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Paper Citation Record · LEDGER

A Survey on Large Language Models for Software Engineering

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 38 inbound Pith citation observations for arXiv:2312.15223.

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

pith.paper-citation-record.v1
2312.15223 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 38 of 38 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 38 of 38 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:06:06.535514Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • malformed identifier0
  • metadata mismatch0

External citation measurements

20
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ffbb15f7-061f-465c-80a3-38425854840e · inbound

Understanding the Human-LLM Dynamic: A Literature Survey of LLM Use in Programming Tasks cites this paper.

Understanding the Human-LLM Dynamic: A Literature Survey of LLM Use in Programming Tasks A Survey on Large Language Models for Software Engineering

Reference 118

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arxiv_id, observed 2026-05-23T20:03:24.562213Z

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=2026-05-23T19:58:28.103216Z digest=sha256:2b60a0a7fe11d4f522d33bdc7a339e5cca7ad36c1e4efc1d900b5fef25d63ddf

Observation 70fc79db-910f-4c6e-8126-6da0f1b7abed · inbound

From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap cites this paper.

From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap A Survey on Large Language Models for Software Engineering

Reference 120

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arxiv_id, observed 2026-05-23T19:08:20.825881Z

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=2026-05-23T19:07:21.016824Z digest=sha256:3df9c07727d9085c77fe981485c72ee110ca7326620ca55440977cb3290b66d2

Observation 70da6515-87b9-43a4-8b75-e567123e3668 · inbound

Augmenting the Generality and Performance of Large Language Models for Software Engineering cites this paper.

Augmenting the Generality and Performance of Large Language Models for Software Engineering A Survey on Large Language Models for Software Engineering

Reference 14

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no resolver link, observed 2026-08-07T04:06:06.535514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:06:06.535514Z digest=sha256:93789bf3d0bdd118b7c91de90ef476672ce2fe4d6792d6f6ffa2bb65394ab540

Observation 7b743598-c7ce-4dea-8175-0ada8e673ef5 · inbound

Domain Specific Benchmarks for Evaluating Multimodal Large Language Models cites this paper.

Domain Specific Benchmarks for Evaluating Multimodal Large Language Models A Survey on Large Language Models for Software Engineering

Reference 24

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no resolver link, observed 2026-08-07T00:39:41.708804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:39:41.708804Z digest=sha256:1f2dfee10d5e10ebcefcd7ea36f8ee2658c1ce93b81d514b478af3fc7840807c

Observation 0e1ac520-9fb7-40dc-b8e1-122d1fe5485d · inbound

Seeing is Fixing: Cross-Modal Reasoning with Multimodal LLMs for Visual Software Issue Fixing cites this paper.

Seeing is Fixing: Cross-Modal Reasoning with Multimodal LLMs for Visual Software Issue Fixing A Survey on Large Language Models for Software Engineering

Reference 8

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no resolver link, observed 2026-08-06T23:49:32.185848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:32.185848Z digest=sha256:6ee74fb5dcac499dd326e7f7f46f0984d71f36c0a7b38ac3933ebfe1165836bc

Observation 922fd222-78c0-4c03-9df7-a9437bc6a35a · inbound

Single Conversation Methodology: A Human-Centered Protocol for AI-Assisted Software Development cites this paper.

Single Conversation Methodology: A Human-Centered Protocol for AI-Assisted Software Development A Survey on Large Language Models for Software Engineering

Reference 18

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no resolver link, observed 2026-08-06T16:44:48.588544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:44:48.588544Z digest=sha256:3fe37053b93e30fef3a6c504452b319c924ac12b8187a1612568a31d70931a32

Observation 1020ccb7-d440-4079-8376-c64cf6fc3fb6 · inbound

Curiosity by Design: An LLM-based Coding Assistant Asking Clarification Questions cites this paper.

Curiosity by Design: An LLM-based Coding Assistant Asking Clarification Questions A Survey on Large Language Models for Software Engineering

Reference 54

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unresolved
no resolver link, observed 2026-08-06T13:00:21.812410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:00:21.812410Z digest=sha256:f73e0bc67db87577f4dcef11e2e36a2d4a59a26353bd18111359feb2b6e06541

Observation 32cc27e7-3c02-46be-acf8-028e82a3843d · inbound

Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems cites this paper.

Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems A Survey on Large Language Models for Software Engineering

Reference 66

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arxiv_id, observed 2026-05-18T22:11:52.616034Z

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=2026-05-18T22:11:00.992743Z digest=sha256:acd7ff8c97ba7130ea1e3ec1e49c19adf6b05dd04178df7595efedf107c1c475

Observation cc87eaf0-14d0-4d6b-b06b-7f0fe32238f5 · inbound

CodeWiki: Evaluating AI's Ability to Generate Holistic Documentation for Large-Scale Codebases cites this paper.

CodeWiki: Evaluating AI's Ability to Generate Holistic Documentation for Large-Scale Codebases A Survey on Large Language Models for Software Engineering

Reference 55

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arxiv_id, observed 2026-05-18T03:10:48.421794Z

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=2026-05-18T03:10:21.188635Z digest=sha256:528f9ad815bcb9680cee6405bfd817daa7110b5e9ba60574d0bee3b25c795865

Observation d1d8c467-2b67-4f72-8a60-3867781a35f4 · inbound

REFLEX: Reference-Free Evaluation of Log Summarization via Large Language Model Judgment cites this paper.

REFLEX: Reference-Free Evaluation of Log Summarization via Large Language Model Judgment A Survey on Large Language Models for Software Engineering

Reference 22

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arxiv_id, observed 2026-05-18T00:25:32.304714Z

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=2026-05-18T00:24:32.368361Z digest=sha256:e79d006d77fbb00692fdf22bbd26a51701e04aadeaf8873547b97a6cd0bae534

Observation 1437cd39-7451-49c0-819e-d2ff845fe7a5 · inbound

SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios cites this paper.

SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios A Survey on Large Language Models for Software Engineering

Reference 66

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arxiv_id, observed 2026-05-16T20:28:24.502099Z

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=arxiv_source observed=2026-05-16T20:24:40.939455Z digest=sha256:baf48fce1fc9c1325957fc30d0e9c880eb15e8e2014859153a5e6da95e7f5e06

Observation f68f85b8-127d-4aee-8983-a4c2be468b9f · inbound

Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI cites this paper.

Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI A Survey on Large Language Models for Software Engineering

Reference 94

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arxiv_id, observed 2026-05-16T14:11:01.164814Z

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=2026-05-16T14:09:33.786576Z digest=sha256:8741ea32d8b1a3c305f39cad167af6cd9edb95419ce7a2f82ff003377d844573

Observation a0ec409a-12a8-489a-8fdf-505ac8efdfdf · inbound

RubberDuckBench: A Benchmark for AI Coding Assistants cites this paper.

RubberDuckBench: A Benchmark for AI Coding Assistants A Survey on Large Language Models for Software Engineering

Reference 40

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arxiv_id, observed 2026-05-16T12:17:51.971308Z

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=2026-05-16T12:16:40.086291Z digest=sha256:3d1b93cc4ed4a423b05212dee147e9f88514e777914f3da6d76dce6ed1676eb1

Observation a69ee99f-f13d-41b1-8892-d6d00eaa08db · inbound

SGAgent: Suggestion-Guided LLM-Based Multi-Agent Framework for Repository-Level Software Repair cites this paper.

SGAgent: Suggestion-Guided LLM-Based Multi-Agent Framework for Repository-Level Software Repair A Survey on Large Language Models for Software Engineering

Reference 2023

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no resolver link, observed 2026-08-02T20:17:27.079893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:17:27.079893Z digest=sha256:9cfd39b3d2b0b18a31737d30539a5df8e28fd46cad963455541088cc14ffe9fc

Observation 026ca23e-c9ea-4337-9dff-acd4d91b31eb · inbound

Story Point Estimation Using Large Language Models cites this paper.

Story Point Estimation Using Large Language Models A Survey on Large Language Models for Software Engineering

Reference 19

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arxiv_id, observed 2026-05-15T15:30:07.562929Z

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=2026-05-15T15:27:47.957035Z digest=sha256:6314d0bcf62ee38ff18b245f4283e66be0619750b282e5c3e65f7d1f95246074

Observation 1fd2bb31-d794-4491-a447-aa8bc2969935 · inbound

Do Papers Tell the Whole Story? A Benchmark and Framework for Uncovering Hidden Implementation Gaps in Bioinformatics cites this paper.

Do Papers Tell the Whole Story? A Benchmark and Framework for Uncovering Hidden Implementation Gaps in Bioinformatics A Survey on Large Language Models for Software Engineering

Reference 13

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arxiv_id, observed 2026-05-15T00:38:23.567952Z

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=2026-05-15T00:33:52.326572Z digest=sha256:c42fcca2530b40329e8847b914fe72f3e0aabca1ff84ee0f656e29f6d06a730c

Observation 45da1c34-170c-417d-b1c6-30d208aee8a0 · inbound

Compiling Code LLMs into Lightweight Executables cites this paper.

Compiling Code LLMs into Lightweight Executables A Survey on Large Language Models for Software Engineering

Reference 78

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arxiv_id, observed 2026-05-13T23:28:26.260158Z

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=2026-05-13T23:26:03.943399Z digest=sha256:419ed48b923b254058dba4f5000a0e5195add96e391411a4d6b6058cc5655adb

Observation 71a8e295-9335-4204-80c6-e6024d8e1c66 · inbound

REAgent: Requirement-Driven LLM Agents for Software Issue Resolution cites this paper.

REAgent: Requirement-Driven LLM Agents for Software Issue Resolution A Survey on Large Language Models for Software Engineering

Reference 87

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arxiv_id, observed 2026-05-11T05:50:58.076905Z

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=2026-05-10T17:56:32.201591Z digest=sha256:8769719f4ea0168d0996ab7f5eb81ca2b921bbf19fe0373792ae2f6f000a846e

Observation bf7360f6-ffff-437e-9525-c5a0aed0181d · inbound

Do AI Coding Agents Log Like Humans? An Empirical Study cites this paper.

Do AI Coding Agents Log Like Humans? An Empirical Study A Survey on Large Language Models for Software Engineering

Reference 41

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arxiv_id, observed 2026-05-11T07:55:59.727704Z

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=2026-05-10T16:54:15.236541Z digest=sha256:1d228728beef4b7b4f81a5bf979bb39268d4d39dd98d2790ca3ac3df373156b3

Observation a4ef902d-9121-49d2-97fb-39d1144beaae · inbound

Towards Enabling An Artificial Self-Construction Software Life-cycle via Autopoietic Architectures cites this paper.

Towards Enabling An Artificial Self-Construction Software Life-cycle via Autopoietic Architectures A Survey on Large Language Models for Software Engineering

Reference 73

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arxiv_id, observed 2026-05-11T11:41:05.448444Z

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=2026-05-10T12:43:14.903173Z digest=sha256:96d629a606196a138272b45213bd112990f0b42c397af86c6d8c5a3fde488703

Observation f3744092-7dfc-4528-a72d-5e1d54065a7b · inbound

Bias in the Loop: Auditing LLM-as-a-Judge for Software Engineering cites this paper.

Bias in the Loop: Auditing LLM-as-a-Judge for Software Engineering A Survey on Large Language Models for Software Engineering

Reference 33

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arxiv_id, observed 2026-05-10T07:32:00.306070Z

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=2026-05-10T07:29:03.994957Z digest=sha256:4f9d4c740f341e2aaf235d2a2f505c0e8aa9b078a2b06a79c05b048d0fcdc8ba

Observation 5124e12d-4344-4af7-87fe-96f8ce582915 · inbound

Query2Diagram: Answering Developer Queries with UML Diagrams cites this paper.

Query2Diagram: Answering Developer Queries with UML Diagrams A Survey on Large Language Models for Software Engineering

Reference 46

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arxiv_id, observed 2026-05-11T21:16:30.619127Z

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=2026-05-08T06:03:13.037369Z digest=sha256:053406d5b97ff57cf983fc0ea1a8b4ce5056a5a88fec268cc4890ddba6b5d8b9

Observation 6ea19e9e-0411-4b04-a510-29ba0bf18736 · inbound

Evaluation of LLM-Based Software Engineering Tools: Practices, Challenges, and Future Directions cites this paper.

Evaluation of LLM-Based Software Engineering Tools: Practices, Challenges, and Future Directions A Survey on Large Language Models for Software Engineering

Reference 44

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arxiv_id, observed 2026-05-11T22:21:52.909407Z

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=2026-05-08T02:52:55.120013Z digest=sha256:ed986f381c2c8d2ba819992e5b390e72382572fc7f1f690aaae4cd6fbe6ce9ac

Observation e1a0ad46-63b5-4fa7-80a2-25d45d26a5d9 · inbound

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code cites this paper.

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code A Survey on Large Language Models for Software Engineering

Reference 149

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arxiv_id, observed 2026-05-11T17:21:11.036793Z

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=2026-05-08T17:37:51.790000Z digest=sha256:703493c2fe5e7adc29a838ba96c86d1ab7723198cf3131c230c716169eca4fe7

Observation ab5153ef-de28-4181-92ec-688f76d4ce29 · inbound

Contextualized Code Pretraining for Code Generation cites this paper.

Contextualized Code Pretraining for Code Generation A Survey on Large Language Models for Software Engineering

Reference 52

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arxiv_id, observed 2026-05-20T09:38:10.858949Z

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=2026-05-20T09:36:15.468902Z digest=sha256:7b1ffd1a8ed1baa4c50100437b30b1edafdd04292c73cc30a7a66791170c5614

Observation ec7251d9-cbec-4e39-993a-98196741234f · inbound

How Helpful is LLM Assistance in Network Operations? A Case Study at a Large Demonstration Network cites this paper.

How Helpful is LLM Assistance in Network Operations? A Case Study at a Large Demonstration Network A Survey on Large Language Models for Software Engineering

Reference 6

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arxiv_id, observed 2026-05-20T02:33:20.379967Z

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=2026-05-20T02:33:11.561559Z digest=sha256:2921deae44a09523e413d797e40b170afb375448b085e71e926c5b2324a79c6e

Observation 8d2941f7-2477-4623-aeb5-ffcf19ef1858 · inbound

Security of LLM-generated Code: A Comparative Analysis cites this paper.

Security of LLM-generated Code: A Comparative Analysis A Survey on Large Language Models for Software Engineering

Reference 87

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arxiv_id, observed 2026-05-25T05:16:39.203527Z

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=2026-05-25T05:16:26.372764Z digest=sha256:2fcefbe1f35f6254c78c27a7cc996e70a27840bd52bf34870d461187db5a424f

Observation 6a28a020-4e85-49b8-9ed4-6bb6738c8b4b · inbound

A Tertiary Review of Large Language Model-Based Code Generating Tasks: Trends, Challenges, and Future Directions cites this paper.

A Tertiary Review of Large Language Model-Based Code Generating Tasks: Trends, Challenges, and Future Directions A Survey on Large Language Models for Software Engineering

Reference 108

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arxiv_id, observed 2026-06-29T20:53:58.474013Z

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=2026-06-29T20:48:19.988304Z digest=sha256:7fa34eefc11dbf4d3fd06d6c6518881743ffd5bee074441b9110e4b13d4054b7

Observation 6ec09bf8-d539-4e28-874a-a9c3e47e0d2c · inbound

Projectional Decoding: Towards Semantic-Aware LLM Generation cites this paper.

Projectional Decoding: Towards Semantic-Aware LLM Generation A Survey on Large Language Models for Software Engineering

Reference 42

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arxiv_id, observed 2026-06-29T06:23:09.147704Z

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=2026-06-29T06:19:48.453862Z digest=sha256:ad224ac657fdfeb1002ea42d2d5d3d9febc8c6af5cf460c7c6a6f8af804306c1

Observation f4503bf5-42aa-4685-b731-d204a1008707 · inbound

Empirical Evaluation of Large Language Models for Migration of Code Fragments to Post-Quantum Cryptography cites this paper.

Empirical Evaluation of Large Language Models for Migration of Code Fragments to Post-Quantum Cryptography A Survey on Large Language Models for Software Engineering

Reference 49

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arxiv_id, observed 2026-07-02T17:47:17.810720Z

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=2026-06-27T21:53:11.767222Z digest=sha256:506c341f3c292e5e9b89382a513144ccfefd2be8a677ba8a17a277e2a5e888ee

Observation 85203f2f-4e3c-424a-8415-38cc613c9944 · inbound

Accuracy and Satisfaction in Multi-Turn LLM Dialogues for NFR Assessment cites this paper.

Accuracy and Satisfaction in Multi-Turn LLM Dialogues for NFR Assessment A Survey on Large Language Models for Software Engineering

Reference 3

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arxiv_id, observed 2026-07-04T18:00:00.892534Z

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=arxiv_source observed=2026-06-25T23:12:20.065631Z digest=sha256:822d043e2278875c7de7da8d017901a4fffab7a0a2bdaaa88fb903492f3dccd0

Observation 8e99629f-39d5-4ff6-bc8e-63e107f7ca45 · inbound

LibEvoBench: Probing Temporal Knowledge Stratification in Code Generation Models cites this paper.

LibEvoBench: Probing Temporal Knowledge Stratification in Code Generation Models A Survey on Large Language Models for Software Engineering

Reference 60

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arxiv_id, observed 2026-06-25T21:18:24.666965Z

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=arxiv_source observed=2026-06-25T20:38:40.331343Z digest=sha256:04349d48dfbea042b6001e4fe71b461d3614a1dfde054767aa41ed20b213ca88

Observation 352d19a0-72a1-45eb-8a9c-9e08924cd576 · inbound

Test Case Selection for Deep Neural Networks: A Replication Study on LLMs for Code cites this paper.

Test Case Selection for Deep Neural Networks: A Replication Study on LLMs for Code A Survey on Large Language Models for Software Engineering

Reference 74

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arxiv_id, observed 2026-06-29T00:52:55.666815Z

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=2026-06-29T00:47:54.236329Z digest=sha256:004764768d7184d79911b54c066b24d6246da6cfcf701e97b7cc4e991380214a

Observation 4f2dbd20-c969-4139-be9e-eddea92487b0 · inbound

MOA: A Profiling-Guided LLM Framework for Memory-Optimization Automation at Codebase Scale cites this paper.

MOA: A Profiling-Guided LLM Framework for Memory-Optimization Automation at Codebase Scale A Survey on Large Language Models for Software Engineering

Reference 46

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arxiv_id, observed 2026-07-01T11:35:43.220845Z

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=2026-07-01T04:18:45.773306Z digest=sha256:3fc5ee51aef7172cd0402452f301ba8eaf0d775dfdebe0371a067bcdde6a1aa6

Observation 352f3fc0-4fd3-46bf-b7e0-be3925cc87a5 · inbound

LLM-Driven CI-CD Workflow Intelligence for Cyber Systems Engineering cites this paper.

LLM-Driven CI-CD Workflow Intelligence for Cyber Systems Engineering A Survey on Large Language Models for Software Engineering

Reference 27

Resolution
unresolved
no resolver link, observed 2026-07-11T16:58:30.448675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T16:58:30.448675Z digest=sha256:e3153e0d16931adf205c7f4899ffce0d5b2129ec9ad68891fd17f7c31a47bd48

Observation 35f7f928-2dfa-4f77-a0d6-9b03a13aa7b9 · inbound

Multi-Agent LLM Collaboration for Unit Test Generation via Human-Testing-Inspired Workflows cites this paper.

Multi-Agent LLM Collaboration for Unit Test Generation via Human-Testing-Inspired Workflows A Survey on Large Language Models for Software Engineering

Reference 23

Resolution
unresolved
no resolver link, observed 2026-07-13T05:24:45.090529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T05:24:45.090529Z digest=sha256:f9ac7afdf38014bab5e098a84b0d0620d8b85bd8036eb3bcdc4c80e1749c85b5

Observation 382d5751-5475-4de1-aadb-d619fdf2571c · inbound

TraceDev: A Traceability-Driven Multi-agent Framework for Requirement-to-Code Development cites this paper.

TraceDev: A Traceability-Driven Multi-agent Framework for Requirement-to-Code Development A Survey on Large Language Models for Software Engineering

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-01T14:04:57.781449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:04:57.781449Z digest=sha256:6e24189d5a7f9493adf1336ba47bbc43ab4d5d0fbe1277fec161e7baf68b4415

Observation 61578d99-bcf4-477f-ae9d-89d25175face · inbound

Large Language Models for Software Engineering Diagrams: A Systematic Review of UML and ER modelling cites this paper.

Large Language Models for Software Engineering Diagrams: A Systematic Review of UML and ER modelling A Survey on Large Language Models for Software Engineering

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-01T02:49:55.174933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T02:49:55.174933Z digest=sha256:7e2e0b121c93746ff4302e0048db9263ab412185f31080613a8f6a1ce6283f62