On the public citation graph

LLM-as-a-Judge for Software Engineering: Literature Review, Vision, and the Road Ahead

https://doi.org/10.1145/3797276
0 signed · 25 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.jss.2023.111741openalex-snapshot
Out of the BLEU: How should we assess quality of the Code Generation models?
inferredcites →https://doi.org/10.1016/s0016-0032(96)00063-4openalex-snapshot
The Jensen-Shannon divergence
inferredcites →https://doi.org/10.1109/access.2022.3196347openalex-snapshot
Code Generation Using Machine Learning: A Systematic Review
inferredcites →https://doi.org/10.1109/tciaig.2012.2186810openalex-snapshot
A Survey of Monte Carlo Tree Search Methods
inferredcites →https://doi.org/10.1109/tse.2019.2962027openalex-snapshot
Machine Learning Testing: Survey, Landscapes and Horizons
inferredcites →https://doi.org/10.1109/tse.2024.3361661openalex-snapshot
Stealthy Backdoor Attack for Code Models
inferredcites →https://doi.org/10.1109/tse.2024.3368208openalex-snapshot
Software Testing With Large Language Models: Survey, Landscape, and Vision
inferredcites →https://doi.org/10.1126/science.22.558.309openalex-snapshot
The Spearman Correlation Formula
inferredcites →https://doi.org/10.1145/3708522openalex-snapshot
Large Language Model for Vulnerability Detection and Repair: Literature Review and the Road Ahead
inferredcites →https://doi.org/10.1145/3708525openalex-snapshot
Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead
inferredcites →https://doi.org/10.1145/3712005openalex-snapshot
The Current Challenges of Software Engineering in the Era of Large Language Models
inferredcites →https://doi.org/10.1145/3773034openalex-snapshot
Synthesizing Efficient and Permissive Programmatic Runtime Shields for Neural Policies
inferredcites →https://doi.org/10.1162/tacl_a_00293openalex-snapshot
Inherent Disagreements in Human Textual Inferences
inferredcites →https://doi.org/10.6084/m9.figshare.31044337openalex-snapshot
Online Appendix for Paper: From Code to Courtroom: LLMs as the New Software Judges

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-981-92-3563-6_36openalex-snapshot
M-CodeQ: A Program Code Quality Assessment Model Integrating Code and LLM Generated Evaluations
inferred← citeshttps://doi.org/10.1007/s42979-026-05242-8openalex-snapshot
A Multi-Agent Benchmarking Framework for Evaluating the Performance of Large Language Models in Logic Programming
inferred← citeshttps://doi.org/10.1016/j.asoc.2026.115708openalex-snapshot
Evaluating AI reasoning and prompt engineering in automated test case generation: A comparative study of GPT-4o, O1 models, and human QA
inferred← citeshttps://doi.org/10.1016/j.jss.2026.113036openalex-snapshot
LLMs as judges: Toward the LLM-assisted review of GSN-compliant assurance cases
inferred← citeshttps://doi.org/10.1093/comjnl/bxag102openalex-snapshot
LEB-SCFI: multi-label security-critical function identification via LLM-enhanced binary summarization
inferred← citeshttps://doi.org/10.1145/3822455.3838767openalex-snapshot
Bridging Feature Models and Users: LLM-Generated Low-Code Configurators for Software Product Lines
inferred← citeshttps://doi.org/10.1145/3832783.3837490openalex-snapshot
RegoMender: A Multi-agent Framework for Automated Rego Policy Repair
inferred← citeshttps://doi.org/10.1145/3832783.3837521openalex-snapshot
To Think or Not to Think: Evaluating LLM Reasoning and Agents in Vulnerability Detection
inferred← citeshttps://doi.org/10.1145/3845307openalex-snapshot
A Second Roadmap for Software Engineering
inferred← citeshttps://doi.org/10.2139/ssrn.7346712openalex-snapshot
ACREF: LLM-as-a-Judge Guided Data Curation and Semantic Evaluation for Automated Code Refinement
inferred← citeshttps://doi.org/10.3390/app16136540openalex-snapshot
Large Language Models for UML Class Diagram Modeling: A Preliminary Empirical Evaluation
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.