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Paper Citation Record · LEDGER

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity

As of 7 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 1 inbound Pith citation observation for arXiv:2509.23449.

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

pith.paper-citation-record.v1
2509.23449 v2

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T14:49:09.228049Z

measured 69 of 69 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T02:55:15.819959Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

68 of 68 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved62
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e26100ad-9a24-4398-a03f-cd1faeac94b2 · outbound

This paper cites Ghidra software reverse engineering framework, 2025-07-31.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Ghidra software reverse engineering framework, 2025-07-31

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:01.279728Z digest=sha256:e02aba98b2055e4ac05a2ffae8b19a72cc2048249c957e276bc6fecfa8d0554a

Observation 58584180-3664-4ecf-be8c-2b5b8fe7e3a7 · outbound

This paper cites Roy, and Juergen Rilling.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Roy, and Juergen Rilling

Reference 2

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verified exact
doi, observed 2026-08-04T14:53:32.413911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-04T14:49:01.363280Z digest=sha256:055f286e93696df3551ad686b036368d8c25b42b21ca627a35d45263a2d68de8

Observation a4e3740b-0d6c-4f35-8dbb-6c9e2f8f2a18 · outbound

This paper cites Beyond embeddings: Interpretable feature extraction for binary code similarity – artifact, 2025-08-.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Beyond embeddings: Interpretable feature extraction for binary code similarity – artifact, 2025-08-

Reference 3

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source=pdf_text observed=2026-08-04T14:49:01.502339Z digest=sha256:abdda70467bb3f5d7c809200e2feae211e241fe3de664a2995cb7b9d49535c57

Observation 63acbb41-bf36-4f11-a37a-f3dcd29564c2 · outbound

This paper cites Fuzzing BusyBox: Leveraging LLM and crash reuse for em- bedded bug unearthing.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Fuzzing BusyBox: Leveraging LLM and crash reuse for em- bedded bug unearthing

Reference 4

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:01.692102Z digest=sha256:4941bf2793ef21a353912f2ab0305197395821e0610264b92d450ffd9b081b09

Observation 0d2ddcf8-a608-436e-b32f-3b1900ab4c32 · outbound

This paper cites an unresolved cited work.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Unresolved cited work

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:01.798782Z digest=sha256:c10f5c85d14565e34c800c155e4f08051bbca0a8c5f0903480f8f9bcf1637e13

Observation 88b37761-0793-4cdd-a5dc-aace8ad56efd · outbound

This paper cites On the way to sboms: Investigating design issues and solutions in practice.ACM Trans.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity On the way to sboms: Investigating design issues and solutions in practice.ACM Trans

Reference 6

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no resolver link, observed 2026-08-04T14:49:01.895933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:01.895933Z digest=sha256:09cbbcfab1bfa1c43effbb1436c4c71d2906f940c4b96fa1857ea3197c88ca3a

Observation 952c903b-38d9-4c3a-9454-33f79bab56f8 · outbound

This paper cites Language Models are Few-Shot Learners.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Language Models are Few-Shot Learners

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:02.016932Z digest=sha256:a43c38c36505687456c1030a9ae1a85ef7631e87482bdc4b5ddff02395fae532

Observation 91d05fd4-5030-4a53-abdc-61d4ca9eadae · outbound

This paper cites Model compression.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Model compression

Reference 8

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source=pdf_text observed=2026-08-04T14:49:02.132046Z digest=sha256:dbe0248aa3aeb7d267a6cf54e632527142e6880cbe0a6c11f83b57c7514581cc

Observation 586e35a5-b9df-43fb-aa56-add3ac05756b · outbound

This paper cites Openssl, 2025-08-05.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Openssl, 2025-08-05

Reference 9

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source=pdf_text observed=2026-08-04T14:49:02.212328Z digest=sha256:e829109974ccfeafec2f4fe218ef008da86f09cbba030fc892c314d796ccef44

Observation f1d1c225-c391-4ab9-bde8-07f9ec21bebe · outbound

This paper cites Mastering digital image alchemy, 2025-07-.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Mastering digital image alchemy, 2025-07-

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:02.337819Z digest=sha256:c63de568a261525001d58f7ddfb3ffe9abdc1e2c862543847650751eca2f97d2

Observation ff65957d-869c-480b-bbfa-bdd826abf549 · outbound

This paper cites Firmup: Precise static detection of common vulnerabilities in firmware.SIGPLAN Not., 53(2):392–404, March 2018.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Firmup: Precise static detection of common vulnerabilities in firmware.SIGPLAN Not., 53(2):392–404, March 2018

Reference 11

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source=pdf_text observed=2026-08-04T14:49:02.544036Z digest=sha256:3a93c916957e518253262d5494442347181d5c4cc47cdb01d869fa1def232d49

Observation c7613fa7-6ba4-4de6-9661-cd61fb7f69be · outbound

This paper cites Bert: Pre-training of deep bidi- rectional transformers for language understanding,.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Bert: Pre-training of deep bidi- rectional transformers for language understanding,

Reference 12

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:02.673150Z digest=sha256:5e53979c8d43494e4911f61382ad5333b92924dd50a7a43358cf3fa9f1aa5862

Observation 2af22f72-5a62-46d3-9bfa-a50d81362f96 · outbound

This paper cites an unresolved cited work.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Unresolved cited work

Reference 13

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source=pdf_text observed=2026-08-04T14:49:02.474254Z digest=sha256:4bc35697718d6e58cd14bdc1cd5db7ea968c7a913ecc55aaabba85605358ead7

Observation 9aa8ca95-dd57-451a-aeb7-0f41b9e93243 · outbound

This paper cites an unresolved cited work.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Unresolved cited work

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:03.118708Z digest=sha256:68e39500d657990aaf0210259bdd60779ac91aa22065eedd5d4df34a030ff52d

Observation ede88f3c-cf4d-41e6-b9d3-04c5039938bd · outbound

This paper cites Ding, Benjamin C.M.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Ding, Benjamin C.M

Reference 15

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:03.224805Z digest=sha256:7a2bbda58bbac5fd7df2bc033fe69c0258a50c47fbbb7ae75a7dd173477cea93

Observation 716f4d49-09cc-421d-99a8-6478061d09c1 · outbound

This paper cites Coreutils - gnu core utilities, 2025-04-09.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Coreutils - gnu core utilities, 2025-04-09

Reference 16

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source=pdf_text observed=2026-08-04T14:49:02.967045Z digest=sha256:4ea0f58aaff283f6d0cc9af84223b03f7f72075572abfb302a2f491064eff4e3

Observation bfc6ced2-cfa5-4a78-8e0e-5868d0fa8dab · outbound

This paper cites Blanket execution: Dynamic similarity testing for program binaries and components.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Blanket execution: Dynamic similarity testing for program binaries and components

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:03.446224Z digest=sha256:7d175648d44fc6955ef3fd992eea7bf35a2553d13c704aece98afc0772ea44ad

Observation ebd489e0-f1a6-485f-a0cc-bdc736eafa59 · outbound

This paper cites Large language models for code analysis: Do LLMs really do their job? In33rd USENIX Secu- rity Symposium (USENIX Security 24), pages 829– 846, Philadelphia, PA, August 2024.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Large language models for code analysis: Do LLMs really do their job? In33rd USENIX Secu- rity Symposium (USENIX Security 24), pages 829– 846, Philadelphia, PA, August 2024

Reference 18

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source=pdf_text observed=2026-08-04T14:49:03.698773Z digest=sha256:1428d2f519ac7fd6971e28e596b9c11b970f04165e5af60090d09c95db56c3f1

Observation 252345a1-9c22-47aa-a93d-6485d5ecf00f · outbound

This paper cites Graph-based comparison of ex- ecutable objects.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Graph-based comparison of ex- ecutable objects

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:03.300603Z digest=sha256:b45feb708e2f2fba33ccca35013739c4580d4aee17cc0c6ced51f286c70b98ed

Observation 007b718e-a94c-48d4-b443-a093f567df5b · outbound

This paper cites Cross-Language Binary-Source Code Matching with Intermediate Representations.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Cross-Language Binary-Source Code Matching with Intermediate Representations

Reference 20

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source=pdf_text observed=2026-08-04T14:49:03.967600Z digest=sha256:241e99d7b02292044e5edbdd813c84c4d4fb4acc774225a614d5432f2810153f

Observation 22cf44ee-da7a-43ee-8029-1cab43360789 · outbound

This paper cites Funcvul: An effective function level vul- nerability detection model using llm and code chunk,.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Funcvul: An effective function level vul- nerability detection model using llm and code chunk,

Reference 21

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source=pdf_text observed=2026-08-04T14:49:04.052068Z digest=sha256:e3a038847a7f93ceb6894799227d38db5416b23f2ae6b402845682a1bbda24ef

Observation f3a2f200-4faf-4429-9cac-6c610e635344 · outbound

This paper cites Code is not natural language: Unlock the power of Semantics-Oriented graph representation for binary code similarity detection.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Code is not natural language: Unlock the power of Semantics-Oriented graph representation for binary code similarity detection

Reference 22

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source=pdf_text observed=2026-08-04T14:49:04.259092Z digest=sha256:95f2829224e1ea93af9ebe06958b82ba2a143a319057a3c10303e1e6599a50a2

Observation 2f5d7854-cbcd-4513-b11f-d8121bc1e467 · outbound

This paper cites Extracting condi- tional formulas for cross-platform bug search.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Extracting condi- tional formulas for cross-platform bug search

Reference 23

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verified exact
doi, observed 2026-08-04T14:53:31.584747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-04T14:49:03.860379Z digest=sha256:75a6994c8c2d1daf7b6071aa193310dcc9f9559674a63110e356a7f70970f56a

Observation dca5c9b6-71e7-4998-a566-bee1b0517686 · outbound

This paper cites Richard Hipp.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Richard Hipp

Reference 24

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source=pdf_text observed=2026-08-04T14:49:04.504824Z digest=sha256:e266b5478c018d1f514e9f69e3a611dfefd5ebc2b109e406c91a6962f3631618

Observation bbdbde88-5cfd-4eca-af94-edc9f611633d · outbound

This paper cites Qwen2.5-Coder Technical Report.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Qwen2.5-Coder Technical Report

Reference 25

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:04.640798Z digest=sha256:2a819e9f9fa252b6fcf94672cf1a3398fb94fedc161f3f1c615c4d43b863e234

Observation db4135e2-9466-474c-9e74-0029dab2c6ff · outbound

This paper cites an unresolved cited work.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Unresolved cited work

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:01.594432Z digest=sha256:aabb8d0099631ecbfd4e8f9e55c3c627df71ba3f8d5b33ad7d36bc664846e3f1

Observation ae2f3ce2-0d86-4067-8fe7-e507f3cbd137 · outbound

This paper cites Scalable malware forensics using phy- logenetic analysis.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Scalable malware forensics using phy- logenetic analysis

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:04.821660Z digest=sha256:66141ac8051f39d2118d059395a14c77a910f16f2e0e3f74f7995cd4586530c8

Observation 557ebe79-cabc-4a0c-9aa2-b8625ec28baf · outbound

This paper cites Ida pro, 2025-02-28.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Ida pro, 2025-02-28

Reference 28

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:04.379017Z digest=sha256:624c862f0b2b97876791507b20b5edb029ce7a79948c6a090634a8255caa26b1

Observation b1fb3aa8-68c2-4129-88bb-2dc68651dc99 · outbound

This paper cites Distributed Representations of Sentences and Documents.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Distributed Representations of Sentences and Documents

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:05.054567Z digest=sha256:dd268e8660035e4a2c2299fb7e71f702f46c330d1acb9b6228793e9539554712

Observation 45e6a6ce-809e-4f97-b19f-cd848b86c6e2 · outbound

This paper cites Understanding security risks of embedded devices through fine-grained firmware fingerprinting.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Understanding security risks of embedded devices through fine-grained firmware fingerprinting

Reference 30

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no resolver link, observed 2026-08-04T14:49:05.158208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:05.158208Z digest=sha256:d5aa683fe5e0832f21a26984ff771cd54e6b41c374e28a9b19c69d9523edc2e0

Observation fe26ede1-c66e-4ebc-a21c-3c7a5a0566ea · outbound

This paper cites International Organization for Standardization, Geneva, Switzerland, February 2012.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity International Organization for Standardization, Geneva, Switzerland, February 2012

Reference 31

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source=pdf_text observed=2026-08-04T14:49:04.731564Z digest=sha256:89cc79be3df827be0a29f9b6d410b4b837dd293d48e61c0f095deb6393f6b35a

Observation 4301a5e5-d3d2-4aa4-b87b-eb5da1c8ecb6 · outbound

This paper cites A structured self-attentive sentence embedding,.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity A structured self-attentive sentence embedding,

Reference 32

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source=pdf_text observed=2026-08-04T14:49:05.641242Z digest=sha256:8bfc7fa31ef55ecefcb58e2828cc3d82de310f4519f1b6c16414375b9e16f401

Observation 4275a7cc-fb67-4b25-9283-3b52dc5876d0 · outbound

This paper cites Scaling Laws for Neural Language Models.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Scaling Laws for Neural Language Models

Reference 33

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source=pdf_text observed=2026-08-04T14:49:04.938009Z digest=sha256:245fe618622b4afc161ff3a238194202eefbf7b51874b833128967c1e0b9159f

Observation 2a0749d4-ab69-4e20-bdd8-b88dfa7778a3 · outbound

This paper cites Binary code similarity detection.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Binary code similarity detection

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:06.098365Z digest=sha256:93c87a526e309833349034e845f52c7f07b7840d1d48db083006329afb8b333f

Observation f37d9503-b33b-429c-81d2-386b3b688330 · outbound

This paper cites How machine learning is solving the binary function similarity problem.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity How machine learning is solving the binary function similarity problem

Reference 35

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:06.197443Z digest=sha256:24b0d59eb02954a9917d23632cd6bca414725bb382a1e2db19761cde3bfc5d2c

Observation 06176218-923a-49c4-a5b0-64403e9c4c49 · outbound

This paper cites Palmtree: Learn- ing an assembly language model for instruction em- bedding.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Palmtree: Learn- ing an assembly language model for instruction em- bedding

Reference 36

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source=pdf_text observed=2026-08-04T14:49:05.326189Z digest=sha256:3ef3a189547df195007888ab118b2b7d94054b4861cb2980c28a7ee5e2cbb805

Observation 9e2fb869-4501-4ea5-bdd8-1b88a8803505 · outbound

This paper cites Distributed Representations of Words and Phrases and their Compositionality.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Distributed Representations of Words and Phrases and their Compositionality

Reference 37

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:06.487992Z digest=sha256:d30cda31e35bd56095d701b4c56a267f37093da099d9608dbbfb55de0e74d2c6

Observation 57cb8f6c-f2b7-46fa-833d-7652d9caab37 · outbound

This paper cites GPT-4 Technical Report.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity GPT-4 Technical Report

Reference 38

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Unavailable: canonical work link unavailable.

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Observation 4583e315-cb4b-4beb-90a3-5a68d9b5b3bb · outbound

This paper cites Malware detection by exploiting deep learning over bi- nary programs.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Malware detection by exploiting deep learning over bi- nary programs

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Observation 6d73a372-7c58-445b-b73f-9dba6e4da768 · outbound

This paper cites Roberta: A robustly optimized bert pretraining approach,.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Roberta: A robustly optimized bert pretraining approach,

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Observation d02522cf-31eb-4e1e-82b6-12f61363a6e6 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity RoBERTa: A Robustly Optimized BERT Pretraining Approach

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Observation 50406123-8f0a-41ab-8a68-406668c44904 · outbound

This paper cites Penya, Borja Sanz, Carlos Laorden, and Pablo G.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Penya, Borja Sanz, Carlos Laorden, and Pablo G

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doi, observed 2026-08-04T14:53:31.255527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 8e5d947f-7fe8-43b9-b1a9-3356620ee4f5 · outbound

This paper cites Binary similarity detection using machine learning.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Binary similarity detection using machine learning

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Observation f6e6d405-2d6b-4f2c-a527-e79d628f865f · outbound

This paper cites Safe: Self-attentive function embeddings for binary similarity,.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Safe: Self-attentive function embeddings for binary similarity,

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source=pdf_text observed=2026-08-04T14:49:06.305886Z digest=sha256:d6811981cfd7858b9eebbc76598ac305bcddff1435822126ba76791d1aeaccca

Observation ff39d80c-8496-4843-8466-b3c13b0f76c7 · outbound

This paper cites SAFE: Self-Attentive Function Embeddings for Binary Similarity.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity SAFE: Self-Attentive Function Embeddings for Binary Similarity

Reference 45

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Source-reported events for the cited work

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Observation 644b2df5-1996-4bf9-9c77-4b55b011093a · outbound

This paper cites Putty, 2025-02-08.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Putty, 2025-02-08

Reference 46

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Source-reported events for the cited work

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Observation 9c5b00d2-7c23-4879-a113-81703e5e11ae · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 47

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source=pdf_text observed=2026-08-04T14:49:07.942663Z digest=sha256:a33d92e98d1e6aa6b0839ed33144c4f456d1b0926f07d5e370015cbe5d7fbecc

Observation 50928234-53a7-4fd6-a8bc-39791d0f72ab · outbound

This paper cites Gemma 3 Technical Report.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Gemma 3 Technical Report

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source=pdf_text observed=2026-08-04T14:49:08.048649Z digest=sha256:6bb65c3feb7e1e62d374626e17972b42b96443ba62fa8d6b27c23ca080278c3b

Observation 6243e0ef-bd37-493f-9e61-91f72975b3da · outbound

This paper cites Nicholas.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Nicholas

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source=pdf_text observed=2026-08-04T14:49:06.836234Z digest=sha256:35729194c17b299f23a7bc270407e25b4a0fa71d185c08b246876ed98c26ffcd

Observation 5e4d6614-5fce-4f8b-bf32-f0d058d966a4 · outbound

This paper cites VenkataKeerthy, Soumya Banerjee, Sayan Dey, Yashas Andaluri, Raghul PS, Subrahmanyam Kalyana- sundaram, Fernando Magno Quintão Pereira, and Ra- makrishna Upadrasta.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity VenkataKeerthy, Soumya Banerjee, Sayan Dey, Yashas Andaluri, Raghul PS, Subrahmanyam Kalyana- sundaram, Fernando Magno Quintão Pereira, and Ra- makrishna Upadrasta

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-04T14:49:08.322817Z digest=sha256:6880cbd3a5689defd7010bf9525292d5a7407b6eb9e2d63e8a612cb95e8360b1

Observation b7e5c1af-cfce-43d6-9dea-051a4c367aec · outbound

This paper cites A survey of binary code sim- ilarity detection techniques.Electronics, 13(9),.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity A survey of binary code sim- ilarity detection techniques.Electronics, 13(9),

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source=pdf_text observed=2026-08-04T14:49:07.097222Z digest=sha256:7b8c61c1518118363357e5a71c8e4433641cc125bdc803c98f6941d5a33fa195

Observation 0b4755e0-1974-4cf3-9667-59306107f4fe · outbound

This paper cites Clap: Learning transferable binary code representations with natural language su- pervision.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Clap: Learning transferable binary code representations with natural language su- pervision

Reference 52

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source=pdf_text observed=2026-08-04T14:49:08.583948Z digest=sha256:89ed4c3f74a5b26092748fcd28a75f9e2bf10bccd48d0c1cac1858ed7a4b5d59

Observation 9d2c96a1-2660-42ef-b570-47f073ed0c09 · outbound

This paper cites Improving ML-based binary function sim- ilarity detection by assessing and deprioritizing con- trol flow graph features.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Improving ML-based binary function sim- ilarity detection by assessing and deprioritizing con- trol flow graph features

Reference 53

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Observation 172085b0-8160-4a99-95eb-77ab8b099d7d · outbound

This paper cites Enhancing machine learning based malware detection model by reinforcement learning.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Enhancing machine learning based malware detection model by reinforcement learning

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source=pdf_text observed=2026-08-04T14:49:08.819956Z digest=sha256:99a53ea9427c06f2846bd843f174d00b1303ed408edc2cdfc31775c0deb2aab9

Observation 34e4b480-ece7-498c-8ec3-4d0df79497bf · outbound

This paper cites curl - command line tool and library for transferring data with urls, 2025-07-16.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity curl - command line tool and library for transferring data with urls, 2025-07-16

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source=pdf_text observed=2026-08-04T14:49:07.611901Z digest=sha256:75f41112a7c4233d78dda3d901fed76f799bd73d370eb3f38e84c42d634633c5

Observation d7eb5f2e-5a2b-494a-9962-6f11162792b8 · outbound

This paper cites LLM4Decompile: Decompiling binary code with large language models.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity LLM4Decompile: Decompiling binary code with large language models

Reference 56

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source=pdf_text observed=2026-08-04T14:49:07.707109Z digest=sha256:1bdc26f428114d8de59e41006ce4d3bb4c8b411f6e0e7213121fbbb2ab35706e

Observation 4405ff2f-3cfd-4314-9876-8aea8066ef16 · outbound

This paper cites Semantic understanding of source and bi- nary code based on natural language processing.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Semantic understanding of source and bi- nary code based on natural language processing

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source=pdf_text observed=2026-08-04T14:49:09.228049Z digest=sha256:7c4eb68e3d80ef4bfc7b6559aa0376ccd8e47e6a4843a4c3d2c9f73e1dd8f0e4

Observation 6d488a2b-d087-42d7-a1ff-a2b31cd4acba · outbound

This paper cites Qwen3 Technical Report.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Qwen3 Technical Report

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source=pdf_text observed=2026-08-04T14:49:08.198241Z digest=sha256:94cebf658de9b8ee1eb6e53ddec771b8551e0ea3dba70068aad039dc36c09b86

Observation 05c161da-3233-4c65-90b5-f0818c60d334 · outbound

This paper cites Busybox, 2024-09-27.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Busybox, 2024-09-27

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Observation 924e8caa-e678-4420-8b53-765a435d78ba · outbound

This paper cites Spain: Security patch anal- ysis for binaries towards understanding the pain and pills.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Spain: Security patch anal- ysis for binaries towards understanding the pain and pills

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source=pdf_text observed=2026-08-04T14:49:08.987203Z digest=sha256:33e508024ef672f5c77b3fb8b865a343348df79a0991fe8bcd200a78bb95bea0

Observation 759d76a4-23f7-46bf-bf48-333e94a35bac · outbound

This paper cites Order matters: Semantic- aware neural networks for binary code similar- ity detection.Proceedings of the AAAI Con- ference on Artificial Intelligence, 34(01):1145– 1152, Apr.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Order matters: Semantic- aware neural networks for binary code similar- ity detection.Proceedings of the AAAI Con- ference on Artificial Intelligence, 34(01):1145– 1152, Apr

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Observation ecfa3226-5e81-4ad0-a595-1f5d69cb9287 · outbound

This paper cites URL: https://www.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity URL: https://www

Reference 2014

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T14:49:03.560042Z digest=sha256:b09a9ea7430575aca2dcb3cf51c1d2adae73d0ec657a62b9ec7c929896e157f5

Observation 9c07ce34-f881-4927-8441-f4d298c90284 · outbound

This paper cites A Structured Self-attentive Sentence Embedding.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity A Structured Self-attentive Sentence Embedding

Reference 2017

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Source-reported events for the cited work

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Observation 48b564ce-e6fc-4c5d-8050-131d98d26af6 · outbound

This paper cites an unresolved cited work.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Unresolved cited work

Reference 2018

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T14:49:06.978193Z digest=sha256:507b254793daefe6424d7536fe5004933a3afc8fdffb7c7a3cc628b22f5f9ea6

Observation eed3e1f8-c664-4fac-b43e-b57059680328 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T14:49:02.830536Z digest=sha256:c34b4faccb98f7ecb83786f5c24f957726513c9076d38a93a13dc54215ef8e32

Observation 46f76aa7-b61e-467a-8242-8dd5062d2d9e · outbound

This paper cites doi: 10.1145/3460120.3484587.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity doi: 10.1145/3460120.3484587

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source=pdf_text observed=2026-08-04T14:49:05.481145Z digest=sha256:92d6b3ca8c258e08577eed65df03b97843be7f10c2d59b33c3c582b05dfa109a

Observation f1438e25-aaeb-4aac-8208-817e9bed46a0 · outbound

This paper cites an unresolved cited work.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity Unresolved cited work

Reference 2024

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no resolver link, observed 2026-08-04T14:49:07.237200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:49:07.237200Z digest=sha256:e19a397463920ae096e8b82455d9660a325a5d7a813b60d2c9555d843b0538f9

Observation 970ba9b8-827f-4b4a-9e78-6623962351f4 · outbound

This paper cites FuncVul: An Effective Function Level Vulnerability Detection Model using LLM and Code Chunk.

Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity FuncVul: An Effective Function Level Vulnerability Detection Model using LLM and Code Chunk

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T14:49:04.136085Z digest=sha256:de68f9a94dba50f3566a056486512b161f86242a576f7f9823fc8eec4857ca25

Pith citing papers

Observation 9beaa4a5-5eb9-44b0-b0f8-a9229d9795a4 · inbound

Practical Source Code Recovery from Binary Functions Using Anchor-Based Retrieval and LLM Reasoning cites this paper.

Practical Source Code Recovery from Binary Functions Using Anchor-Based Retrieval and LLM Reasoning Beyond Embeddings: Interpretable Feature Extraction for Binary Code Similarity

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T02:55:15.819959Z digest=sha256:48cf97e4ec2b1c73b37dac3cc006e33856c3643ddf43b894b214337d89533565