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Paper Citation Record · LEDGER

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning

As of 7 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 4 inbound Pith citation observations for arXiv:2506.10125.

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

pith.paper-citation-record.v1
2506.10125 v3

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:41:57.196132Z

measured 81 of 81 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:44:23.442024Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T09:41:21.790429Z

Reference resolution

77 of 77 outbound references displayed

  • verified exact2
  • verified fuzzy56
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f20f266a-88d5-4821-9260-9bdc7090b788 · outbound

This paper cites an unresolved cited work.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:41:58.395141Z

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.

source=pdf_text observed=2026-08-07T04:41:56.882049Z digest=sha256:6e125c87b3556dc84b9c5b1056c7781817b6441a6114183dcb167dfa6e1e8085

Observation b52d93a3-3383-45f3-b940-d761f2f3e4f1 · outbound

This paper cites Hex rays decompiler.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Hex rays decompiler

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.382481Z

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.

source=pdf_text observed=2026-08-07T04:41:56.886970Z digest=sha256:68f5a42aa33ceaa40fc7b8fab5749004ebf330cfdc6892a06bfe3f854b710a38

Observation 076eb843-7488-4222-94e3-6a3f75a2dbbd · outbound

This paper cites an unresolved cited work.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:41:58.369361Z

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.

source=pdf_text observed=2026-08-07T04:41:56.891417Z digest=sha256:d7e1e07da61e519ed143af2721c8c7b5bca12607aae873034535b2f628cbe7e1

Observation 3bfa30d6-c3ec-4171-a005-df8fe1fa3bd7 · outbound

This paper cites Claude AI (Claude 3, May 2025 version).

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Claude AI (Claude 3, May 2025 version)

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.355998Z

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.

source=pdf_text observed=2026-08-07T04:41:56.895969Z digest=sha256:bc4a90b6426116dc9b443d644c6ae14eabac4c9cf919ec6da3d458f6de3f8382

Observation 05a89e77-a2f9-4caf-ae90-10cfcf3893d8 · outbound

This paper cites RetDec: A retargetable machine-code decompiler.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning RetDec: A retargetable machine-code decompiler

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.328461Z

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.

source=pdf_text observed=2026-08-07T04:41:56.904135Z digest=sha256:cb9bdcc4d544b180ca6caca9d875cd5744e47dda95fb409f906ac8617762b12e

Observation 23893f9b-0462-45cc-b9da-20cbdde654d6 · outbound

This paper cites Qwen Technical Report.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Qwen Technical Report

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:56.908363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:56.908363Z digest=sha256:aab3994824878e49f12aba53379cecbc2b4590795c743a57243b17276170f11b

Observation 56df8c2a-7c58-4945-8408-da5fee39cf13 · outbound

This paper cites Ahoy SAILR! there is no need to DREAM of c: A Compiler- Aware structuring algorithm for binary decompilation.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Ahoy SAILR! there is no need to DREAM of c: A Compiler- Aware structuring algorithm for binary decompilation

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.313248Z

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.

source=pdf_text observed=2026-08-07T04:41:56.913569Z digest=sha256:8e52b55bc96fc90672b3f0484c1323c484bca40348605780b7c788b631e2090f

Observation 4562b4df-28b4-47e0-be95-f6ad84e8dde1 · outbound

This paper cites Native x86 decompilation using{Semantics-Preserving} structural analysis and iterative {Control-Flow} structuring.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Native x86 decompilation using{Semantics-Preserving} structural analysis and iterative {Control-Flow} structuring

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.299604Z

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.

source=pdf_text observed=2026-08-07T04:41:56.918187Z digest=sha256:b4b8b6205fdd427c9906f478bfd854c85aa0716a4ded487fd598fe5ea5d5233d

Observation 57387835-e585-4066-b683-5c1c518fcb40 · outbound

This paper cites Decomperson: How humans decompile and what we can learn from it.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Decomperson: How humans decompile and what we can learn from it

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.285909Z

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.

source=pdf_text observed=2026-08-07T04:41:56.922537Z digest=sha256:af00867fe16ca82c67ce972729ceb687828422af4b2a911d071e7792116992d0

Observation 5c186840-58ad-4765-9199-5f5937abf358 · outbound

This paper cites Buse and Westley R.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Buse and Westley R

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.271242Z

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.

source=pdf_text observed=2026-08-07T04:41:56.927322Z digest=sha256:a2942a6ebb6448845b35fe528a8420df986dbcb9dde195830b1ef57e6016a4ac

Observation 3318773e-ff0c-40ab-bb00-40cfe70ab392 · outbound

This paper cites Evaluating the effectiveness of decompilers.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Evaluating the effectiveness of decompilers

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.257497Z

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.

source=pdf_text observed=2026-08-07T04:41:56.931493Z digest=sha256:aee0a8fc6a3bdf2377efcf3fd7ff922210c84e18a44bd32ca5e766c767f0f901

Observation 41c28051-f6cf-4a88-8dff-e95397709bc1 · outbound

This paper cites Schwartz, Claire Le Goues, Graham Neubig, and Bogdan Vasilescu.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Schwartz, Claire Le Goues, Graham Neubig, and Bogdan Vasilescu

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.244340Z

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.

source=pdf_text observed=2026-08-07T04:41:56.935259Z digest=sha256:1be138000f85c6c9bc96a3808c2ef91673940172c13eb3a01b7387306fefd1eb

Observation 9e80a09d-a04c-40e0-b854-f57e353ed3bb · outbound

This paper cites coreutils.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning coreutils

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.230760Z

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.

source=pdf_text observed=2026-08-07T04:41:56.939037Z digest=sha256:a61847f9c6ffc8a6b7e590a757f04807cd0f8d7686a8a6babd2937b0fd84726b

Observation 771bfca8-e4b4-4423-83f3-156ea77b1b8c · outbound

This paper cites Z3: An efficient smt solver.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Z3: An efficient smt solver

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.217444Z

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.

source=pdf_text observed=2026-08-07T04:41:56.943812Z digest=sha256:95d89cfb87fd2ed9cafcbe405ebcb6f69c81179506e6cf472b595486b834ecbc

Observation 14c18af4-3176-4b4b-a3dc-f9fdb4b4e445 · outbound

This paper cites StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:56.947388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:56.947388Z digest=sha256:f0fcdbf3f074d357b32ea47890c0038327f96a5202c6cb782a52297d775e9245

Observation d94c0385-d69d-4b61-a9d7-c20cfe8956da · outbound

This paper cites Schwartz, Bogdan Vasilescu, and Claire Le Goues.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Schwartz, Bogdan Vasilescu, and Claire Le Goues

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.204134Z

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.

source=pdf_text observed=2026-08-07T04:41:56.951720Z digest=sha256:82c21ce2f4768ed9eb3ebfd6f8e53bcd27091f8f4e53e30b36eb9f30ef8fac86

Observation b6d45851-b3c9-41ce-84d7-79d26395c602 · outbound

This paper cites R2i: A relative readability metric for decompiled code.Proc.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning R2i: A relative readability metric for decompiled code.Proc

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.190039Z

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.

source=pdf_text observed=2026-08-07T04:41:56.955499Z digest=sha256:ff680bd70d5a1e1b206a225b3cc244bcdcd099630647e8e70a35cf898557a400

Observation ac98f771-195e-47b9-bced-b806b2bbe38e · outbound

This paper cites Curran Associates Inc., Red Hook, NY, USA, 2019.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Curran Associates Inc., Red Hook, NY, USA, 2019

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.176066Z

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.

source=pdf_text observed=2026-08-07T04:41:56.959179Z digest=sha256:f2785c836ebf73bdb0a28e07b0000cece56f15ed676f1dc0441bf4078c5a3272

Observation f7fb8868-7cd5-472f-aa5a-05ccbcc75f86 · outbound

This paper cites Github copilot.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Github copilot

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.162715Z

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.

source=pdf_text observed=2026-08-07T04:41:56.963021Z digest=sha256:15f88f25b9cdd7f5e7d54dcee21d6680f0573c82b42f924c9088c8fed9b4179a

Observation 44a9781c-1905-4d4a-aa0d-ae116c9c64c3 · outbound

This paper cites Gemini Code Assist.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Gemini Code Assist

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.134120Z

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.

source=pdf_text observed=2026-08-07T04:41:56.970495Z digest=sha256:5f55287c23dca386fa62ae0a77dd0d4cedadc1850ddecb2ff2740edea5bd9138

Observation b0017a74-9044-4afb-919c-4dc125a49237 · outbound

This paper cites The llama 3 herd of models, 2024.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning The llama 3 herd of models, 2024

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.119672Z

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.

source=pdf_text observed=2026-08-07T04:41:56.974162Z digest=sha256:dbc4df692c98632d5c01349668c11031189a878c1ad1588bf445f9a8cf1f0f4c

Observation 57e60ad6-8410-4a34-8286-89fef4b61d14 · outbound

This paper cites Queryx: Symbolic query on decompiled code for finding bugs in cots binaries.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Queryx: Symbolic query on decompiled code for finding bugs in cots binaries

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.106220Z

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.

source=pdf_text observed=2026-08-07T04:41:56.977866Z digest=sha256:fdff4f79f6f5db2307157a5d39933d7bf392a2df828f6c39837504a1064162ea

Observation bcbd8602-0457-466e-8f17-a15a727c3e17 · outbound

This paper cites On the importance and shortcomings of code readability metrics: A case study on reactive programming, 2021.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning On the importance and shortcomings of code readability metrics: A case study on reactive programming, 2021

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.093152Z

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.

source=pdf_text observed=2026-08-07T04:41:56.981575Z digest=sha256:96e5cd1cb11c9cd72b4bfe30adb4660bfd423f8be279f15f8e4bea99a060f67a

Observation 23fe7c87-a6ce-4e9c-9ec7-a596ebb95a3a · outbound

This paper cites Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model, 2025.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model, 2025

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:56.985238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:56.985238Z digest=sha256:c0e0753347968027879fddaab2327e95436d4d74ca417ab3d75d0ff20da60182

Observation 42e39a95-d1c6-4eee-b993-79a22db3ae78 · outbound

This paper cites Degpt: Optimizing decompiler output with llm.Proceedings 2024 Network and Distributed System Security Symposium, 2024.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Degpt: Optimizing decompiler output with llm.Proceedings 2024 Network and Distributed System Security Symposium, 2024

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.070400Z

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.

source=pdf_text observed=2026-08-07T04:41:56.988961Z digest=sha256:ce5b53c1ec8160bf46b473a0d1eaaa6ddc49f87935c5731aa96a031370e07ddf

Observation 15f6009d-ad1e-42c0-a927-e16b3aa54c3f · outbound

This paper cites Qwen2.5-Coder Technical Report.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Qwen2.5-Coder Technical Report

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:56.993199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:56.993199Z digest=sha256:52f8ffb3e2938f79a3be35628cc86e49cb67c39375c1f9fcf539395ff69e7f93

Observation 70fe8468-c517-4779-aade-ccda362424f3 · outbound

This paper cites A survey on large language models for code generation, 2024.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning A survey on large language models for code generation, 2024

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:56.997347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:56.997347Z digest=sha256:f7fcb0bdab05998e2838880282e5e135d3ff8c15165b1dff5c99abcdcd3d9be3

Observation 92e1ff20-a6e6-4f1f-b12a-fbd7084b138e · outbound

This paper cites an unresolved cited work.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:41:58.046098Z

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.

source=pdf_text observed=2026-08-07T04:41:57.001493Z digest=sha256:c4bc5b5e7ce431d2d5a788c3c24dc739c4bdef47a8f44d80b203c959e610c9e9

Observation c4176a02-c9d2-440b-bd23-9f393dfa6ffe · outbound

This paper cites Towards Neural Decompilation.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Towards Neural Decompilation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.005468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.005468Z digest=sha256:409c3b10cd29ec5e60447227e1edecb04aceb88e1725b14b0ca073785a1f6478

Observation 9453ef82-efe1-4faa-9304-2812f85c7485 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Gonzalez, Hao Zhang, and Ion Stoica

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.009690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.009690Z digest=sha256:7fd1db21de972b448a85ef01145f7724d2fca7f3f450e3cc8b7f16f0adae2da3

Observation c8ffadf5-98bf-4cb7-b63a-305d71b69cd5 · outbound

This paper cites Ghidramcp: Mcp server for ghidra.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Ghidramcp: Mcp server for ghidra

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.020063Z

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.

source=pdf_text observed=2026-08-07T04:41:57.013621Z digest=sha256:27c1c0d8a425798a1ac3e2b4bce1ebca6574eebbf15c208d9ca74487bf4f1c21

Observation 59d2787b-3092-4259-a8de-649011c6f5b1 · outbound

This paper cites Coderl: Mastering code generation through pretrained models and deep reinforcement learning.Advances in Neural Information Processing Systems, 35:21314–21328, 2022.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Coderl: Mastering code generation through pretrained models and deep reinforcement learning.Advances in Neural Information Processing Systems, 35:21314–21328, 2022

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.017536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.017536Z digest=sha256:19b42b7a7d7c5d817cc0de8e9a867f4c93cebb26ea4120cd7a74223dce234aa1

Observation d3e1b6eb-3e3f-4ddb-b9c8-496dc96e0777 · outbound

This paper cites TIE: principled reverse engineering of types in binary programs.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning TIE: principled reverse engineering of types in binary programs

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.996092Z

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.

source=pdf_text observed=2026-08-07T04:41:57.021726Z digest=sha256:14a649cc71a313b6d51568f178b51a451032f8c392af50dc1d2ae93d88ac9d43

Observation 83392661-6a51-4efd-8775-143f2e6fff24 · outbound

This paper cites When function signature recovery meets compiler optimization.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning When function signature recovery meets compiler optimization

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.982954Z

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.

source=pdf_text observed=2026-08-07T04:41:57.025998Z digest=sha256:ad3c2a68744a314e38ba8a9c537231132a86459d3c4d9101b51ecb0b5cb14416

Observation 24326f23-6be8-429f-bb56-defcecd6ba5f · outbound

This paper cites Zhang,and Dongyan Xu.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Zhang,and Dongyan Xu

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.970298Z

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.

source=pdf_text observed=2026-08-07T04:41:57.030031Z digest=sha256:11d64e43dfd17005d730260fe277166e98a2cabd406e512f1560fa9e0c6e16d2

Observation d43461cd-8972-4ebe-bf13-7c63b0fd59f4 · outbound

This paper cites Understanding llms: A comprehensive overview from training to inference, 2024.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Understanding llms: A comprehensive overview from training to inference, 2024

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.957290Z

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.

source=pdf_text observed=2026-08-07T04:41:57.034254Z digest=sha256:32fb8268eea7022ce9e4e7796998441081c53dd2676e4cfc8530276a40be8f5e

Observation 201654be-b411-47c0-ad02-cc829823be52 · outbound

This paper cites How farwe have come: testing decompilation correctness of c decompilers.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning How farwe have come: testing decompilation correctness of c decompilers

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.943155Z

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.

source=pdf_text observed=2026-08-07T04:41:57.038328Z digest=sha256:fd176c77ef5c7fc13b0c2939253db27e70d4b8df26d45f20606be9cb4f2235e9

Observation b9850101-18d6-4748-ab49-93f3bcd03a87 · outbound

This paper cites Understanding r1-zero-like training: A critical perspective, 2025.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Understanding r1-zero-like training: A critical perspective, 2025

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.042744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.042744Z digest=sha256:8806cf89afeea54741e99c50990c69850df1eb8e1dda0f846e10203f0352f182

Observation b52376ff-1b1d-4a02-a97a-bed57b6a87f6 · outbound

This paper cites Lopes, Juneyoung Lee, Chung-Kil Hur, Zhengyang Liu, and John Regehr.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Lopes, Juneyoung Lee, Chung-Kil Hur, Zhengyang Liu, and John Regehr

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.918558Z

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.

source=pdf_text observed=2026-08-07T04:41:57.046761Z digest=sha256:00d2fc7a636a4d62d70ca2ca2e015ce2667ea6e50f9f27a515da8a668ade4397

Observation a7a87ca9-0a79-480b-a369-7a8abc1f1a56 · outbound

This paper cites The convergence of source code and binary vulnerability discovery – a case study.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning The convergence of source code and binary vulnerability discovery – a case study

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.905931Z

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.

source=pdf_text observed=2026-08-07T04:41:57.050671Z digest=sha256:02a03f18610099d599c74db1fa733b02e4c17b87bc155c3812347ea26abca104

Observation 3a2e3d20-e06d-4574-b48f-f7e36cc07624 · outbound

This paper cites an unresolved cited work.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:41:57.892296Z

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.

source=pdf_text observed=2026-08-07T04:41:57.054678Z digest=sha256:0146bc97504d4b8674dc4c75f85b2334a7a1d370d894c7c70c23a5be4e0d88df

Observation f1c856ee-a5ed-45e5-a725-f12f7f535372 · outbound

This paper cites An empirical validation ofcognitive complexityas a measure ofsource code understand- ability.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning An empirical validation ofcognitive complexityas a measure ofsource code understand- ability

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.878677Z

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.

source=pdf_text observed=2026-08-07T04:41:57.058775Z digest=sha256:f4dd3647903ebbac4c32ec1c87fb6816c635a6d7aa496d13bd4aee4b9fb949e5

Observation 86948324-45c8-4587-b4ef-d4f90e52cccf · outbound

This paper cites NVIDIA Data Center Deep Learning Product Performance AI Inference.NVIDIA Developer.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning NVIDIA Data Center Deep Learning Product Performance AI Inference.NVIDIA Developer

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.863741Z

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.

source=pdf_text observed=2026-08-07T04:41:57.062569Z digest=sha256:11d1f0e75758ff48e2f31d67946a30dde59285ff3faaebd60cbd3c1100c17747

Observation 3ace089a-ed35-4676-9dc6-8b571fcdde39 · outbound

This paper cites Goucher, Adam Perelman, and Aditya Ramesh et al.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Goucher, Adam Perelman, and Aditya Ramesh et al

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.848959Z

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.

source=pdf_text observed=2026-08-07T04:41:57.066480Z digest=sha256:4a45f7ec54088ecd8552170aac053ba8540f78ba046349122ab79fc4c85fc73b

Observation bedefeae-a940-419d-9737-e03a819a739f · outbound

This paper cites ChatGPT (May 2025 version).

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning ChatGPT (May 2025 version)

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.835220Z

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.

source=pdf_text observed=2026-08-07T04:41:57.070322Z digest=sha256:ff82c2b8cb8dbf64739d03943ed7dd6d936a41c560ff03008bfb7479758d1e54

Observation 9c157e45-1516-42bc-8d62-5de375c30342 · outbound

This paper cites Generating refactored code accurately using reinforcement learning.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Generating refactored code accurately using reinforcement learning

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:41:57.295918Z

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.

source=pdf_text observed=2026-08-07T04:41:57.074357Z digest=sha256:7c98363c116f8d5fe92a27e1017d59aa85f387f17ef96e47ebe4f2118192a072

Observation 132817c1-fb61-4a01-ae2b-990f69c8e939 · outbound

This paper cites Lost in translation: A study of bugs introduced by large language models while translating code.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Lost in translation: A study of bugs introduced by large language models while translating code

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.819906Z

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.

source=pdf_text observed=2026-08-07T04:41:57.078635Z digest=sha256:6fb62693c3eebb9d6de26cc9e53eeeb6c90ddd77b9b0224454887c3471edf054

Observation 0b7986cb-bf21-47c2-a00f-bf8be0e9e7fc · outbound

This paper cites A simpler model of software readability.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning A simpler model of software readability

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.803275Z

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.

source=pdf_text observed=2026-08-07T04:41:57.082785Z digest=sha256:12f9a9d4790612488cb6c17885b227bbf8623eb117c5de86f2db8a6d42d00c90

Observation 0c842000-1dce-4300-b9bf-a01823e728e1 · outbound

This paper cites Automatically mitigating vulnerabilities in binary programs via partially recompilable decompilation.IEEE Transactions on Dependable and Secure Computing, 22:2270–2282, 2022.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Automatically mitigating vulnerabilities in binary programs via partially recompilable decompilation.IEEE Transactions on Dependable and Secure Computing, 22:2270–2282, 2022

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.789167Z

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.

source=pdf_text observed=2026-08-07T04:41:57.086830Z digest=sha256:77d44a71a14d5ce0cca3e2538a186d66cad9b995560ae56a8c472828f3088ce8

Observation 20904294-95a8-4d2f-aa89-2b77acae23ee · outbound

This paper cites Learning by playing solving sparse reward tasks from scratch.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Learning by playing solving sparse reward tasks from scratch

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.774801Z

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.

source=pdf_text observed=2026-08-07T04:41:57.091127Z digest=sha256:8fedc5e96130099abf7946c83791f631f0b4c62caf8bb89b1438ab8076bddca2

Observation 743d53b0-e2d3-4ac5-a7ec-23abd16acab4 · outbound

This paper cites Code llama: Open foundation models for code, 2023.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Code llama: Open foundation models for code, 2023

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.760480Z

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.

source=pdf_text observed=2026-08-07T04:41:57.095379Z digest=sha256:7fb49a185e25995d701c3fcc3b20e2cc7c167de0e5cde26b1e61907a81d4e450

Observation c7af97bf-3feb-44d1-bbad-61ec553ec730 · outbound

This paper cites A comprehensive model for code readability.J.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning A comprehensive model for code readability.J

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.747087Z

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.

source=pdf_text observed=2026-08-07T04:41:57.099347Z digest=sha256:97a6483b077f489cb7cc8328496bc0f7724688935fd59b0bd4d9b49a558b4043

Observation 6c0defa4-2995-4ceb-b638-de4162284e5f · outbound

This paper cites Proximal policy optimization algorithms, 2017.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Proximal policy optimization algorithms, 2017

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.103126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.103126Z digest=sha256:ff5d071536fe43d33f30613fffddbb2bede328033f894ce686e1a8ba4040802b

Observation 7d9281bf-4e09-4650-be6e-6fe3638e0e21 · outbound

This paper cites an unresolved cited work.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Unresolved cited work

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.106975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.106975Z digest=sha256:f2b45816f4c9dcb477b7dd5b3be3b6478f7fe4d9fe1d85062297ed50b6d44286

Observation fc237243-3fcd-422c-b51e-f8f869279c90 · outbound

This paper cites Execution-based Code Generation using Deep Reinforcement Learning.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Execution-based Code Generation using Deep Reinforcement Learning

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.111117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.111117Z digest=sha256:45237e0b2c4e5b2eca04fbab1f3fe923a680d73878eed52260af41b096c9c2b7

Observation 6fafabac-40e5-43f3-9bb3-87d5daa6b8e1 · outbound

This paper cites Llm4decompile: Decompiling binary code with large language models.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Llm4decompile: Decompiling binary code with large language models

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.714097Z

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.

source=pdf_text observed=2026-08-07T04:41:57.115316Z digest=sha256:f860c4348942bc3d46937929d4060f58e02bf636661831a17189ec1c70d4eae8

Observation d03c4e44-1332-4e26-a3bc-94a0fe358c32 · outbound

This paper cites LLM-Vectorizer: LLM-based Verified Loop Vectorizer.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning LLM-Vectorizer: LLM-based Verified Loop Vectorizer

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:41:57.259086Z

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.

source=pdf_text observed=2026-08-07T04:41:57.119467Z digest=sha256:df76cdb96fc84063781a415164d04ee80927fc8b3bb03d2ae8644732fe10d44e

Observation eff714c0-17be-492f-90dc-047d07292180 · outbound

This paper cites automatically assessing code understand- ability.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning automatically assessing code understand- ability

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.699869Z

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.

source=pdf_text observed=2026-08-07T04:41:57.124049Z digest=sha256:d00c1fcd7160877f655b438331950420955c0fe2fec4d3b007eb23bfba54eba4

Observation 03f1f9ef-7e5e-49a0-96d4-7ffe88e0ab84 · outbound

This paper cites util-linux.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning util-linux

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.686309Z

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.

source=pdf_text observed=2026-08-07T04:41:57.128648Z digest=sha256:57c72e09b7f8cbbaed9362813a57228808be287d21077c26ca6fd3cdebf80800

Observation be8d05bc-49ed-43c2-b502-86aeadf8268b · outbound

This paper cites TRL: Transformer Reinforcement Learning.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning TRL: Transformer Reinforcement Learning

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.133428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.133428Z digest=sha256:1042dd263c1a697f9e9a34f8dea67c5a73ed7cdc44d0162b8e2af960d762a75b

Observation 513929e8-fae4-4b04-85b1-de4ba39750d0 · outbound

This paper cites Foster, and Michelle L.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Foster, and Michelle L

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.663865Z

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.

source=pdf_text observed=2026-08-07T04:41:57.137935Z digest=sha256:44a3efe6808dd0691916cfa079889785a80b08057eea03223902ffbe757c56f8

Observation ac2271b2-aeb3-4387-99d0-4b3cb1691cb7 · outbound

This paper cites Angr - the next generation of binary analysis.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Angr - the next generation of binary analysis

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.651171Z

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.

source=pdf_text observed=2026-08-07T04:41:57.142293Z digest=sha256:a9a66a5e92d77340fab5b1a2c939a524df26b0edda638f4dd5dd74d47b5e9011

Observation 34c90538-d623-4d93-90e8-4c6d70bb6fc3 · outbound

This paper cites Enhancing translation validation of compiler transformations with large language models, 2024.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Enhancing translation validation of compiler transformations with large language models, 2024

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.637483Z

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.

source=pdf_text observed=2026-08-07T04:41:57.146528Z digest=sha256:0811b3467cb3e0c76f639c9796ab3a9f427dae37ad194449c2e6132c53acb4d2

Observation f8f4a469-6861-4842-a6e1-f9b9af972f48 · outbound

This paper cites Refining Decompiled C Code with Large Language Models.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Refining Decompiled C Code with Large Language Models

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T04:41:57.150479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:41:57.150479Z digest=sha256:905803efa9643bd1d85e826f954f4ae5d75cd2cc2e924f330fe421cd5c74e15f

Observation ef0ba986-78e1-4868-bbf3-d2e9f6d06681 · outbound

This paper cites DEEPTYPE: Refining indirect calltargets withstrong multi-layertype analysis.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning DEEPTYPE: Refining indirect calltargets withstrong multi-layertype analysis

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.623385Z

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.

source=pdf_text observed=2026-08-07T04:41:57.154696Z digest=sha256:b36cbecdb371e456a16a5588586b7341b1cb80872d7610c64f9f4df1de9bdf74

Observation 7dacf552-3e21-4a8c-81cb-6328a3300ed3 · outbound

This paper cites Resym: Harnessing llms to recover variable and data structure symbols from stripped binaries.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Resym: Harnessing llms to recover variable and data structure symbols from stripped binaries

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.609933Z

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.

source=pdf_text observed=2026-08-07T04:41:57.158931Z digest=sha256:ac248c31d407c56de3ed808457eb51637fabe224ee93b8e281694f6f426a59fe

Observation e22a4805-95b0-4ff0-9596-ca5c705c741b · outbound

This paper cites Unleashing the power of generative model in recovering variable names from stripped binary.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Unleashing the power of generative model in recovering variable names from stripped binary

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.595933Z

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.

source=pdf_text observed=2026-08-07T04:41:57.162759Z digest=sha256:20fa73f7eb0b5311c04a7376026bdc80335018039befb7f378f865460eba480c

Observation 288da05e-7ee5-4c99-8b26-4419658c7417 · outbound

This paper cites Helping johnny to analyze malware: A usability-optimized decompiler and malware analysis user study.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Helping johnny to analyze malware: A usability-optimized decompiler and malware analysis user study

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.583083Z

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.

source=pdf_text observed=2026-08-07T04:41:57.166786Z digest=sha256:2df84fe4774449914ff87611e42a6ca359152cabe2c6f2d3f14a1b2c6b81c5cc

Observation cf3639ea-4085-466b-804b-917ed4185cf9 · outbound

This paper cites No more gotos: Decompilation using pattern-independent control-flow structuring and semantic-preserving transformations.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning No more gotos: Decompilation using pattern-independent control-flow structuring and semantic-preserving transformations

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.569290Z

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.

source=pdf_text observed=2026-08-07T04:41:57.170868Z digest=sha256:7d5d04a8519d0504f3dee9ba4680d1ba39bad7e7efc5310d64f23af8e9ad70ac

Observation 23f310bc-6812-428a-ac6c-9a8e8c90ea1b · outbound

This paper cites Bin2wrong: a unified fuzzing framework for uncovering semantic errors in binary-to-c decompilers.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Bin2wrong: a unified fuzzing framework for uncovering semantic errors in binary-to-c decompilers

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.445701Z

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.

source=pdf_text observed=2026-08-07T04:41:57.175018Z digest=sha256:1aaf204b0b3a09cb05ac8ff25fc5672fb23fe8d7b269e1f49143e5e82c092ac7

Observation e6224d19-7228-4651-8064-5825408e1c46 · outbound

This paper cites Analyzing system software components using api model guided symbolic execution.Journal of Automated Software Engineering, 2020.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Analyzing system software components using api model guided symbolic execution.Journal of Automated Software Engineering, 2020

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.430694Z

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.

source=pdf_text observed=2026-08-07T04:41:57.179002Z digest=sha256:b10179c105ba07a6a829712cd3f56667ae051c21cbb93cb95a3dbe30d1afaaa0

Observation b18f5bd8-05d2-4a5e-81b5-55367ecf7d72 · outbound

This paper cites Osprey: Recovery of variable and data structure via probabilistic analysis for stripped binary.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Osprey: Recovery of variable and data structure via probabilistic analysis for stripped binary

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.414975Z

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.

source=pdf_text observed=2026-08-07T04:41:57.183004Z digest=sha256:ad5715a751c34b0ed6317d0b23617af905322a4d4f67b2d08e2685f079baa751

Observation 4ad30d6e-2110-4345-9d01-f604f9e57a3f · outbound

This paper cites Llm hallucinations in practical code generation: Phenomena, mechanism, and mitigation.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Llm hallucinations in practical code generation: Phenomena, mechanism, and mitigation

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.400451Z

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.

source=pdf_text observed=2026-08-07T04:41:57.187643Z digest=sha256:921559be907789eb914413585728aa05f8059d52e06590cc0cd41cdc2f1419f1

Observation 5284b0c1-0ba3-4fbb-8740-724d19a5fee0 · outbound

This paper cites TYGR: Type inference on stripped binaries using graph neural networks.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning TYGR: Type inference on stripped binaries using graph neural networks

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.386234Z

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.

source=pdf_text observed=2026-08-07T04:41:57.192177Z digest=sha256:840b27d6cd99d7c5f4942451256f0c6c28806affb4920e1ef715228956cbd964

Observation 54a1349b-ce0c-4ce6-9b1a-e07a57117b8c · outbound

This paper cites D-Helix: A generic decompiler testing framework using symbolic differentiation.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning D-Helix: A generic decompiler testing framework using symbolic differentiation

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:57.372296Z

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.

source=pdf_text observed=2026-08-07T04:41:57.196132Z digest=sha256:585a201d44ac7c40aa9701f1404110ea572d4e4d57914cc426acf111b467a9c8

Observation b6540b56-0f35-4cf6-a2d6-8ee1dca840c9 · outbound

This paper cites an unresolved cited work.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Unresolved cited work

Reference 2021

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:41:58.147996Z

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.

source=pdf_text observed=2026-08-07T04:41:56.966738Z digest=sha256:0b6624279bd2ca955613fd8ca1123bac2e49f32902cb149a7c973019fe7056ff

Observation dddf3ace-cd39-4641-bb9f-21af8f4b1f90 · outbound

This paper cites Accessed: 2025-06-04.

D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning Accessed: 2025-06-04

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:41:58.341664Z

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.

source=pdf_text observed=2026-08-07T04:41:56.900086Z digest=sha256:e1f70f84c9c6c9094a8ac042b17e06bfacc29bbe541140d41076a6b3a727c4e4

Pith citing papers

Observation 110c5ce4-e72c-4ab1-9ed9-e0f813fe1688 · 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 D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-07-15T00:21:12.099934Z

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.

source=pdf_text observed=2026-05-10T14:37:28.107313Z digest=sha256:bba4d71c72ee6005ab83633d2eb43a6e809b9f7fe2b1362566d8fb98e5b0f53a

Observation 955258cd-8dcb-4418-aeb2-8f7147b7f79c · 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 D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning

Reference 18

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:b325efcf9a1a2a1bdf5676693194b0a318897f9050e45117df6fabb769a55b92

Observation 4b3c9e9c-d1c7-4393-8bae-8baf9dcd90c6 · inbound

ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage cites this paper.

ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning

Reference 94

Resolution
verified exact
arxiv_id, observed 2026-07-15T00:21:12.099934Z

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.

source=pdf_text observed=2026-05-22T09:40:21.746161Z digest=sha256:4202ebabb3dd12dbb657b7ee23db319a485db3cafeec3428b293d5fb7d470b93

Observation 89c480a1-6202-45d1-9edf-0cc3144ad3f6 · inbound

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

NotDec: WebAssembly Decompilation With Inter-Procedural Type Recovery D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T21:44:23.442024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:44:23.442024Z digest=sha256:46ac3b1682299f48bc440e8dbe78864cf5883ca961500b10448da57c32d3968c