f13e34a796a38b45209b1289ddfa6a670bbd868ed21edc6

Observation 8bd6cd4a-348a-473a-8e43-cae31c78c5a0 · outbound

This paper cites tracemalloc — Trace memory allocations.

Evaluating LLMs on Real-World Software Performance Optimization tracemalloc — Trace memory allocations

Reference 30

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:4183d637addae7b2fbef8784bd759b1d3d602437aa906be7f8b7297ddba7e3d3

Observation 25e9c537-7411-4a38-9b3f-46beeb615cff · outbound

This paper cites Zhang, Heming Cui, Siu Ming Yiu, Dong HUANG, See-Kiong Ng, and Anh Tuan Luu.

Evaluating LLMs on Real-World Software Performance Optimization Zhang, Heming Cui, Siu Ming Yiu, Dong HUANG, See-Kiong Ng, and Anh Tuan Luu

Reference 31

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:06b73cd22c8a8f6b40bba00fa4e79ed1df66bebe60c0d63215bc93eb63167263

Observation 75bd916e-a941-490b-bdb1-4db9285ab4ca · outbound

This paper cites How efficient is llm-generated code? a rigorous & high-standard benchmark, 2025.

Evaluating LLMs on Real-World Software Performance Optimization How efficient is llm-generated code? a rigorous & high-standard benchmark, 2025

Reference 32

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:70f0fcecf5778ba6d3fe9c9f73be73a8fd026a96c4b8d40959bde821a19ad320

Observation c565f4b7-0036-4ebf-a37a-4152966959ab · outbound

This paper cites A large-scale empirical study on mobile performance: energy, run-time and memory.Empirical Softw.

Evaluating LLMs on Real-World Software Performance Optimization A large-scale empirical study on mobile performance: energy, run-time and memory.Empirical Softw

Reference 33

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:346bdb67cc7b923bb69d237ff1c51610f9acd52c40255d213dd30d348bc43451

Observation 7a3513c0-bae1-4519-b038-236ea342bfdd · outbound

This paper cites Saha, Matthew Lease, Sarfraz Khurshid, and Dewayne E.

Evaluating LLMs on Real-World Software Performance Optimization Saha, Matthew Lease, Sarfraz Khurshid, and Dewayne E

Reference 34

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:b68a3b1f89ab09018342a615128a0b4e47f89fe6d422b8805a69b931b476b87a

Observation e4a798c4-09f3-4702-8f62-8616f6c17d95 · outbound

This paper cites Gso: Challenging software optimization tasks for evaluating swe-agents, 2025.

Evaluating LLMs on Real-World Software Performance Optimization Gso: Challenging software optimization tasks for evaluating swe-agents, 2025

Reference 35

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Observation 59f168cc-90c5-4c62-a95f-08c729f62b7d · outbound

This paper cites Learning performance-improving code edits, 2024.

Evaluating LLMs on Real-World Software Performance Optimization Learning performance-improving code edits, 2024

Reference 36

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:1ba8d30a98dd1bf7a1f9b7dc3a9f39a4cbebd91153ce27f971e90302c1765e34

Observation 1c5a8b2e-ddb4-4e78-848c-0bfdfee8a7b6 · outbound

This paper cites an unresolved cited work.

Evaluating LLMs on Real-World Software Performance Optimization Unresolved cited work

Reference 37

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:1306da9d15b6a214752fc3ed3cf3ef07becfa21ae77242bc0261e0032b09d942

Observation 032fb1b0-b2bb-4b0f-8604-61a9e414b562 · outbound

This paper cites Ecco: Can we improve model-generated code efficiency without sacrificing functional correctness?, 2024.

Evaluating LLMs on Real-World Software Performance Optimization Ecco: Can we improve model-generated code efficiency without sacrificing functional correctness?, 2024

Reference 38

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:a118a6ade36cfe9eae516ce2e88262193d73d3e5eaf8bf63a824aae4bcf41cd8

Observation ee6a826f-2f8a-426b-a3c8-3e2016dbb16c · outbound

This paper cites Perfgen: Automated performance benchmark generation for big data analytics, 2024.

Evaluating LLMs on Real-World Software Performance Optimization Perfgen: Automated performance benchmark generation for big data analytics, 2024

Reference 39

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unresolved
no resolver link, observed 2026-06-25T20:09:37.551395Z

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:e6a5648b7f1b0371e8f8ec70066938fe7de7c7c9ee42e2c16689636cc8c123b2

Observation e88ba221-aa15-40c7-b58b-d471a5965476 · outbound

This paper cites GLM-51.https://z.ai/blog/glm-5.1, 2026.

Evaluating LLMs on Real-World Software Performance Optimization GLM-51.https://z.ai/blog/glm-5.1, 2026

Reference 40

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unresolved
no resolver link, observed 2026-06-25T20:09:37.551395Z

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:d55834d55026c71b95eec93a0760bec92678cf2e02c75ea994657c54201dcdd9

Observation cf513d70-7dec-4dea-b36a-d50e499237b6 · outbound

This paper cites an unresolved cited work.

Evaluating LLMs on Real-World Software Performance Optimization Unresolved cited work

Reference 41

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no resolver link, observed 2026-06-25T20:09:37.551395Z

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:70fe58cadcec8908ec4829f72d60edc7251fe16ac6e8cc1f44fce9a365cde62e

Observation ec033e3d-f27b-4dad-b549-e7f97e707923 · outbound

This paper cites "" PR #50778 - Benchmark Series.replace when using a large dict for to_replace. Parameters: - N: Series length - R: Number of values to replace.

Evaluating LLMs on Real-World Software Performance Optimization "" PR #50778 - Benchmark Series.replace when using a large dict for to_replace. Parameters: - N: Series length - R: Number of values to replace

Reference 42

Resolution
unresolved
no resolver link, observed 2026-06-25T20:09:37.551395Z

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source=pdf_text observed=2026-06-25T20:09:37.551395Z digest=sha256:1036c3e087d9a17a5373ee9d3f6e17ef549b37979f1ac0258a0b064879c775b6

Pith citing papers

No inbound Pith citation observations are available.