Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2504.16027.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T11:10:06.520779Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T07:22:31.204263Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 5ea1dce1-7027-46f5-ac13-12847ff76092 · inbound
Are We SOLID Yet? An Empirical Study on Prompting LLMs to Detect Design Principle Violations cites this paper.
Are We SOLID Yet? An Empirical Study on Prompting LLMs to Detect Design Principle Violations Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:10:06.520779Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b2aeaaf-6b14-4f49-a423-6fe8031865a7 · inbound
Towards Generalizable Reasoning: Group Causal Counterfactual Policy Optimization for LLM Reasoning cites this paper.
Towards Generalizable Reasoning: Group Causal Counterfactual Policy Optimization for LLM Reasoning Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T07:22:31.207472Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4bef57b6-c9e3-4791-bd69-b67b2f4bfe64 · inbound
Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions cites this paper.
Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T23:04:36.291592Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1ab5abea-5ee6-4819-88d6-1acc5e1c087d · inbound
DynamicsLLM: a Dynamic Analysis-based Tool for Generating Intelligent Execution Traces Using LLMs to Detect Android Behavioural Code Smells cites this paper.
DynamicsLLM: a Dynamic Analysis-based Tool for Generating Intelligent Execution Traces Using LLMs to Detect Android Behavioural Code Smells Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:51:01.312074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c91ab388-4f3d-49ae-8a5b-ecda5e0ea9db · inbound
Mitigating LLM Sycophancy in Code Smell Detection Using Evidence-Guided Reasoning Prompts cites this paper.
Mitigating LLM Sycophancy in Code Smell Detection Using Evidence-Guided Reasoning Prompts Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T11:57:56.953101Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.