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Paper Citation Record · LEDGER

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code

As of 13 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2411.19508.

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

pith.paper-citation-record.v1
2411.19508 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:11:36.806692Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T09:27:30.923556Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T04:06:35.205093Z

Reference resolution

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5e51a35-4597-49cf-aff8-c0bde75e1e99 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:11:37.283961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.657427Z digest=sha256:dd805c51ec211e88e9d63f7d598038499311b7db45be5aa1a942a8e28de33ba5

Observation 5e176611-a17a-408b-a2e7-20cea136654c · outbound

This paper cites Report from GitHub Copilot.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Report from GitHub Copilot

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:11:37.268806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.662896Z digest=sha256:6a75a07c7073b339acd48f0314f1c05fa8b1b4018f45c8db3d41d374b7931c8c

Observation 24c6e1d0-2776-4c04-a52d-fafa3e67fd23 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:11:37.252035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.667699Z digest=sha256:9c7beeb182c513d694d7b85f46e60f5011e50a91026fd605d073e625dc35eb7d

Observation 60cedf89-8688-447c-b4b5-06ba28d6664b · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:11:37.236786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.672628Z digest=sha256:318401be6a962b16d64402ed5e1ce5bde349db28ec43ee59d2b1c7a235220e17

Observation 32e50709-84e5-49b2-85f9-12c3afe11a67 · outbound

This paper cites Program Synthesis with Large Language Models.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Program Synthesis with Large Language Models

Reference 5

Resolution
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no resolver link, observed 2026-08-12T10:11:36.677416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.677416Z digest=sha256:81a3cf9306d4718b4c9008914ffedd0fa92bb0c7a60cd284fc44ddb020965612

Observation 47013e9d-eb85-4766-bf41-7227eb39a0a4 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.682557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.682557Z digest=sha256:02c3034ea3e4768033deea92395d09df17d0d472dc4b827e4a335f4bc089455b

Observation 758ad416-19fe-4ffb-9e47-079cb3912e0e · outbound

This paper cites Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.692165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.692165Z digest=sha256:9bd1ade76f5ae389a4f5fc81729667d58e380c370655a7569829b091829a9317

Observation 44dd132b-ecd9-4ecc-9dea-3ec5f31bda47 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Evaluating Large Language Models Trained on Code

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.697514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.697514Z digest=sha256:e0a845d70a12dbaa23e175260d3bd31c3e4502f250a48f2bf17992ddaa34117f

Observation 3cc8e8d7-f2e1-4069-bfca-01a3a04a8371 · outbound

This paper cites GitHub Copilot AI pair programmer: Asset or Liability?.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code GitHub Copilot AI pair programmer: Asset or Liability?

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.702374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.702374Z digest=sha256:bfe1390f89a6f9029ecdf3888251ed139e5bc0fe53544bc917f4c4527e33cf24

Observation c38a164b-1df0-499b-81f5-64491e3b8805 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:11:37.212093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.707771Z digest=sha256:f6d81c80f8a706009e6d6d63621982cc4d2625f12a4693a35e9a5ec70c91a297

Observation dc41c418-5b38-455e-a7a4-593046b3f65c · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:11:37.196931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.712980Z digest=sha256:8e416a2511a6eb9baa0b9e26e6467b46e90964cbb254e1f0478a87335fe46860

Observation 221cb186-5c3f-4f67-9157-0e33f17aedd0 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:11:37.181913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.717853Z digest=sha256:bf40794f8843c24e82e6ae82b763aed7897212fd72d065f586dde5ef2d0394e6

Observation 711bec8c-5f76-46b9-bd3d-af48040302a6 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.722282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.722282Z digest=sha256:9eabecc2fb88141284b411fa7d58f43ea8b929e3fbbce6bf8b2e3d7cecc34da2

Observation 39817fe5-f8f1-4236-a0cf-44aa914561ab · outbound

This paper cites Double Backdoored: Converting Code Large Language Model Backdoors to Traditional Malware via Adversarial Instruction Tuning Attacks.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Double Backdoored: Converting Code Large Language Model Backdoors to Traditional Malware via Adversarial Instruction Tuning Attacks

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.732515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.732515Z digest=sha256:8e87b602838e45d2be4ab9e63d9063777fe3ec3103173d6d42699a527e626d64

Observation 73ffb548-e710-4639-9a05-ad192f0e6563 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:11:37.156251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.737030Z digest=sha256:7f6ed3a40270fe838684f668ec494860ae7cbcc99d44050c6bafd436a6ecb4b7

Observation ced1d4f6-c57a-4d83-a216-c0b75b43f2fd · outbound

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

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Gonzalez, Hao Zhang, and Ion Stoica

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.741516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.741516Z digest=sha256:a53d43366173b771e415c51cad595d9475f84020c32eedbefb088c74175087e5

Observation 3571b90c-4e5e-4526-abd9-170a0eeefd7b · outbound

This paper cites WizardCoder: Empowering Code Large Language Models with Evol-Instruct.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.746115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.746115Z digest=sha256:391072765ea75ca952c1d1deabdc99b609fb282a6e1b06b1505d82ad9bf4b052

Observation 887aace3-7094-4000-bff7-54c36b633ac1 · outbound

This paper cites OctoPack: Instruction Tuning Code Large Language Models.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code OctoPack: Instruction Tuning Code Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.752160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.752160Z digest=sha256:6b4a4468627fd6305d05908f29c6a8aa3c946923e68326f36feddfdcbf5d3bd6

Observation 6e4422f3-58d9-4a95-a750-a20c620d4e2b · outbound

This paper cites AI-assisted Code Authoring at Scale: Fine-tuning, deploying, and mixed methods evaluation.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code AI-assisted Code Authoring at Scale: Fine-tuning, deploying, and mixed methods evaluation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.757859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.757859Z digest=sha256:e0d1c85f2c9ab2a0cfd645fd971639bba04429cbacc4d941f0de825313fb15a0

Observation 1b255001-c7d5-497b-9b74-a2500f86fcbb · outbound

This paper cites GPT-4 Technical Report.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code GPT-4 Technical Report

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.763188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.763188Z digest=sha256:312b4bc55fc086c2f800669e8820355c5b02e871385fe57bcbcc43d09bab541e

Observation 5bfec20b-f944-4064-91ba-4b8281979614 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.768243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.768243Z digest=sha256:08fea21e10650e1a7b2975d4875479adb58d00042d890c47afa885411217f3ff

Observation e92b8190-c5bc-4cd3-94d9-2b28f4aedf5a · outbound

This paper cites Code Llama: Open Foundation Models for Code.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Code Llama: Open Foundation Models for Code

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.772818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.772818Z digest=sha256:1ce0db1b7ecae12c3102cebdd5c67d6cc9a30e19c2209cda0f1aa5a0ded4c5b9

Observation 232804cd-b04f-45ed-8372-16e12a0790e2 · outbound

This paper cites Universal Adversarial Triggers for Attacking and Analyzing NLP.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Universal Adversarial Triggers for Attacking and Analyzing NLP

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.777862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.777862Z digest=sha256:d4841128706f346ed0b092d2f2dc86a0b8d9d60a387dbbf5a79484c48bdb8594

Observation ac3b8ba5-34bf-4003-9753-747ca3ad7bb0 · outbound

This paper cites ReCode: Robustness Evaluation of Code Generation Models.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code ReCode: Robustness Evaluation of Code Generation Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.783381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.783381Z digest=sha256:b904442b9cc0bf2ab28bbbc1f7e2a320448ffa0570e354f166d39e9c8524ffef

Observation 7b581b6f-5324-4e79-b779-b68f9ba03e7e · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.788087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.788087Z digest=sha256:ccaf940606a1adcfcafb75f68e75973a5063ffb5510f18c2128c6b174b82fd44

Observation ace2bf8b-0f52-4219-a4ea-1aee9181bcb8 · outbound

This paper cites DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.793067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.793067Z digest=sha256:51ff5afb7a2b69672c8dbc8fcb860f6cba99aa0768afbbfa2a52a3bc55cbda2a

Observation f2e2daa1-137a-48a4-846a-4530d68dc843 · outbound

This paper cites Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.797628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.797628Z digest=sha256:e536723c4710774aba28090c5fc86d9c62fdbd6985c510f3f53401453ff59bbc

Observation 4414c005-b243-4a19-9e04-3d25fe1a6a58 · outbound

This paper cites an unresolved cited work.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:11:37.118605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:11:36.802314Z digest=sha256:b05bd2153b51ebb36e72d9a0d211acfb96482bce041dc01f9084ce878e9a9e68

Observation 6e2a9193-c780-4efd-8372-25aa9768d517 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.806692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.806692Z digest=sha256:8daad6e451dc68ddee26b32538fa4955987a0c25203e801c693ba68d3d48e0ad

Observation 739f996c-a09c-410e-8f9b-835b8c7e72c3 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.687387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.687387Z digest=sha256:8838a1d85cba999fc3b97677856047c98e6fb00d29947ef009e4a13e21324eef

Observation cfbac2a9-edd9-4ca2-871c-5f29a45f6215 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-12T10:11:36.726739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:11:36.726739Z digest=sha256:9c85ec8856cbd4dd8d4b0a288f03efd1dd5228d3359ffe6fb192b4f0564b868a

Pith citing papers

Observation e7e7fd07-f6fa-48a6-b43c-307d95fd11ed · inbound

Testing LLM Arithmetic Reasoning Generalization with Automatic Numeric-Remapping Attacks cites this paper.

Testing LLM Arithmetic Reasoning Generalization with Automatic Numeric-Remapping Attacks On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-02T04:06:35.206512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-28T09:27:30.923556Z digest=sha256:62132c851a0d0ee92319b1c77c11efe9a6256678cef15b5520085fa283a9c9ab