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Paper Citation Record · LEDGER

Rethinking Code Complexity Through the Lens of Large Language Models

As of 9 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2602.07882.

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

pith.paper-citation-record.v1
2602.07882 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T03:32:07.864648Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T07:39:03.430900Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T07:39:50.239133Z

Reference resolution

26 of 26 outbound references displayed

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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fdb3249f-19b4-4388-ae9e-b2a17ab33dde · outbound

This paper cites U., Tushar, M.

Rethinking Code Complexity Through the Lens of Large Language Models U., Tushar, M

Reference 1

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source=pdf_text observed=2026-08-03T03:32:07.761119Z digest=sha256:cc6c85ca848fd305ccf0c537ce645db61b6dae900b3bafdb3983acf002aa3107

Observation 77a92115-4217-42a7-9d97-8fdc17d990da · outbound

This paper cites DeepSeek-V3 Technical Report.

Rethinking Code Complexity Through the Lens of Large Language Models DeepSeek-V3 Technical Report

Reference 7

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source=pdf_text observed=2026-08-03T03:32:07.787706Z digest=sha256:768243ccd2e21a7d45ff4ca61a66dc624d4e49f6ef93313c468562e80c86b6bb

Observation f0ebe482-d1b8-435e-9d1a-3ab47a0c50e3 · outbound

This paper cites B., Galstyan, A., Wells, A., Schwartz, R., Huerta, E.

Rethinking Code Complexity Through the Lens of Large Language Models B., Galstyan, A., Wells, A., Schwartz, R., Huerta, E

Reference 8

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source=pdf_text observed=2026-08-03T03:32:07.791995Z digest=sha256:7bdb9261d378463f6b778697b703d78d16d744ab4cde8d9a906d9415c3a365f5

Observation b80234d8-8c13-4075-9ecc-081d911d5dbd · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Rethinking Code Complexity Through the Lens of Large Language Models DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 10

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source=pdf_text observed=2026-08-03T03:32:07.800429Z digest=sha256:4fa33bf81db769a3aa1ea448a9ebb6cb5445c745589123560baaa2b6fce87809

Observation 78470649-162e-434d-b6bc-f3c0dde766ad · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

Rethinking Code Complexity Through the Lens of Large Language Models LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 13

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source=pdf_text observed=2026-08-03T03:32:07.813569Z digest=sha256:b369e78aeeccc0b02794b7005b6a4320eebeebfe264d64bf4ff2b3ea296ffbf3

Observation 1c6741a3-c7f0-4d26-98a3-8f8d38cea049 · outbound

This paper cites C., Vinh, H.

Rethinking Code Complexity Through the Lens of Large Language Models C., Vinh, H

Reference 14

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source=pdf_text observed=2026-08-03T03:32:07.818491Z digest=sha256:9e743cb98ecf754f11d4d4819d3c6e93542ee5124bb175f901b8bd984afe3442

Observation e15532a3-3cea-4649-a469-0fcb2d2da3ab · outbound

This paper cites Entropy-gated branching for efficient test-time reasoning.arXiv preprint arXiv:2503.21961,.

Rethinking Code Complexity Through the Lens of Large Language Models Entropy-gated branching for efficient test-time reasoning.arXiv preprint arXiv:2503.21961,

Reference 15

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source=pdf_text observed=2026-08-03T03:32:07.822133Z digest=sha256:ce0bc40c679ce2eb56d6ebe9e3cbcf2f7ce20b6dcc4ca965a6f31d95d30f2829

Observation 46501164-fe3b-4770-880c-24a1ed628f5c · outbound

This paper cites CodeMind: Evaluating Large Language Models for Code Reasoning.

Rethinking Code Complexity Through the Lens of Large Language Models CodeMind: Evaluating Large Language Models for Code Reasoning

Reference 16

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source=pdf_text observed=2026-08-03T03:32:07.826205Z digest=sha256:142dd00a1d870cbdc4ff8f9f4df69d2a7a441d2fd65cc39247acac5f46df333a

Observation 8c76458d-cdf4-4b1f-863f-508ec862548f · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Rethinking Code Complexity Through the Lens of Large Language Models Code Llama: Open Foundation Models for Code

Reference 18

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source=pdf_text observed=2026-08-03T03:32:07.834093Z digest=sha256:0d58e6ae9854569db98ee20f30b106224a1855b57f81294083704cbd2395b2d4

Observation 331077e5-902e-49a6-bd76-8536041194c0 · outbound

This paper cites Enhancing llm-based code generation with complexity metrics: A feedback-driven approach.

Rethinking Code Complexity Through the Lens of Large Language Models Enhancing llm-based code generation with complexity metrics: A feedback-driven approach

Reference 19

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source=pdf_text observed=2026-08-03T03:32:07.838034Z digest=sha256:d879c58f8ec0039acfcc27e6ed2a98373bb5366f7c9bc33570696aa3bf2b52ce

Observation 9f6ce121-2525-4dbc-9a24-e61fb5b0e384 · outbound

This paper cites From code to correctness: Closing the last mile of code gen- eration with hierarchical debugging.arXiv preprint arXiv:2410.01215, 2024a.

Rethinking Code Complexity Through the Lens of Large Language Models From code to correctness: Closing the last mile of code gen- eration with hierarchical debugging.arXiv preprint arXiv:2410.01215, 2024a

Reference 20

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source=pdf_text observed=2026-08-03T03:32:07.841709Z digest=sha256:ec57c5e6a7430419767576a7da6cd99af89d7c1f663794b664df093d6d45b312

Observation d4306843-4110-4325-9334-51cc2c811f99 · outbound

This paper cites Evoc2rust: A skeleton- guided framework for project-level c-to-rust translation.

Rethinking Code Complexity Through the Lens of Large Language Models Evoc2rust: A skeleton- guided framework for project-level c-to-rust translation

Reference 21

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source=pdf_text observed=2026-08-03T03:32:07.845454Z digest=sha256:b40586c9c986a8bf5d723e0794ccec856f62edb295a8b22f02fd803216580764

Observation fbca5d15-2d58-4f39-95f2-aed192b6c197 · outbound

This paper cites Epicoder: Encompassing diversity and complexity in code generation.

Rethinking Code Complexity Through the Lens of Large Language Models Epicoder: Encompassing diversity and complexity in code generation

Reference 22

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source=pdf_text observed=2026-08-03T03:32:07.849170Z digest=sha256:fa05f1b1616c3037df32e7405a23c0898f818aa2e6d8e704dc71aa02772b8ab9

Observation 5e34234b-9aff-4cec-ba67-8f1280768d3d · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

Rethinking Code Complexity Through the Lens of Large Language Models DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 23

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source=pdf_text observed=2026-08-03T03:32:07.852952Z digest=sha256:17b08556d04c2b1b486fee1a7a534583e007f93223a9aee1f22fea8884d29501

Observation 3b0f9d19-8978-48dc-8505-a83962362549 · outbound

This paper cites lost in the middle.

Rethinking Code Complexity Through the Lens of Large Language Models lost in the middle

Reference 24

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source=pdf_text observed=2026-08-03T03:32:07.856818Z digest=sha256:9869e212c83c77c5ad002a807a5fd397c6ae59d4606175f0641aec0531d60651

Observation 6731d787-7350-4802-82a0-d73e26d3f72a · outbound

This paper cites In the context of code, control-flow constructs (conditionals, loops) introduce structural ambiguity requiring the model to reason about multiple execution paths.

Rethinking Code Complexity Through the Lens of Large Language Models In the context of code, control-flow constructs (conditionals, loops) introduce structural ambiguity requiring the model to reason about multiple execution paths

Reference 25

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source=pdf_text observed=2026-08-03T03:32:07.860934Z digest=sha256:13c101a4304aa8ab1ca4cbc1f4ccd768b5ea7845ceba9e6ad530a423b7aa08da

Observation 2658dcdf-82e4-4b4b-a85a-f17a150de77d · outbound

This paper cites Chain structure ( c2).Units are arranged in a linear compositional chain with levels 1,2,.

Rethinking Code Complexity Through the Lens of Large Language Models Chain structure ( c2).Units are arranged in a linear compositional chain with levels 1,2,

Reference 26

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source=pdf_text observed=2026-08-03T03:32:07.864648Z digest=sha256:3d41537c2f03a6a2fcb30450072e2d8b020c7e35eae7832b8a88604c07fc2d05

Observation 052fe75b-2332-4867-9b4f-7f9e9b05f959 · outbound

This paper cites OctoPack: Instruction Tuning Code Large Language Models.

Rethinking Code Complexity Through the Lens of Large Language Models OctoPack: Instruction Tuning Code Large Language Models

Reference 1976

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source=pdf_text observed=2026-08-03T03:32:07.830196Z digest=sha256:e5dbc6a6b08be78d5ecd56393f5dc917640a989be2f294cb80413c950b4c46f3

Observation cefde051-b152-4a3a-98ff-3eeec25f892a · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Rethinking Code Complexity Through the Lens of Large Language Models Evaluating Large Language Models Trained on Code

Reference 2018

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source=pdf_text observed=2026-08-03T03:32:07.778709Z digest=sha256:bf121e7e550abb41ade4eaee595ceea4a501bcd76961296d7a3a7b443e476b28

Observation 31b89818-5b8e-40ff-b569-749f061bf273 · outbound

This paper cites an unresolved cited work.

Rethinking Code Complexity Through the Lens of Large Language Models Unresolved cited work

Reference 2019

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source=pdf_text observed=2026-08-03T03:32:07.765931Z digest=sha256:179e0d4200b23970c47c433de693852f15ed996bd0a515644cd6c2084e94b2e6

Observation aacc22f5-baa5-491c-90c1-44a82a8a1457 · outbound

This paper cites A critical study of what code-LLMs (do not) learn.

Rethinking Code Complexity Through the Lens of Large Language Models A critical study of what code-LLMs (do not) learn

Reference 2020

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source=pdf_text observed=2026-08-03T03:32:07.770148Z digest=sha256:29043229a0b8bbf6644578ac2e8e622072f581796cd3d4d73c495ea3e52f2df0

Observation 4a696686-9381-4408-9cc3-49b0061e7bd0 · outbound

This paper cites Perplexed: Understanding When Large Language Models are Confused.

Rethinking Code Complexity Through the Lens of Large Language Models Perplexed: Understanding When Large Language Models are Confused

Reference 2021

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source=pdf_text observed=2026-08-03T03:32:07.783204Z digest=sha256:1686c12be71c280c1d6b1d7cde4660eea9d87a103707e8884541361f09eae21b

Observation 6f755aa5-d192-4a57-8528-9aeee71b4e6d · outbound

This paper cites DynaCode: A dynamic complexity-aware code bench- mark for evaluating large language models in code gener- ation.

Rethinking Code Complexity Through the Lens of Large Language Models DynaCode: A dynamic complexity-aware code bench- mark for evaluating large language models in code gener- ation

Reference 2023

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source=pdf_text observed=2026-08-03T03:32:07.805008Z digest=sha256:f04d2479d6017de76998431983ccda88a7cd85080b16876e35ab04808317e559

Observation 6b819685-a369-42c1-9e32-70cc1d939656 · outbound

This paper cites Nestful: A benchmark for evaluating llms on nested sequences of api calls.

Rethinking Code Complexity Through the Lens of Large Language Models Nestful: A benchmark for evaluating llms on nested sequences of api calls

Reference 2024

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source=pdf_text observed=2026-08-03T03:32:07.774466Z digest=sha256:7a4b058661c6b0f27a54e23708813bddeaf7cf3041c97ba6c2faeba1b4c2a0bc

Observation 9a9256c9-c0e0-47aa-af8c-22789d2ab44a · outbound

This paper cites Qwen2.5-Coder Technical Report.

Rethinking Code Complexity Through the Lens of Large Language Models Qwen2.5-Coder Technical Report

Reference 2025

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source=pdf_text observed=2026-08-03T03:32:07.809040Z digest=sha256:9d7d03b3a1d15aed618b62266f86f6981a17ccdd64deb7c8ff7947dd92fe2650

Observation b8f3522e-78cc-4f89-bb34-73cba802696e · outbound

This paper cites an unresolved cited work.

Rethinking Code Complexity Through the Lens of Large Language Models Unresolved cited work

Reference 2026

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source=pdf_text observed=2026-08-03T03:32:07.795889Z digest=sha256:b146ef697750f74c8c3d41516772b1bab7cb8f9ff621a885ea6069aed871f674

Pith citing papers

Observation 0ed53ff3-1c57-49b0-81ab-72cf855aa11f · inbound

Zero-Shot Vulnerability Detection in Low-Resource Smart Contracts Through Solidity-Only Training cites this paper.

Zero-Shot Vulnerability Detection in Low-Resource Smart Contracts Through Solidity-Only Training Rethinking Code Complexity Through the Lens of Large Language Models

Reference 76

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arxiv_id, observed 2026-05-28T03:04:45.627631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T07:39:03.430900Z digest=sha256:6a5963bb0036815230b5496f2722dbf92a4f905b42315cf05cc4e2c4df31497f