Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The Code Barrier: What LLMs Actually Understand?
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2504.10557.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:17:35.254425Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T11:35:42.832954Z
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 298e4df5-19b8-447c-96bf-5ce8ac996869 · inbound
Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency cites this paper.
Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency The Code Barrier: What LLMs Actually Understand?
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:17:35.254425Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7e13953a-f72c-48e9-9a16-6aca096ff70b · inbound
Using Contrastive Learning to Improve Two-Way Reasoning in Large Language Models: The Obfuscation Task as a Case Study cites this paper.
Using Contrastive Learning to Improve Two-Way Reasoning in Large Language Models: The Obfuscation Task as a Case Study The Code Barrier: What LLMs Actually Understand?
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:28:34.536630Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2acb36da-02b1-47e0-9d23-816c1bde1c8c · inbound
Is "Knowing It's Malicious Enough?" Evaluating LLMs for Fine-Grained Malware Behavior Auditing cites this paper.
Is "Knowing It's Malicious Enough?" Evaluating LLMs for Fine-Grained Malware Behavior Auditing The Code Barrier: What LLMs Actually Understand?
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:56:17.568021Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 37975b99-e31f-4119-94fd-81d8389269c5 · inbound
From Rookie to Expert: Manipulating LLMs for Automated Vulnerability Exploitation in Enterprise Software cites this paper.
From Rookie to Expert: Manipulating LLMs for Automated Vulnerability Exploitation in Enterprise Software The Code Barrier: What LLMs Actually Understand?
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T20:03:22.168293Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 96a98f60-b023-4042-9a66-224704d37137 · inbound
(How) Do Large Language Models Understand High-Level Message Sequence Charts? cites this paper.
(How) Do Large Language Models Understand High-Level Message Sequence Charts? The Code Barrier: What LLMs Actually Understand?
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T17:49:23.224745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8c446b88-e276-4e48-88e8-e68b1ff62c35 · inbound
(How) Do Large Language Models Understand High-Level Message Sequence Charts? cites this paper.
(How) Do Large Language Models Understand High-Level Message Sequence Charts? The Code Barrier: What LLMs Actually Understand?
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T05:49:47.836070Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation dfa3ebe5-3da0-49b4-b4d2-b84f20dc9adb · inbound
Do Machines Struggle Where Humans Do? LLM and Human Comprehension of Obfuscated Code cites this paper.
Do Machines Struggle Where Humans Do? LLM and Human Comprehension of Obfuscated Code The Code Barrier: What LLMs Actually Understand?
Reference 58
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T11:35:42.835199Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.