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Paper Citation Record · LEDGER

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

As of 18 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 5 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 82 of 82 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:39:35.321148Z

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.882049Z digest=sha256:e8af1afa7c9dccfb4531e7c792ee72d9a161f2c95ae43c6faf6b3ef757a71843

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.886970Z digest=sha256:2cf45a3aa17c8c9640a05976c652af57395605ebcf72773b5facef78d3d0db24

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.891417Z digest=sha256:7484db0aa926725e08fc8a72b38bb8411fe55b5ccf88e70ee64f9aa4e32440c6

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.895969Z digest=sha256:e7db3b26b67302829b8fde49ac8edca13e2b61e134e602e3b8072542ec3d81ca

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.904135Z digest=sha256:0b10d0a35012eac6fae4b12bdfe9f4e5ae750dcb7b5cfa4498b9c98a33cb3b0f

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=sha256:61aa21462387eb3150f0c64a7460bfd24f5c6f36837ec57aac82dc470a6c2da1

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.913569Z digest=sha256:22d3dd5106ea23ba87de9f3f180718b44d31fdeae89b8f53fde6a77d7699b7e9

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.918187Z digest=sha256:4881f28472bd2cd179c15978d35c014eaad5f60ba255e7ff696629ab090ef559

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.922537Z digest=sha256:e7279c564bb56edaddc5f30436a636ddabd54a151f9266db0c01c430d5c74874

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.927322Z digest=sha256:71510f02e43c5a0937c7760492680134d1e50a42968515195410fce1dff2b113

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.931493Z digest=sha256:82b00d1037547c87ea31dd16059fd64cfe262bb59c6650f148eaa33a08c7d059

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.935259Z digest=sha256:3991d833e2f2ff6a02e9c4fe1f82d5ac133addf778d3c55fbe1b7248dcba0e1a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.939037Z digest=sha256:dae88d7c6f70c1058a040fcb70d6ca807c1dc490b00a9c8798e8cef4886950c7

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.943812Z digest=sha256:89e79e4db0b6f3f4418fe2c578f9c47b842ee4037df2c5b390170fb2bfdfb077

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=sha256:9e00581bc4dd9db86d97e5b81d21b8a9b452fd21382684328be5575de33cf8f1

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.951720Z digest=sha256:efe035b9f8554b46b169bcc27b25bd212405d32f27ec1048a90e26013f0d0473

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.955499Z digest=sha256:a6dd793c571ea23bb8b75cf19190b82018eb8bb96b021a7950e92a6b261659ea

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.959179Z digest=sha256:c9b61e8ec9652d5ef4e7ddf061ac4ea331e749a450c1902acf3b791700900889

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.963021Z digest=sha256:eb265862b94bf1c173c7dfac8b2ea7e907e313a2bffb9ed3f275da9b4d62e037

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.970495Z digest=sha256:f94f1fa0d8ea78751297eba7dc11a42c98fae13f9f7f78b807df13c9c4508f34

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.974162Z digest=sha256:6d82451fbce86de5bb693994ed47e48c9927b80e2a7fc4941be73555b9a55ef9

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.977866Z digest=sha256:6d61e6ae676f2de8c0929237266fe60947d2667b070d8703dbd0eae8b0372fca

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.981575Z digest=sha256:c1b566a5b90e77fc72873b11b76402213a51fb7f0f7547a087514e630e71fecc

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:da76fd3b8d8746d0b37398beff88186f9be2c3fb988a52c9e5ea76e871494ed6

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.988961Z digest=sha256:1fe7d6644ae1d1314096661aa25d8cf66abbb473111cb638e66365a306dcc545

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:d37eb52d5ada460e9ef7cd92418056f91790f08460c20228c08b790f73d6cf01

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=sha256:7be8028d837fb4203a02697c6e516530da4923f8d7496173e5819ab749dd3eeb

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.001493Z digest=sha256:a9e5d41a027bb0bb52ba2287068893f2ec40270348351a39fb4a24a7d4866d71

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=sha256:1c8a240df49709e8e00565a8e104a984199e805443daae6499d5b14959c3c31f

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=sha256:9d4df44d60bf108676fbaac0b6b8eacea127e98dc8b16362945c5f2052bc89c6

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.013621Z digest=sha256:00e47949abf8865d544d049e3b61cfa353c6ef43b436742f2d36f85cd4fc338f

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=sha256:3234d651b19a644b5d9bdd84d49ab0913c794eb34a2495876c0e2312cd7692d2

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.021726Z digest=sha256:6d7fde3194a18dc90bc996e18f21e80c416735577c7f17a13b0b7c7608b64664

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.025998Z digest=sha256:38ef02fe1cc5fac41f01f2816b938c8879ac4b599a08ba9aa390e36fbd841ce3

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.030031Z digest=sha256:95b49d83a544a59b3a77ff1ad06d06997f7d63e264e665029160f48ffaeb91ba

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.034254Z digest=sha256:d47c395cd43a3d2c56cb1ddb23d182859ebee5273d3d2d270b97dc6e16a41854

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.038328Z digest=sha256:f89f519abfc9564f3734472ca5b68a4332ca9c8e6f865eb54a38279df50736f0

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=sha256:459b5f13c57e6e0532196c00dda2af547499ff2cc3d0a491fd1663e8ab7be89a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.046761Z digest=sha256:d5af428522763245b5ec72bcc54e6e437d370cffaf957238cc45f25d06caa19d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.050671Z digest=sha256:7019fdf0203894c1c930b4bbb771ef4d6765192ae834aa294f077e4b5a619adf

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.054678Z digest=sha256:716e27849b581a521a5ac8351094ab0a096a93afa7a366eb53ae181f933e4a24

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.058775Z digest=sha256:319c8d968bf1216b52a40a571999f2d9182f8aaa78a11ea46a4e46cfcffd6de5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.062569Z digest=sha256:54c6991aa37cdd7980e53becaffd410ed543fa850249326789d0f2734afef1b5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.066480Z digest=sha256:81dead0c992cbcc6cb8aca25dd91d88a640b9641ea6ead2806dc399b8b0148b5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.070322Z digest=sha256:8489928c2299a108c319f1f2ce55a02373f8bcf77e927de098b74fdd4e9d40e9

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.074357Z digest=sha256:83b3ff589f1b5973586678d7659b505fa4ebb155ccc8c378e0fd34e29400dc48

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.078635Z digest=sha256:9a1240d5d7ad516bda9d9845fa8f38bda03086982fdc5df451f3b20d3200627d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.082785Z digest=sha256:7ca74ff8bb14d0efdd3fcc3a7caaaaedf8b2a31c2b531d761eb40f25852e79bc

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.086830Z digest=sha256:eb5b6842775bcd29d51a6ff21c11f163faa0aecd019756fabd0c69a8d6396513

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.091127Z digest=sha256:a728e30c91bb50310c50545d8e72d1f81aef9a5d8aa30610fcbc6f2140c6066b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.095379Z digest=sha256:04329201080654603f254980397a1a030579c953648c877b16d64666514c7b92

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.099347Z digest=sha256:c414276ec57a1021df3439cba9e75243d3697954e97b340519660a151cac77a3

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:c5c548f611748887ce903d9554d8ca6b4920d27a172477f6e30e7f9873efadb2

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:ad9a1227fca1dde7059286a60f67e416c59dd4bc72e830ad5a7d8718a7e08bf2

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=sha256:4746baad9bc5025eb66e84e00fbe2aa2e4d886abfd0b3211cc7a3eb51e9be7fb

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.115316Z digest=sha256:40f5e8a983261f58a605bd4bbc2b437bddb70d34b24cb44aa10a420bb81e6a40

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.119467Z digest=sha256:4e1dfc4f83cbf3b8c54a8085d1e7c29e78bc3b028d11d1db5d015486fb3bbd7c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.124049Z digest=sha256:c32adcea7e7988414d7ae4e4df934f40e7aba7e14675a89f4c7b72f84d867638

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.128648Z digest=sha256:b366881b9b82962c9510da1646b92053ce28d452888c12236c017865bb670afc

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:eb23bf8cec52dda8185971b1b656a0cddaf8cee40b4efcce271333c452dcca49

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.137935Z digest=sha256:6b6c8047f6598d1a4991c5aaacfd226ca6e17cf965ce6c5b57b0e6740cc6f91b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.142293Z digest=sha256:a23837cd34de1ebac7bfc4d9f676accbfb1b7db1ab4cea450b2bee4ff4765a5f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.146528Z digest=sha256:0d9c0b893eba0f2bb9a1902c22ff06c8351df7cca2e7d4c25658afb37c74c277

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=sha256:6db3fc99d9aae12a477d9ca52360c39f4d648e54e9513e7a283660150780434f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.154696Z digest=sha256:5a3a97403ecb4b5db4281682cfa78bf44f01eab3ab0c477e23ec0140ae11c1a5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.158931Z digest=sha256:8a27dd6da9a078f84b39c00685f2bf39ee0c865863c9f8a91e5b91c8c8aa6a44

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.162759Z digest=sha256:0b9e12ce43d1d486a23f88b92360e837a028c1dde5a64e0094132d0e1ad56228

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.166786Z digest=sha256:b5d19ba10718c068e6df561cbd80c2bb58ee2ff14534240f44fc8c90d4a06dd3

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.170868Z digest=sha256:ca99d3182aaf95e2252dded733768d09a08d722d8120b3245112916754c57c83

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.175018Z digest=sha256:2e67c4c0afd64a16e20b5850e68c1ae216a445606405f564b1fd006a04ad6b85

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.179002Z digest=sha256:7d63683989bfd1b16591e6dd720518d44fee269c7e2f749809dc2661ef75db4b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.183004Z digest=sha256:2834250faf71c768d27bb41b0c273b6521f13f1df5b02f4c50ef651a1d2efa48

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.187643Z digest=sha256:14dc584f9f1580da49459340275f42954e3bb323bc8f2d84482673e3f1be24c1

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.192177Z digest=sha256:38b61d685c957811707064077a1265947e1c5bfcfd0d714564cdf0802d20c388

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:57.196132Z digest=sha256:54d88aeb4885763294ae6283b74a89292ca88b6e7eab36a39e16c24e78bfa43d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.966738Z digest=sha256:b6838cb008a59ff6db163007d18918f3296edfac299daaab6a176903b252b7bc

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:41:56.900086Z digest=sha256:98daa1b2b3990d30d7dc836ee3b168f7eaf66aa366f9f455ef3945973ca7a427

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T14:37:28.107313Z digest=sha256:5f4310a97f9512e3bb2165261e3ad06398b39cd10dfe55672903ebc8b2aee9e3

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:dd5d8ea00b0d71dd62035a6887e9a3e438bde1331966bf10ed0ec7b683e2f15b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-22T09:40:21.746161Z digest=sha256:fe149f6c0af6d636918dbd62285d732877e0a0d4d778dddf5ae54771ccd75167

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:e0d9dc13da4a9f8080f6397520493ce21cbb9a3fc7d34cb6b4fa89820aa92d94

Observation 443cedb3-970e-4fc1-b621-af1551d65420 · inbound

Statistical Analysis of Executability and Program Equivalence in Decompilation for IoT Vulnerability Detection cites this paper.

Statistical Analysis of Executability and Program Equivalence in Decompilation for IoT Vulnerability Detection D-LiFT: Improving LLM-based Decompiler Backend via Code Quality-driven Fine-tuning

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:35.321148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:39:35.321148Z digest=sha256:0df7bb19482287a7cc246bfb7f3e79f4f9b3c6f2a10439d9ac2dc64b2f759054