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Paper Citation Record · LEDGER

LLM4Decompile: Decompiling Binary Code with Large Language Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2403.05286.

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

pith.paper-citation-record.v1
2403.05286 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:11:29.339661Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
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 c2dc8d24-c2d8-4c78-a767-6bbc22c3f706 · inbound

Fast, Fine-Grained Equivalence Checking for Neural Decompilers cites this paper.

Fast, Fine-Grained Equivalence Checking for Neural Decompilers LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T21:31:38.282896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:31:38.282896Z digest=sha256:fe82240f71721d39c6a6713e570ecec9cae03a48240a67cd310db7f12ce7d30b

Observation 73a30504-eebc-45a7-a7e4-613865b2c13d · inbound

Assessing Large Language Models in Comprehending and Verifying Concurrent Programs across Memory Models cites this paper.

Assessing Large Language Models in Comprehending and Verifying Concurrent Programs across Memory Models LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-10T15:19:35.882604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:19:35.882604Z digest=sha256:79d01ab9b0fb70ed9d9c125746a22ee497e9afb531faa888e6b238c502d02c7b

Observation 3bb471ef-9e8d-46aa-9d27-90d3e49b004d · inbound

Can Large Language Models Understand Intermediate Representations in Compilers? cites this paper.

Can Large Language Models Understand Intermediate Representations in Compilers? LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-08T20:20:19.718564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:20:19.718564Z digest=sha256:83c5ec12e0f96699247dbe4e9ddc0ac8069c5616fdd8d69dfe95473a241c6f79

Observation a6153dde-ead1-4fab-9ef9-07803c17bce4 · inbound

Beyond the Edge of Function: Unraveling the Patterns of Type Recovery in Binary Code cites this paper.

Beyond the Edge of Function: Unraveling the Patterns of Type Recovery in Binary Code LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:12:21.520707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-23T01:07:51.075137Z digest=sha256:1c0253437339a26f45fe382459b1a98018f381d3cfe53aa23bbbab5ae6458abb

Observation 6bd3524f-0530-478c-af5a-714402db8db8 · inbound

Large Language Models for Validating Network Protocol Parsers cites this paper.

Large Language Models for Validating Network Protocol Parsers LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-16T12:11:29.339661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:11:29.339661Z digest=sha256:b6111ca1696bef5507be425f44a11534c2be7b4ab62d238cfe4ead97ae781be9

Observation 540cdecf-4d7a-4b92-bb8e-1002098c6b34 · inbound

BinMetric: A Comprehensive Binary Analysis Benchmark for Large Language Models cites this paper.

BinMetric: A Comprehensive Binary Analysis Benchmark for Large Language Models LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-15T22:23:46.789326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:23:46.789326Z digest=sha256:1bf8df09e040597416c0187363b7852084937923c687eb937f696d768f256fdc

Observation c2ae29dc-8fb3-4110-850a-9092f4d963ff · inbound

DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios cites this paper.

DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T20:59:37.239249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:59:37.239249Z digest=sha256:7601f7ec525664731727976989734bba999c548ec1aaaf5c06ae08e811a53354

Observation 488135c3-c42f-465f-a878-db19d1c64dd3 · inbound

VulBinLLM: LLM-powered Vulnerability Detection for Stripped Binaries cites this paper.

VulBinLLM: LLM-powered Vulnerability Detection for Stripped Binaries LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:11.899620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:23:11.899620Z digest=sha256:359965ab3393fd53f730ccd67968c17e5db25b99e7aeba4f1e5a958a1d0cc8ea

Observation c505c07d-fa71-48f9-a6f4-360ef26a4f7d · inbound

AIRTBench: Measuring Autonomous AI Red Teaming Capabilities in Language Models cites this paper.

AIRTBench: Measuring Autonomous AI Red Teaming Capabilities in Language Models LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-15T19:53:32.640743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:53:32.640743Z digest=sha256:905c22808c967873b77e302675347fabce3474d124684e01d80ea32eeae36a4e

Observation 794190c2-c3ca-4156-9b00-c26215b32da5 · inbound

Decompiling Smart Contracts with a Large Language Model cites this paper.

Decompiling Smart Contracts with a Large Language Model LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T18:33:53.681753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:33:53.681753Z digest=sha256:b9b1e51c890d85fb44c7a92f6b437dfc883a6f5ab18ff251967351b9cc3ce757

Observation f86c4cde-96f1-4e60-a8de-3fbf840d43f4 · inbound

gigiProfiler: Diagnosing Performance Issues by Uncovering Application Resource Bottlenecks cites this paper.

gigiProfiler: Diagnosing Performance Issues by Uncovering Application Resource Bottlenecks LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:23.020505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:09:23.020505Z digest=sha256:c5649b7c89a2aa878b2cd1dbd76ab5e3c3245068a385d385bc9e883a38c49105

Observation e588517d-4fb9-4d63-89db-919417c1b499 · inbound

CodableLLM: Automating Decompiled and Source Code Mapping for LLM Dataset Generation cites this paper.

CodableLLM: Automating Decompiled and Source Code Mapping for LLM Dataset Generation LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T20:45:44.343567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:45:44.343567Z digest=sha256:33403c121c3f5d73022f9fb43ab843ae3e122ac8170c87cf8b314cb11c626eb7

Observation 452e3322-a1b3-49f3-b8af-e46794ed1654 · inbound

TraceRAG: A LLM-Based Framework for Explainable Android Malware Detection and Behavior Analysis cites this paper.

TraceRAG: A LLM-Based Framework for Explainable Android Malware Detection and Behavior Analysis LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-04T20:52:32.532133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:52:32.532133Z digest=sha256:45d846dcbfbb18395986eb4a9830c1eba0948adfb0b558a9361ff304f00b2047

Observation 89a17afa-30a3-4b4d-b55c-218f1e1954e6 · inbound

Context-Guided Decompilation: A Step Towards Re-executability cites this paper.

Context-Guided Decompilation: A Step Towards Re-executability LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:35:35.674943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T01:33:54.870931Z digest=sha256:eef4a9ddceee7365247ad9b16c716f0366eb0e3f4593a07220d917ba931af18f

Observation eb0f7e5d-b8f6-45ba-91f0-218143e2f5d9 · inbound

Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation cites this paper.

Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:36:00.007421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T18:02:53.996840Z digest=sha256:ba56486a6204ca7cfa98d13e1e4904ea35767ffc2dc0788bee4f93ce67c7944e

Observation 3aa6f963-1019-4f65-936b-db79c89c839c · inbound

CoDe-R: Refining Decompiler Output with LLMs via Rationale Guidance and Adaptive Inference cites this paper.

CoDe-R: Refining Decompiler Output with LLMs via Rationale Guidance and Adaptive Inference LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:45:50.338896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T14:37:28.107313Z digest=sha256:44b5ccca2f6517e2525babbfa83f81891477c478abe48757c32a6a56c1e8e59d

Observation 2504c6b0-348b-4f7e-9ca8-4f56af10be3c · inbound

CoDe-R: Refining Decompiler Output with LLMs via Rationale Guidance and Adaptive Inference cites this paper.

CoDe-R: Refining Decompiler Output with LLMs via Rationale Guidance and Adaptive Inference LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-12T21:07:20.347554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T21:07:20.347554Z digest=sha256:1d1dc6807dd05fd098d98f2fed1f01dffd035612fd5b0119fd150ada21afdc5a

Observation 83411ffb-b1a4-4d47-b974-cd54f162d73a · inbound

Constraint-Guided Multi-Agent Decompilation for Executable Binary Recovery cites this paper.

Constraint-Guided Multi-Agent Decompilation for Executable Binary Recovery LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:01:11.746992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T03:38:20.915757Z digest=sha256:92181b61909892b2a01fa639eefddda7227370d118e991130f83febfb4933e25

Observation 46cd83d6-20ea-4d32-9579-fab2f726acc1 · inbound

Agentic Vulnerability Reasoning on COTS Binaries cites this paper.

Agentic Vulnerability Reasoning on COTS Binaries LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:56:06.381381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T16:56:40.135544Z digest=sha256:814de00dc99e46c6167475570768f610d478d4ca4bb6835ddca4108177f089e1

Observation b8f13d68-c52b-4c9d-9f48-3ef2e467f72f · inbound

Agentic Vulnerability Reasoning on COTS Binaries cites this paper.

Agentic Vulnerability Reasoning on COTS Binaries LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-02T14:49:44.334860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:49:44.334860Z digest=sha256:7bc63399db1f9a51f61e80741d9ed9b64593dd4ebdd5d577cd0e410c01c5986f

Observation da22caa1-8008-4d8b-a93f-5e77e94718e3 · inbound

Decaf: Improving Neural Decompilation with Automatic Feedback and Search cites this paper.

Decaf: Improving Neural Decompilation with Automatic Feedback and Search LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:07:08.047348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-13T02:03:19.836506Z digest=sha256:2f34f64873c1738d8fb70573ab20b8b569a571ba53686bc84fa8f42a663c5ea6

Observation e7fb38b3-6e0a-448a-aa2d-1585b317179a · inbound

LLM Agent-Assisted Reverse Engineering with Quantitative Readability Metrics cites this paper.

LLM Agent-Assisted Reverse Engineering with Quantitative Readability Metrics LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T19:07:18.287242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T21:38:43.883961Z digest=sha256:b716cccff8b766628314e7b0aadfcf7099f97d2ca8015a8d65c92fbc1ad40029

Observation b00a6234-f02f-493d-ad52-5a320725c983 · inbound

OASIF: An Efficient Obfuscation-Aware Self-Improving Framework for LLM-Based Assembly Code Instruction Following and Comprehension cites this paper.

OASIF: An Efficient Obfuscation-Aware Self-Improving Framework for LLM-Based Assembly Code Instruction Following and Comprehension LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-06-30T03:04:13.902354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T02:58:39.929690Z digest=sha256:eebd59156d8b92d65dba5ff3e2949d21e6f4d3dd47cdd42d787ae41d7d18ee65

Observation 75bc1bd0-c212-42a0-b1db-74b83415ba90 · inbound

Checked Program Recovery from Execution Video: A Sound Oracle for Untrusted Generators cites this paper.

Checked Program Recovery from Execution Video: A Sound Oracle for Untrusted Generators LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-02T08:46:48.487712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-02T08:45:25.011736Z digest=sha256:c668a92ae29fc67937c7c3b3ee6e3e0817e8f0558be271e9941df29709600569

Observation a8cb5949-4aea-4280-9c85-af3750d94922 · inbound

When LLM Defenses Backfire: Characterizing Safety, Performance, and Cost Trade-offs cites this paper.

When LLM Defenses Backfire: Characterizing Safety, Performance, and Cost Trade-offs LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-31T16:06:05.601499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T16:06:05.601499Z digest=sha256:867cf3ecf37f9aa59b5c17468389dfcb446427118fdba50e905ea587ccb67d21

Observation 7eed6ee0-2940-4bc2-9a27-968f5e5b595d · inbound

NotDec: WebAssembly Decompilation With Inter-Procedural Type Recovery cites this paper.

NotDec: WebAssembly Decompilation With Inter-Procedural Type Recovery LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-05T21:44:22.913280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:44:22.913280Z digest=sha256:d2bc5c17c6286af55c16fadb3c089e4d7de8b25d3dc7bcd84b5479391e3db943