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Paper Citation Record · LEDGER

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 2 inbound Pith citation observations for arXiv:2505.23953.

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

pith.paper-citation-record.v1
2505.23953 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:42:49.380605Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:28:04.662036Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T20:26:12.312629Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact0
  • verified fuzzy16
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2d1d413a-cfde-4218-8e67-a108ba5800ef · outbound

This paper cites No Man is an Island: Towards Fully Automatic Programming by Code Search, Code Generation and Program Repair.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach No Man is an Island: Towards Fully Automatic Programming by Code Search, Code Generation and Program Repair

Reference 1

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source=pdf_text observed=2026-08-07T12:42:47.266982Z digest=sha256:15a8acbb8ab79bf0f31f04895301463c2f288577e28c904be53c9fd93e70f451

Observation adf27e45-5821-4b0a-abf3-72d96962fd46 · outbound

This paper cites GPT-4 Technical Report.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach GPT-4 Technical Report

Reference 2

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source=pdf_text observed=2026-08-07T12:42:47.301532Z digest=sha256:9af764ffef2424a4f707f7da0ad5c4341f00af19c1bb4bc7dfc0c3a2dcd10236

Observation c597eb55-f80a-413c-bfe7-e8d94f4ddcd1 · outbound

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

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Chain-of-thought prompting elicits reasoning in large language models,

Reference 3

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source=pdf_text observed=2026-08-07T12:42:47.399613Z digest=sha256:88a6b346797f72cbddd107ed4790a39546d07761546e0b40ee2ed8e0a33c91f4

Observation ca7c204f-bb87-42c0-919e-75cc28bd74a8 · outbound

This paper cites Reflex- ion: Language agents with verbal reinforcement learning,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Reflex- ion: Language agents with verbal reinforcement learning,

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:47.489296Z digest=sha256:ad13164fb5bd7d48966a0baeb93b8daba7442fb7e7c18bbc6224d92b3ca94c76

Observation f7538d63-9f61-4f7a-a4be-3a284c70d6bf · outbound

This paper cites Cyclomatic complexity,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Cyclomatic complexity,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation eff05077-bdf4-4797-a461-b66d3eb9981a · outbound

This paper cites Software complexity analysis using halstead metrics,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Software complexity analysis using halstead metrics,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a54ee7bc-c2a9-4800-8493-f81cc38ad761 · outbound

This paper cites an unresolved cited work.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:47.649809Z digest=sha256:f0464fcefb2aa2aae28d5b27f26e498dc32da1bdd400dd8cc476c77e3260a6a8

Observation bc4b5b42-8b38-4b00-b62c-b926372ff371 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Evaluating Large Language Models Trained on Code

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:47.707195Z digest=sha256:0cf9e7eb13e941bfbd31e9bd99f543d23cd8f815da3922bbca69f69eeef1de98

Observation 8da40589-7982-481c-a1a6-af257376fc47 · outbound

This paper cites Logistic regression,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Logistic regression,

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:47.745640Z digest=sha256:ccd31653e0f2769c58086ea23c1ae3ee5077526d581184450c678e38e0177c4b

Observation 1492496d-7328-45a2-86c2-bb1931a9ee8b · outbound

This paper cites Gpt-3.5-turbo,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Gpt-3.5-turbo,

Reference 10

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raw_fallback, observed 2026-08-07T12:42:51.754048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:47.787975Z digest=sha256:ab32986ed2fa5a5b9ba595600937d001147b652b5bb7314c72861130ccf73845

Observation 82e6b995-8548-454b-954b-262c4aee58aa · outbound

This paper cites The Llama 3 Herd of Models.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach The Llama 3 Herd of Models

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:47.844950Z digest=sha256:883875d1503aa81124466966f100ad75f0fa347090e3e509b8daae365930cc30

Observation ec3497aa-42b8-4687-9535-00a18fd6a349 · outbound

This paper cites Program Synthesis with Large Language Models.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Program Synthesis with Large Language Models

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:47.884835Z digest=sha256:4d423a5c7cd4564547bcbb92d9703eb8f004eab09e559ae78f154a1c5c2e0bf8

Observation 28fd7036-9151-4c9e-8d6d-786dd1e43b5f · outbound

This paper cites Leetcode dataset,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Leetcode dataset,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:47.919535Z digest=sha256:8849ad848c6b58e22258bbff1d953f06fb3aa38b1678b71f6a09cce66c032860

Observation 9d0603c5-dbf5-4981-8e85-c8684cdfcc6f · outbound

This paper cites Introduction to the shapley value,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Introduction to the shapley value,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:47.953398Z digest=sha256:666ce639d2ec8f6d2dbdae2926e0b22fb17a88dcd1cf8a215b4980ec3912fca3

Observation 93263ceb-5838-459e-aa0e-6fbd614f96ef · outbound

This paper cites BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions

Reference 15

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:47.989730Z digest=sha256:8f53f5172eb4984b7a17736094231425fbbf7ace74cc27ab8e825c4a210a84ed

Observation b64ace2c-b152-405f-86e2-9ca9929c968f · outbound

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

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Code Llama: Open Foundation Models for Code

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:48.021836Z digest=sha256:4f2a8436637aee6ac6c3b2366c3cf855d2bfaaeee8c34cc6785160c5aa0431f6

Observation 906bae7e-5d62-4d27-b5a8-569c83fd7569 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:48.052643Z digest=sha256:a2427804920fefd53ee7919e27ff05a03f80a612efe231bb64bd782ac3f935fb

Observation d4355666-d183-4f00-ae0c-a92f4165f873 · outbound

This paper cites Gpt-o3-mini,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Gpt-o3-mini,

Reference 18

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raw_fallback, observed 2026-08-07T12:42:51.411825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:48.095355Z digest=sha256:f1ba198584b2179819e667ae699322c02d735377ed1f3adc0f45238fe58ca9f8

Observation 281931f0-19f6-45a7-8144-e57f288e0805 · outbound

This paper cites Parsel: Algorithmic reasoning with language models by composing decompositions,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Parsel: Algorithmic reasoning with language models by composing decompositions,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:48.160504Z digest=sha256:c057117717e8944966a1c06ca6e37f22a1e9d0d9d4fe5b9247e3a7dac729bc08

Observation 953d045a-dbd6-40b1-a877-2de29bcb9a02 · outbound

This paper cites Anpl: towards natural programming with interactive decomposition,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Anpl: towards natural programming with interactive decomposition,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:48.244656Z digest=sha256:f8907edff4f7ea2466fd7fd8a94c6641f02a3855dcd000eb14e69906c09842ec

Observation ca285ce8-5ec6-45db-9b4f-e1da5d77c7e6 · outbound

This paper cites A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:48.283041Z digest=sha256:1994bdbbe78fd8949c6b65051a2274f8f977594da6ea899adb924295c38950e0

Observation 4a02b37f-f55b-4716-ae10-2eb43e116c62 · outbound

This paper cites AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:48.318234Z digest=sha256:de006177bc151470a72903f19cb13baf304a819ab9ca38213befe3f8c47b68f7

Observation e48c0abb-38b3-46e7-a054-709324835ec9 · outbound

This paper cites Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:48.385369Z digest=sha256:4a634697281f714fb1cc8273f372c1d55ee54589466828f9d82d93d0f092b1ee

Observation 7797ed5c-8f72-47d5-8ceb-9483a04ecb80 · outbound

This paper cites Automated Prompt Engineering for Cost-Effective Code Generation Using Evolutionary Algorithm.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Automated Prompt Engineering for Cost-Effective Code Generation Using Evolutionary Algorithm

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:48.458168Z digest=sha256:01d2e0976caf34fb1503f853e31f8199cc5f7eeb599bc0a3b7f1669489d3664f

Observation ff59a357-265e-48f6-a87e-d5e16b697141 · outbound

This paper cites A survey on metric of software complexity,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach A survey on metric of software complexity,

Reference 25

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raw_fallback, observed 2026-08-07T12:42:50.990468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:48.556930Z digest=sha256:e88a0a880f4f7939e2e21a99731d3d3ee6d563ea022248aa0db8ab23d729bf8c

Observation 9ec0a775-57bd-472c-b842-d1579a8404bd · outbound

This paper cites A pragmatic approach for hyper-parameter tuning in search-based test case generation,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach A pragmatic approach for hyper-parameter tuning in search-based test case generation,

Reference 26

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raw_fallback, observed 2026-08-07T12:42:50.839308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:48.653316Z digest=sha256:ac1eb30d02c1ee73150f9c9681da83163e14f820425033602c5b8564ba254c15

Observation 673717ef-94b6-46bf-b2c2-6d97721eb6df · outbound

This paper cites An empirical study on bug severity estimation using source code metrics and static analysis,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach An empirical study on bug severity estimation using source code metrics and static analysis,

Reference 27

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raw_fallback, observed 2026-08-07T12:42:50.694054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:48.733294Z digest=sha256:dc7705f969d3c5c71814f101e2ab5d94b9362d9ebec3372c3a3afaf542daaf4d

Observation ddfa489d-6048-4707-9dd4-5cec615d4a90 · outbound

This paper cites Analysis and modeling conditional mutual dependency of metrics in software defect prediction using latent variables,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Analysis and modeling conditional mutual dependency of metrics in software defect prediction using latent variables,

Reference 28

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raw_fallback, observed 2026-08-07T12:42:50.513519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:48.810001Z digest=sha256:70656037b7b2e62893b351fb55bec5842d402408cd8ebde4147fd192fc87095b

Observation 459817a3-daf6-4175-bf9a-2f21768c9b4a · outbound

This paper cites Automatically learning semantic features for defect prediction,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Automatically learning semantic features for defect prediction,

Reference 29

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raw_fallback, observed 2026-08-07T12:42:50.326852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:48.887609Z digest=sha256:5d7ebbed1035d5b5a494cad9b7c53c5837917e4ce2ab557f529a6595abcc4c1f

Observation 5a289458-ded9-4002-8664-1cd0659948e7 · outbound

This paper cites Continuous software bug prediction,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Continuous software bug prediction,

Reference 30

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raw_fallback, observed 2026-08-07T12:42:50.193140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:49.016709Z digest=sha256:d36511c7afc81b6bbe40aa188667116a2d106eb7997cfc74a947dfac8ba53347

Observation 8f402f69-8672-4bb9-b03e-1491686418ac · outbound

This paper cites Feature selection, l 1 vs. l 2 regularization, and rotational invariance,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Feature selection, l 1 vs. l 2 regularization, and rotational invariance,

Reference 31

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raw_fallback, observed 2026-08-07T12:42:50.010422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:49.119679Z digest=sha256:78d7875f42e5b253e7c38661c22a47b95bed85b328e39e73c48faa249cd82322

Observation 0e59e6a2-15b4-48ff-828a-257c8bc737b9 · outbound

This paper cites Gene selection for cancer classification using support vector machines,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Gene selection for cancer classification using support vector machines,

Reference 32

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raw_fallback, observed 2026-08-07T12:42:49.826918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:42:49.186518Z digest=sha256:3014c84adcd38c7b282a9b42d7fc9ae191b340e1f04aa440be1c26ed08c1c551

Observation 82f7346e-64af-492f-8e2b-43b5bc6fdbab · outbound

This paper cites Correlation-based feature selection for machine learning,.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Correlation-based feature selection for machine learning,

Reference 33

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no resolver link, observed 2026-08-07T12:42:49.263703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:49.263703Z digest=sha256:86baa88d482ba66684aac6bb545016aebc5c50c408b67e7922f6140d23d7c302

Observation ad89ffdc-a058-4693-8f79-c2b736181a4f · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach A Unified Approach to Interpreting Model Predictions

Reference 34

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no resolver link, observed 2026-08-07T12:42:49.380605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:42:49.380605Z digest=sha256:8169b44336c5173dea9c6f55a6b1342046a7b1a51b08acada2f046362f8ae348

Pith citing papers

Observation 405a92cd-5fca-4046-aff2-35c4a4fa2a0a · inbound

Throttling Web Agents Using Reasoning Gates cites this paper.

Throttling Web Agents Using Reasoning Gates Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach

Reference 84

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no resolver link, observed 2026-08-05T12:28:04.662036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:28:04.662036Z digest=sha256:b24137e8b99305d8c695322a5eb710a7b9b09c9d732af7db5a95fb6bcf1dd94c

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How Generation Architecture Shapes Code Complexity in Multi-Agent LLM Systems: A Paired Study on HumanEval cites this paper.

How Generation Architecture Shapes Code Complexity in Multi-Agent LLM Systems: A Paired Study on HumanEval Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach

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