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Paper Citation Record · LEDGER

Rethinking Code Complexity Through the Lens of Large Language Models

As of 8 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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  • verified fuzzy0
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External citation measurements

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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=sha256:7a53dd7a8bf5785b30b617a3dd004f1dc506be75efe00e4c3718a76a87451395

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:d79ed4badfbfe08467ca9fd76fba1d7b0e5aea04897af4b248e799f5601a2e5f

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=sha256:1039e62d417fa2229de30321c4e537b6e0d73552a6aa881f82253bd5b00b0b27

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=sha256:751a6c30aeeebd8b38313d86735367e8210173d225cd12383e22d2c86dad1176

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=sha256:259f2feae068935cb2a9d313ff58f1c17483eadedd639ea0de4c8cef4106fde4

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=sha256:802b434142a2b076691f89b45fc8cb35a2858aefed38f12bca0c0e3566694622

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=sha256:32cb099ee77c41f1dea93e747fa920dddfde652ab71862d31780202dc67da1bd

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=sha256:0100c958f51dc9409ede672f09d0090a6a71327a6d860856d8b6856f15b2e8fd

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=sha256:6d1dab20c47305d8b4fa92f56607eef50cba165c73e462564cd0e86a8967db8d

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=sha256:4ca55a6907d08b704d74ca61345a352eed921f1ad1588cedbdc41bc4990b7925

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=sha256:6791bf48d5c6f00e471360684c13103fc333d23492b37c6b22ad6b8c4ab7a104

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=sha256:5f15b6f6db5fb1710ab666228445c863dd2b8dd8c96d78618cdf995c07146b33

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:f300e129b9d8cbab99a28a4a64806cae30ec3786313b8400ae22a880cb0ee066

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:f1c9603ff7d256b9ceae88a7d5bbe743b5ffe274115c6008ddf6359e5af5a9e0

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=sha256:44a8ced2f26fd4d219da980dccf2b3f31a26311a5c7c11418f568fb147fa398d

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:a721fde92338286698a19d016742bd107854d7697f00a2d6ae22ed9b2dd94b2d

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=sha256:7776b8108ddd9ac6844a63f12d8d32e5a71e798b50bfeaacb30734e107eee141

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=sha256:2cbb0c5dad76b606762811530943666612a1401a597102f2db4776f710ef9c40

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=sha256:2562e2512e9f02eff0a3632a83f5abf93821a505c17ec32a0d840433281c56aa

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=sha256:779b517141d3ad461a78b593a7e1125cf69508999c596feedba5ee6b92aeb407

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=sha256:6830a8a77bb5ae1f92a62518556900c7f72518eb0b6d10858683f4b75a32ddcc

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=sha256:1e30379725c5944193a5b07e4c509bc35ea883542ab28d0bc940b9f7cc4c6d9e

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=sha256:5d37cc2d515f8c854614ca008cd9bcb25f504122451d241d5269fd628190e36d

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=sha256:63b87f340384228a06b0e3f433df94ddb757c6103e65ee1d73e3fab290165ca4

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=sha256:99656f5687f432cb59f2fa5e26a0d38fda2df6927c3701f46bc486bad48ddfc7

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=sha256:14339135e2edae0b647a87d725143c25f64a23e3351c4ca6dfaea682fc2404d5

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=sha256:251de7ea62683e708495949f4cac8f713f83c3e6a99852523d7831cdce4b3876