Paper Citation Record · LEDGER

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities

As of 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 7 inbound Pith citation observations for arXiv:2601.09822.

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

pith.paper-citation-record.v1
2601.09822 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T10:30:42.216792Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:38:39.545367Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:48:46.447342Z

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy0
unresolved35
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8c0d7c93-2cba-4e85-be37-17b0dd02165d · outbound

This paper cites [Ba24] Bairi, R.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities [Ba24] Bairi, R

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:37.630342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5bb6b7b-1c5f-4bd2-bf94-edbdf71c4122 · outbound

This paper cites et al.: A survey on in-context learning.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities et al.: A survey on in-context learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:38.193158Z

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Observation e16b110c-fe09-439e-b410-102e0c6dd93d · outbound

This paper cites arXiv preprint arXiv:2511.07257,.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities arXiv preprint arXiv:2511.07257,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:38.369536Z

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Observation 9542aec8-22a5-4880-88f2-ad3bca79f958 · outbound

This paper cites In: 2017 IEEE 25th international requirements engineering conference (RE).

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities In: 2017 IEEE 25th international requirements engineering conference (RE)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:38.677244Z

Source-reported events for the cited work

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Observation 7ef6d2f7-9373-43b5-b541-39e21af55075 · outbound

This paper cites CoCoST: Automatic Complex Code Generation with Online Searching and Correctness Testing.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities CoCoST: Automatic Complex Code Generation with Online Searching and Correctness Testing

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:38.939430Z

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Observation 1f5c2301-d7ac-4fa2-bd9a-f626b283e102 · outbound

This paper cites CigaR: Cost-efficient Program Repair with LLMs.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities CigaR: Cost-efficient Program Repair with LLMs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:39.032533Z

Source-reported events for the cited work

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Observation 23b548f9-9f04-4627-93bd-059811479b17 · outbound

This paper cites et al.: Large language model-powered smart contract vulnerability detection: New perspectives.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities et al.: Large language model-powered smart contract vulnerability detection: New perspectives

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:39.204091Z

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Observation 81b89b3d-c08f-4a4f-a35c-e6aa4409b692 · outbound

This paper cites MARE: Multi-Agents Collaboration Framework for Requirements Engineering.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities MARE: Multi-Agents Collaboration Framework for Requirements Engineering

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:39.327380Z

Source-reported events for the cited work

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Observation 2779a30c-04b8-44eb-b182-73a2d1087e12 · outbound

This paper cites SelfEvolve: A Code Evolution Framework via Large Language Models.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities SelfEvolve: A Code Evolution Framework via Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:39.504025Z

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Observation 4f4c2c85-4fa6-4849-b62f-59870b5d4cfb · outbound

This paper cites A Quantitative and Qualitative Evaluation of LLM-Based Explainable Fault Localization.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities A Quantitative and Qualitative Evaluation of LLM-Based Explainable Fault Localization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:39.659107Z

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Observation e1208c3d-0a6d-4cf0-a197-42be21671696 · outbound

This paper cites CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:39.806089Z

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Observation cdf1a11b-82e0-48f4-912b-fcc2e45fd7c9 · outbound

This paper cites et al.: Non-functional requirements as qualities, with a spice of ontology.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities et al.: Non-functional requirements as qualities, with a spice of ontology

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:39.982913Z

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Observation 2c131923-0133-40a6-984f-8bc84cde05f9 · outbound

This paper cites DeepSeek-V3 Technical Report.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities DeepSeek-V3 Technical Report

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:40.319796Z

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Observation 84ebaee9-c74e-493f-ae87-b1e5b7bbf5a7 · outbound

This paper cites et al.: Multi-role consensus through llms discussions for vulnerability detection.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities et al.: Multi-role consensus through llms discussions for vulnerability detection

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:40.637184Z

Source-reported events for the cited work

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Observation f45bd011-ca57-47fa-ad98-e770bf4b4037 · outbound

This paper cites ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:40.825075Z

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Observation e1a0bbbd-ec53-41e7-b2d7-769449655b3e · outbound

This paper cites CoverUp: Effective High Coverage Test Generation for Python.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities CoverUp: Effective High Coverage Test Generation for Python

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:40.939727Z

Source-reported events for the cited work

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Observation f1e763d6-2363-4bb1-a347-90d6fe0b499a · outbound

This paper cites AgentFL: Scaling LLM-based Fault Localization to Project-Level Context.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities AgentFL: Scaling LLM-based Fault Localization to Project-Level Context

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.118106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b62a83a4-49dd-4c48-a21e-28ab4bc8f047 · outbound

This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.311359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bd26096-4d8c-4579-adcd-009f2a3418cc · outbound

This paper cites CodeAgent: Autonomous Communicative Agents for Code Review.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities CodeAgent: Autonomous Communicative Agents for Code Review

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.447497Z

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Observation a29eb7da-c3fa-4131-9675-0118d26be51c · outbound

This paper cites MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.526303Z

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Unavailable: canonical work link unavailable.

Observation 4314f968-196d-4928-b1af-3d4f1c0e2cbb · outbound

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

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities Teaching Code LLMs to Use Autocompletion Tools in Repository-Level Code Generation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.638701Z

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Observation 3015a1ff-9d4d-4135-b2d2-3b3af5947dc6 · outbound

This paper cites Emergent Abilities of Large Language Models.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities Emergent Abilities of Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.712632Z

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Observation a954fb36-0e75-465f-8730-bb9b0032cbb6 · outbound

This paper cites A Survey of AI Agent Protocols.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities A Survey of AI Agent Protocols

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.825918Z

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Observation ebda495a-e8a8-4365-9848-e71392b8f8ac · outbound

This paper cites Evaluating Instruction-Tuned Large Language Models on Code Comprehension and Generation.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities Evaluating Instruction-Tuned Large Language Models on Code Comprehension and Generation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.902327Z

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Observation 981e6fa4-fa35-41b3-ba00-2ed3224bb7b4 · outbound

This paper cites No More Manual Tests? Evaluating and Improving ChatGPT for Unit Test Generation.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities No More Manual Tests? Evaluating and Improving ChatGPT for Unit Test Generation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:41.987627Z

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Unavailable: canonical work link unavailable.

Observation ec2857a0-644b-491a-a21d-edd419c17106 · outbound

This paper cites ToolCoder: Teach Code Generation Models to use API search tools.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities ToolCoder: Teach Code Generation Models to use API search tools

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:42.063309Z

Source-reported events for the cited work

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Observation 9829b405-226d-4dd8-92ae-2bb7a974232d · outbound

This paper cites CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:42.137738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c613b45d-ab81-42b8-9a1f-c2e22e3e53e3 · outbound

This paper cites A Survey of Large Language Models.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities A Survey of Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:42.216792Z

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Observation 10460ded-791c-44f6-b510-b1941270b06e · outbound

This paper cites SpecGen: Automated Generation of Formal Program Specifications via Large Language Models.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities SpecGen: Automated Generation of Formal Program Specifications via Large Language Models

Reference 2005

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:40.508028Z

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Unavailable: canonical work link unavailable.

Observation 02930942-2ca9-42b6-b7e3-8795f140264b · outbound

This paper cites et al.: Camel: Communicative agents for"mindëxploration of large language model society.AdvancesinNeuralInformationProcessingSystems36,pp.51991–52008,2023.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities et al.: Camel: Communicative agents for"mindëxploration of large language model society.AdvancesinNeuralInformationProcessingSystems36,pp.51991–52008,2023

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:40.176961Z

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Observation 46615e54-3a4b-4c34-8c8c-51198d3d2c88 · outbound

This paper cites [Go25] Google: Gemini 3 Pro - Best for complex tasks and bringing creative concepts to life, 2025, https://deepmind.google/models/gemini/pro/.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities [Go25] Google: Gemini 3 Pro - Best for complex tasks and bringing creative concepts to life, 2025, https://deepmind.google/models/gemini/pro/

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:38.781040Z

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Observation 43d5d9b5-78c6-4a83-b9f7-5fe5b5213eae · outbound

This paper cites Agentic AI Frameworks: Architectures, Protocols, and Design Challenges.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities Agentic AI Frameworks: Architectures, Protocols, and Design Challenges

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:38.060095Z

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Unavailable: canonical work link unavailable.

Observation b112d338-30bf-44cc-b9c5-e36abf545cf8 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities Training Verifiers to Solve Math Word Problems

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:37.910974Z

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Observation c52785ec-c203-4f53-9aec-8b0dac63bc2e · outbound

This paper cites Evaluating Large Language Models Trained on Code.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities Evaluating Large Language Models Trained on Code

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:37.754975Z

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Observation 211afd19-cf2c-4473-bb79-c91d04fb46f8 · outbound

This paper cites Static Code Analysis in the AI Era: An In-depth Exploration of the Concept, Function, and Potential of Intelligent Code Analysis Agents.

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities Static Code Analysis in the AI Era: An In-depth Exploration of the Concept, Function, and Potential of Intelligent Code Analysis Agents

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T10:30:38.559388Z

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Pith citing papers

Observation 8cd99b61-acb4-4b1d-8eac-fce4064a8e72 · inbound

Code Broker: A Multi-Agent System for Automated Code Quality Assessment cites this paper.

Code Broker: A Multi-Agent System for Automated Code Quality Assessment LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-17T02:20:38.115711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 15564d67-d9fd-4512-b6ad-7ca8ec10b1d9 · inbound

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems cites this paper.

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities

Reference 236

Resolution: verified exact; arxiv_id, observed 2026-07-17T02:20:38.115711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 93c15d2a-de2a-4a93-9b9e-2693a0600670 · inbound

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems cites this paper.

Reference 237

Resolution: verified exact; arxiv_id, observed 2026-07-17T02:20:38.115711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 40c1b8fa-2c63-4306-8655-4609c2a1fb17 · inbound

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization cites this paper.

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-07-17T02:20:38.115711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 65d9ba9e-6321-431d-8d42-4f007f251e45 · inbound

PromptMN: Pseudo Prompting Language cites this paper.

PromptMN: Pseudo Prompting Language LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-17T02:20:38.115711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3cc108ff-294b-4edc-ba2e-6711131f897f · inbound

Specifying the Delegated-Autonomy Boundary: Requirements Engineering for Agentic AI cites this paper.

Specifying the Delegated-Autonomy Boundary: Requirements Engineering for Agentic AI LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T18:40:57.804670Z

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Observation 1cd68544-b06e-4784-8e3e-bd694f19e3cd · inbound

OneDayAgent: Towards a Long-Horizon Harness for Autonomous Agents cites this paper.

OneDayAgent: Towards a Long-Horizon Harness for Autonomous Agents LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-08-08T00:38:39.545367Z

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Unavailable: canonical work link unavailable.