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Paper Citation Record · LEDGER

A Survey on Large Language Models for Software Engineering

As of 10 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 2026-08-09T06:31:02.800959+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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  • 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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T19:58:28.103216Z digest=sha256:144077450d52875c44fe5b9231b4c7963441031befa74b2a851ef0a69cc41785

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T19:07:21.016824Z digest=sha256:9164389acf02240cb8d8425ddde9270608f7b6e37312c7545e9b4713af082c40

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=sha256:13c47c2bc0027d4d0f37c205d1fef09c5288a523ebe83bdd23bcd51d03ac7df4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T22:11:00.992743Z digest=sha256:b504fe0882567927a7f7ef9c688ccdd0ed32d5c300a2096ac1f3fd1f41a015b4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T03:10:21.188635Z digest=sha256:e861b7997b34523458f27cd3f9db33a2c2c3cf1a9617fe9f94c216a6f1332d49

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T00:24:32.368361Z digest=sha256:fcdb87e35adf1018f70271135df2dbda6c001c6e29eb7aceac2f2163333c68af

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-16T20:24:40.939455Z digest=sha256:18ea9e2859621d0de82b763a3134391f2ab029f3ff5bda44d51e74085929b6ca

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T14:09:33.786576Z digest=sha256:fa2cddddb1c6e7adb41604cdaf062bf1b8fee2ae36ca0213ce6187031eb08be9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T12:16:40.086291Z digest=sha256:55aff3cddf4847b16ccceb22e5b22e20b4340a06437d1702692db26fcb632a17

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T15:27:47.957035Z digest=sha256:984b7c64cfc665d576c2e9cb552d2a7f5ea5b6ff71e271b8264d1af7fdf71d63

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T00:33:52.326572Z digest=sha256:23d15a26c2357126e74153be7fa4e5024fbf8fd27a77ae8a3e84c909767b006f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T23:26:03.943399Z digest=sha256:8c91054dfe2d42ab396689ba23b241a5b8c6b65a82d79fd6da8ca3c68166f37c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T17:56:32.201591Z digest=sha256:090c75d377c20686d52f3f99c81225f21e87437d6ddf06d2078ca2270956a860

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:54:15.236541Z digest=sha256:8df15547e930e54d57e00b5a84ae14ad3ab792b214858d721609d6d27a4653ce

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T12:43:14.903173Z digest=sha256:59aba4bde7a8c77d5855146b2af5f6434dc5d6ab124fa20892ffddf5dac0fe73

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T07:29:03.994957Z digest=sha256:4660402d5d4e712b0c890c19d39f5f9480f7a616d908e7cbe4aedef4c7283dc9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T06:03:13.037369Z digest=sha256:69d59e738565c2fd8972a6543cb02c32d4fb9e7b64cfa40cf448ff8d6eee1991

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T02:52:55.120013Z digest=sha256:3a05ccfe76e9bca5fbc9d4a28ecc3939ea4d5bd36272dadbd97d5ae71cbc6ae9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T17:37:51.790000Z digest=sha256:7c7e6b8a42e2d7f42b6db461496582f522daf66f46e02cdeb1b335d4e318cdc2

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T09:36:15.468902Z digest=sha256:ef9014e3394b31640cc803c2969d4768c50bd76da88089ce3802316a784ee418

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T02:33:11.561559Z digest=sha256:4ba4396054a4aec88f27f45701a9b55d4db600d25384d8f5965797c796f8861d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T05:16:26.372764Z digest=sha256:5fb5dc8ae274ccea54d739b0ae7348baf2cf2da4a37493c6f07ef29897284a31

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T20:48:19.988304Z digest=sha256:00b081d148d0f9b8c065fbabaf65dcda0624d7186f074a3497d7f40d11f67c7a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T06:19:48.453862Z digest=sha256:31aea645b63f9e4a749325a3f566da91396d275bbf13841942f1263703f94023

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T21:53:11.767222Z digest=sha256:4a1f4bc334f8df6a2db938aa4c17c3c024ac68fbf858f21d4f1f1624b2d2f9aa

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-25T23:12:20.065631Z digest=sha256:0d7a5273f992be1a5fdf46dc8771da87ca7e86e57b548425a0de38d1a1767e9b

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-25T20:38:40.331343Z digest=sha256:1660548ba7c112498a22ee519d4393a5ad0c2c8a60a64a0a8ff61c74a9e6fa7a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T00:47:54.236329Z digest=sha256:d7c6ea8b1fd062875d3a7c69d9b9b9583fa5da364c43742d80327f0fce747b5d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-01T04:18:45.773306Z digest=sha256:c41e3dbf75552fc30089cf5da6e78cb4e256ad2afca3018e56034b98b206c682

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:a024214f18dada330d04834d1bd8104f3beb765fa5aff0109a13d829091ecbb4

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=sha256:0cea61d6475766e28e58cedac76ef930a2db8c38261cd9798577e7ab8ce17a84

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:cd76c76dabdbfee82ce5c858956337740442224a0fd6d6fe7dd1ea0f61284cb9