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Paper Citation Record · LEDGER

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

As of 19 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 8 inbound Pith citation observations for arXiv:2501.19282.

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

pith.paper-citation-record.v1
2501.19282 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:46:18.446065Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:38:57.785099Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T21:03:59.401697Z

Reference resolution

59 of 59 outbound references displayed

  • verified exact0
  • verified fuzzy56
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cb3b0360-6908-407c-9a05-b273d71262ab · outbound

This paper cites https://openai.com/index/dall-e-3/.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators https://openai.com/index/dall-e-3/

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:19.058853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.242329Z digest=sha256:051a65b1668d847d051ed8de5d5583a0a63f69920b2f6bc643ac996ca24b7fa5

Observation 9f80d91a-44a1-4243-afbb-66a9f0d1349a · outbound

This paper cites https://github.com/google/ honggfuzz.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators https://github.com/google/ honggfuzz

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:19.048150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.247179Z digest=sha256:ec225c48351be093bf27c1e9c7c815bf0f896b63889fc8225792b9d6afe0e8fb

Observation e4bca70e-5cc6-4d61-83aa-affeaa90efa6 · outbound

This paper cites On hardware security bug code fixes by prompting large language models.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators On hardware security bug code fixes by prompting large language models

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:19.038181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.251155Z digest=sha256:6302f26a22153ee5b7bce6bb2296f2cda6068a40ba6885e8fe0044b9fb0cb1c4

Observation da0268ea-7371-4c88-a887-bceba667a2b5 · outbound

This paper cites Sarid: Arabic storyteller using a fine-tuned llm and text-to-image generation.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Sarid: Arabic storyteller using a fine-tuned llm and text-to-image generation

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:19.028342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.255221Z digest=sha256:f1150c05950789f22e9590279079b137177372dbde5ba1d0c923454e325d5d9d

Observation f49fb228-35e6-4699-bf50-fa60ae631c85 · outbound

This paper cites Nautilus: Fishing for deep bugs with grammars.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Nautilus: Fishing for deep bugs with grammars

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:19.018166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.258779Z digest=sha256:23f48fd36a4bacc9242eacb94313f3834d746ce6b1eaaebecf70e3b5ed804212

Observation e3cb54c9-b438-4187-9510-45abf66ffcda · outbound

This paper cites Redqueen: Fuzzing with input-to-state correspondence.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Redqueen: Fuzzing with input-to-state correspondence

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:19.008733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.263146Z digest=sha256:b4290d4ef8b366d2f10d4f3a36731f94e386ea28ce0fd46dd0b3b8acf31d219d

Observation 187dd280-93f0-4e18-b40e-f333756c4d9e · outbound

This paper cites Fuzztruction: Using fault injection-based fuzzing to leverage implicit domain knowledge.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Fuzztruction: Using fault injection-based fuzzing to leverage implicit domain knowledge

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.998838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.267800Z digest=sha256:2f49c9a8197c92d0c4881a4e2b77b793906778a71b070236a7733bfed61882d2

Observation c7c2fdcf-b4bb-4f6e-b624-75d6eab5c365 · outbound

This paper cites {GRIMOIRE}: Synthesizing structure while fuzzing.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators {GRIMOIRE}: Synthesizing structure while fuzzing

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.989145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.271782Z digest=sha256:6669cedcb6ef197883fa497b21f0300829880f577941bde43d96cbf1ed51e308

Observation 213256cb-e866-460a-ba31-f0ae4db5b4fb · outbound

This paper cites Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.979904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.276042Z digest=sha256:61dced8b747b0fba781f161b4844cc1e216d190a0ef569e732e139c06f450a5c

Observation 7ebdd4e3-d577-4549-979b-50a592e37725 · outbound

This paper cites Large language models are edge-case genera- tors: Crafting unusual programs for fuzzing deep learn- ing libraries.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Large language models are edge-case genera- tors: Crafting unusual programs for fuzzing deep learn- ing libraries

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.969760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.279263Z digest=sha256:08206af940ed0d212c3f9ecb48f46ef4e3e1ea9bcace7f5aa7c259045b85f2a9

Observation 0ca78359-572d-469c-86e4-8b7704044689 · outbound

This paper cites Large language models of code fail at completing code with potential bugs.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Large language models of code fail at completing code with potential bugs

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.958900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.282920Z digest=sha256:af5a6e5ef8a3feb505357013c9af5c777aa3109e35ce523831d07289d4ac687b

Observation bb614cd4-1045-48b7-9392-56e7afa54135 · outbound

This paper cites Is “ai” useful for fuzzing? (keynote).

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Is “ai” useful for fuzzing? (keynote)

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.948147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.286099Z digest=sha256:6e94aec1adf90e3032fcace026d9ee17b91b2dbf1c8f8200301f5deb87537ed8

Observation c7cecd76-11d9-4d56-8c71-ea585c5c6beb · outbound

This paper cites For- matfuzzer: Effective fuzzing of binary file formats.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators For- matfuzzer: Effective fuzzing of binary file formats

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.938366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.289727Z digest=sha256:31d24c090a8f3e9e50a9975350d53f4654d73466313b08a4ea05b5f102bb2d5b

Observation ae06086c-3f0d-4680-8d8a-39fbe0eba0d9 · outbound

This paper cites Evolutionary grammar-based fuzzing.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Evolutionary grammar-based fuzzing

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.929423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.293447Z digest=sha256:892d7202bbe4ab300c703d92f480ac95fe5faa2a5d620ce978c2f2fbaee79ee1

Observation a62bc627-a75e-4b5a-843d-c38b2746abbc · outbound

This paper cites Weizz: Automatic grey-box fuzzing for struc- tured binary formats.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Weizz: Automatic grey-box fuzzing for struc- tured binary formats

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.918836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.296506Z digest=sha256:79db0a2390b7c89c41b136843735470b459232dbdeef7e9f4acddc55f3594b5d

Observation 01786e3b-39f5-4f5c-9454-94c0e4346bd2 · outbound

This paper cites {AFL++}: Combining incremental steps of fuzzing research.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators {AFL++}: Combining incremental steps of fuzzing research

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.908603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.299696Z digest=sha256:08c4498478104d742c079f87f1b67ce53433c314aa6ed6905413f8b785a4f0bb

Observation 61eb9ac2-121b-4d4f-b7f8-ea64655815de · outbound

This paper cites In USENIX Security, 2020.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators In USENIX Security, 2020

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.898661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.303355Z digest=sha256:ff1f79600fabda635b95f743f66a3a6e53a47659360599b249994a1b1e078d2b

Observation 23bb0809-a0a2-4fd8-8bce-71426732e85e · outbound

This paper cites Llm blueprint: En- abling text-to-image generation with complex and de- tailed prompts.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Llm blueprint: En- abling text-to-image generation with complex and de- tailed prompts

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.888970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.306416Z digest=sha256:9b8647c4b004d6281bf38f838c8c4e13c25876e29d9b4e25e7146050986f93c8

Observation 705382d8-3ee5-4807-b681-d3b9a2e47681 · outbound

This paper cites an unresolved cited work.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-09T20:46:18.879550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.309730Z digest=sha256:31a2db15ed245a0fbd7453991a89a1d631e02016dcb5ba55ce6cfbba12ead62c

Observation e546196b-61ce-4f7e-8c99-200ff679cebc · outbound

This paper cites Longcoder: A long-range pre-trained language model for code completion.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Longcoder: A long-range pre-trained language model for code completion

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.870311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.313568Z digest=sha256:2a5c76abce73a2b3a7bb2dab0077da6ee865706a72a1a29663e0b98ef64c7e39

Observation 0baac12d-e034-4734-afe0-e3d47e1ce0bf · outbound

This paper cites Gramfuzz: Fuzzing testing of web browsers based on grammar analysis and structural mutation.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Gramfuzz: Fuzzing testing of web browsers based on grammar analysis and structural mutation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.860434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.317512Z digest=sha256:4120afe7455ed6e39bd225747a3cbaaf1f78b8baadc7df896d448b2e97a18bf2

Observation 6442e12d-3c6a-47af-90da-4d5f9c479a71 · outbound

This paper cites Magma: A ground-truth fuzzing benchmark.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Magma: A ground-truth fuzzing benchmark

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.850664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.321586Z digest=sha256:7cb3140f06a792084f6e24559218b236d7224e2e9c2874707ebf1189f6534a6e

Observation a4358c98-e444-4634-8d4e-dfd3c8917697 · outbound

This paper cites Grammarinator: a grammar-based open source fuzzer.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Grammarinator: a grammar-based open source fuzzer

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.841161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.325371Z digest=sha256:0cf13d852f3d0d9003e7af2621fdd3ae96b6534db2e9c413fb970a7dddf1fbfc

Observation 0ff4e981-01cd-4810-b3e4-061dc4892950 · outbound

This paper cites Towards making the most of llm for translation quality estimation.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Towards making the most of llm for translation quality estimation

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.831528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.328491Z digest=sha256:dbe993e3b0590500f28d1733397021c6081ee96857ed4cc818b19ef52618a916

Observation 970bd67f-6892-4701-99a3-383ab12dd2cc · outbound

This paper cites Large language models strug- gle to learn long-tail knowledge.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Large language models strug- gle to learn long-tail knowledge

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.821709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.331685Z digest=sha256:d7edd3b52beefab3150140251635c8db87802ee03da117cc5cbf7712e241f6a6

Observation 9997c1de-b2d3-4c43-b76f-fb6053fef1a4 · outbound

This paper cites Learning to correct for qa reasoning with black-box llms.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Learning to correct for qa reasoning with black-box llms

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.811359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.335376Z digest=sha256:e2c37dc4596121f02ee9ee09b3d2279ebe283e857ecb33de8b456d36e0dfc1b0

Observation 6029a099-9877-4c49-b396-4eb8b431bc81 · outbound

This paper cites Saffron: Adaptive grammar-based fuzzing for worst-case analy- sis.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Saffron: Adaptive grammar-based fuzzing for worst-case analy- sis

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.801648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.338466Z digest=sha256:adc6347586e71a3efd4ec611034e608ee1ca38a76137e438392f23e720e1c8ac

Observation 49284c65-a389-407e-bfb7-4ab82e9ae00e · outbound

This paper cites Fairfuzz: A tar- geted mutation strategy for increasing greybox fuzz test- ing coverage.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Fairfuzz: A tar- geted mutation strategy for increasing greybox fuzz test- ing coverage

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.792059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.341695Z digest=sha256:04cdd5ea699aaad617ddbd75f5e006715cab22904d7050e5c3f9b577691fdb9e

Observation f28c9d04-8077-4746-a6a4-a39e47282ce5 · outbound

This paper cites Clip-event: Connecting text and images with event structures.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Clip-event: Connecting text and images with event structures

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.782338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.344722Z digest=sha256:1ba5feb851f7d5baef4796e55db48cb1e841f706923b6a6d2eee90d91af54805

Observation 235b6734-f6bf-4c83-90f5-3b1d096ba9b9 · outbound

This paper cites {UNIFUZZ}: A holistic and pragmatic {Metrics-Driven} platform for evaluating fuzzers.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators {UNIFUZZ}: A holistic and pragmatic {Metrics-Driven} platform for evaluating fuzzers

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.771689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.347797Z digest=sha256:e7db7fdabecb441cd218b233405be2123037b02f6e3030b14e6608fc6caffd18

Observation ccf063b3-1c83-4c59-9eb8-0cded2ffa5ca · outbound

This paper cites Multi-task learning based pre-trained language model for code com- pletion.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Multi-task learning based pre-trained language model for code com- pletion

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.761619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.350797Z digest=sha256:ef41a5fd6a6fe2816a5cf406a068add78013765c53fce552871858d7d5e5a8a4

Observation 7dc46a65-8aa9-4c57-bc8d-5312750642e5 · outbound

This paper cites Fuzzinmem: Fuzzing pro- grams via in-memory structures.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Fuzzinmem: Fuzzing pro- grams via in-memory structures

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.751638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.353911Z digest=sha256:a4803363ea636ee07f3cc1a58476ab8ca8359302d7d7997528f17206636c1dab

Observation 781e7a72-86ae-46f9-8101-82c65362fd28 · outbound

This paper cites Vd-guard: Dma guided fuzzing for hypervisor virtual device.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Vd-guard: Dma guided fuzzing for hypervisor virtual device

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.740415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.356931Z digest=sha256:d588ffadd567fcc5f779662d5292905b732153d7ce6bf4ae5bcae0d1296e201e

Observation 46e05f99-bf4a-4824-be18-1b198efa7028 · outbound

This paper cites Llmscore: Unveiling the power of large language models in text-to-image synthesis evalu- ation.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Llmscore: Unveiling the power of large language models in text-to-image synthesis evalu- ation

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.730571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.360374Z digest=sha256:66555fd39dbcebd03fdc3261fbd467433827303dfe2f945e8005602df8d0446a

Observation 17371e13-9d0f-46b7-a3ec-1b8e80c6b4e4 · outbound

This paper cites {MOPT}: Op- timized mutation scheduling for fuzzers.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators {MOPT}: Op- timized mutation scheduling for fuzzers

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.719968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.363489Z digest=sha256:1ebb27b164af7b4d585ba01efde20a54ec2367c920d068687ac43a899b6a594f

Observation 2c10bc42-0583-4919-a120-b9f485f99942 · outbound

This paper cites Ems: History-driven mutation for coverage-based fuzzing.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Ems: History-driven mutation for coverage-based fuzzing

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.709106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.367075Z digest=sha256:e48c1fa61591442738fe2271a83fd3d90c2120d382eec7bf24e9e43847365b81

Observation b70810a5-a768-4a12-9933-07129eeb86db · outbound

This paper cites Large language model guided proto- col fuzzing.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Large language model guided proto- col fuzzing

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.697370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.370971Z digest=sha256:9faec45ecbab2510c7c9715b277739476fa8c8dcd33c590dc03cd7df4ae3054a

Observation 895b7da8-b923-4f2d-a672-5b5e9e413e46 · outbound

This paper cites Fuzzbench: an open fuzzer benchmarking platform and service.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Fuzzbench: an open fuzzer benchmarking platform and service

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.685978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.374530Z digest=sha256:2b54581ed7037a7b3df04ecc7dcec1578c5137f6b17c498974e88868f438baa2

Observation 56ec3f1c-419b-45d6-b1a9-1f6a447951e7 · outbound

This paper cites Fuzzing javascript engines with aspect- preserving mutation.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Fuzzing javascript engines with aspect- preserving mutation

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.674769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.377581Z digest=sha256:e1b2e05812c3d67660e0245cb441d465100fbaa92c4a5098a63f1a1736230b2d

Observation 80fcee67-a725-4c16-9c86-7110f79e24de · outbound

This paper cites Examining zero-shot vulnerability repair with large language mod- els.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Examining zero-shot vulnerability repair with large language mod- els

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.663391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.380868Z digest=sha256:a8a96c4e69e7600a1101fed4d68b9a64dfcb64708e56c3737cb6242d6c37728a

Observation 798fc478-19b1-4cc1-8664-dbae89a6c7bf · outbound

This paper cites Smart greybox fuzzing.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Smart greybox fuzzing

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.652392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.384960Z digest=sha256:f4b21b474effffe80028a8709f8d51e5a46af9b8a2c4cbe3b0e60ff03ac645ff

Observation e7d68600-543b-426d-8bca-8b74a4888f79 · outbound

This paper cites On extractive and abstractive neu- ral document summarization with transformer language models.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators On extractive and abstractive neu- ral document summarization with transformer language models

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.641421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.388136Z digest=sha256:150c26549c3ede941a1302196cbe6405140658e03a6f5df8dc85ff77bb901d36

Observation e15a6b0c-70a5-4024-870f-905fdbb11b54 · outbound

This paper cites Unified text-to-image generation and retrieval.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Unified text-to-image generation and retrieval

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.631534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.391167Z digest=sha256:14440cc2f2da4f0821dbbea0b82162cd5acc0130b07d4738fb5924b8d9671640

Observation 9ba05312-5041-4f40-93cd-e4e062a8848a · outbound

This paper cites Zero-shot text-to-image generation.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Zero-shot text-to-image generation

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-09T20:46:18.394738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:46:18.394738Z digest=sha256:13984ceb450772de970bb53f3768af62d22dbce7598057a5bbd4daca1b9aa584

Observation 37b517d0-a633-4e04-a8e4-996cfba5eb88 · outbound

This paper cites The battle of llms: A comparative study in conversational qa tasks.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators The battle of llms: A comparative study in conversational qa tasks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.616061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.398018Z digest=sha256:f01df65355b14bad53acedbe958c0e1446e6b09d193f54025833320fd3d66007

Observation 15c2fcf1-0bb7-418b-ae48-8072796189cf · outbound

This paper cites Unsupervised llm adaptation for question answering.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Unsupervised llm adaptation for question answering

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.606700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.401593Z digest=sha256:5b4f5f36dfebe1824f8d9ac60903fb61e78e0f3eb80e20bf4f902dd5cfd145ee

Observation d5fd38e4-ccb0-4cc5-8dff-1823fb64df1c · outbound

This paper cites Grammar-based fuzzing.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Grammar-based fuzzing

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.596149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.405145Z digest=sha256:08f15ec394ff9a035c2a77b34eee72b5b3d62972576e2961b9b33bc83da4f8dc

Observation 0f6d51d6-7afa-449d-8604-2e855ac6dc3b · outbound

This paper cites Fox: Coverage-guided fuzzing as online stochastic control.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Fox: Coverage-guided fuzzing as online stochastic control

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.586629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.408759Z digest=sha256:9b42eff889d68ddbef0822299a8766d7cdaca2d2eaf2b6eab82aac3327612212

Observation c35969e6-776c-4e15-a686-e8c2c2697ed3 · outbound

This paper cites Gramatron: Ef- fective grammar-aware fuzzing.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Gramatron: Ef- fective grammar-aware fuzzing

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.576717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.412434Z digest=sha256:a0a53c9f96c795e27621a96c3c0ebdd4187480301e7082c52785aead14c2d384

Observation f525bfcd-e3a6-498e-bda0-3af63452512e · outbound

This paper cites Evaluating large lan- guage models on medical evidence summarization.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Evaluating large lan- guage models on medical evidence summarization

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.566322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.416124Z digest=sha256:66721186a7a1440e43e04bff7f80187a5d7e6e87aa119a7dc30549c78c9eb5d6

Observation 66cb5f1b-97cb-488e-aa67-88fcc21adcdf · outbound

This paper cites Supe- rion: Grammar-aware greybox fuzzing.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Supe- rion: Grammar-aware greybox fuzzing

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.555020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.419263Z digest=sha256:21934116bee90728bf3ebdb51dd03ea70a11b96792cada6d64c4d2a86cfcf848

Observation d0b52948-4804-4f1f-b19f-d4098931d163 · outbound

This paper cites Self-instruct: Aligning language model with self generated instructions.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Self-instruct: Aligning language model with self generated instructions

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.542894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.423038Z digest=sha256:88e3c15c24a0eb88c3ca6b1522442f4990e957bd51da63b23ee535b350ae99b6

Observation bd0dfdf0-b2ff-453f-96a9-b06bef53815d · outbound

This paper cites Fuzz4all: Uni- versal fuzzing with large language models.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Fuzz4all: Uni- versal fuzzing with large language models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.532673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.426365Z digest=sha256:fa5219d3777d28fcb7a21b25447345ed92794eb82aacdb4191c8763070db9e10

Observation 464a7c9e-dc09-4fae-a1c8-3371403d7509 · outbound

This paper cites A systematic evaluation of large lan- guage models of code.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators A systematic evaluation of large lan- guage models of code

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.522149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.429365Z digest=sha256:a53396261e797f1a4ce726b9c066a68c7992a35d29724d7edfb0f980a9171562

Observation cabdbcf8-ff8c-4e9d-b0ec-ec42e540726c · outbound

This paper cites Pro- fuzzer: On-the-fly input type probing for better zero-day vulnerability discovery.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators Pro- fuzzer: On-the-fly input type probing for better zero-day vulnerability discovery

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.511592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.432569Z digest=sha256:75909240c200c2ca8bbcaf7c24e25e9f3af654fbc14a52cd18947814d92c043f

Observation 03c0067f-4b30-483c-831f-3d0bcc9e8e85 · outbound

This paper cites {EcoFuzz}: Adaptive {Energy- Saving} greybox fuzzing as a variant of the adversarial {Multi-Armed} bandit.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators {EcoFuzz}: Adaptive {Energy- Saving} greybox fuzzing as a variant of the adversarial {Multi-Armed} bandit

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.501167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.435817Z digest=sha256:ef9364d0fc5daa45a855ed18bc28a52cbc98b34a54c2cdda9d1fa7c40f92720f

Observation b28e403f-5c79-4337-943a-e15ab5c34e5a · outbound

This paper cites American fuzzy lop, 2017.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators American fuzzy lop, 2017

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-09T20:46:18.438949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:46:18.438949Z digest=sha256:b6c8d7264cc9e9ce403dd30229851b89f2a43780463c1c3bd4bccfb340fc629d

Observation 09ad714f-fb1e-4501-9a66-afd49759a4c1 · outbound

This paper cites unparsed.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators unparsed

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.483783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.442067Z digest=sha256:e6f1cffaeb7f46c2dde342bdac99da6db0ab57e01ce3e1a331818877797366f8

Observation 4f202aec-a11c-4ec3-8578-4faa60af514f · outbound

This paper cites default features describing the target format.

Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators default features describing the target format

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:46:18.472745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-09T20:46:18.446065Z digest=sha256:e92487c2f190906af7a0be269012c53d1d39c395b12aa1df8d414a0b9abd0a8a

Pith citing papers

Observation 94265197-348d-41eb-93a8-afb86d395450 · inbound

IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems cites this paper.

IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T20:38:57.785099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:57.785099Z digest=sha256:7d505b51be291622cbe357992e093c304c6868925652c0705de58d80b4293bb4

Observation 99a6730c-09dd-4df6-9aa2-a15b599d4e4d · inbound

RAG or Fine-tuning? A Comparative Study on LCMs-based Code Completion in Industry cites this paper.

RAG or Fine-tuning? A Comparative Study on LCMs-based Code Completion in Industry Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:39.729227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:25:39.729227Z digest=sha256:d289246e9ee4a3c5b491edbbff99ec5c9fe434dcad5a94cb61e759504be30625

Observation a1a95c35-eb97-4e30-a183-b519f6507979 · inbound

ZTaint-Havoc: From Havoc Mode to Zero-Execution Fuzzing-Driven Taint Inference cites this paper.

ZTaint-Havoc: From Havoc Mode to Zero-Execution Fuzzing-Driven Taint Inference Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T05:06:57.322780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:06:57.322780Z digest=sha256:6a81a0692845237f00085c3ec531780d8cf4f823f896f23fc4a4a78d55616e4f

Observation ca8258de-fbaf-4781-9cf8-20c235142471 · inbound

Reasoning as a Resource: Optimizing Fast and Slow Thinking in Code Generation Models cites this paper.

Reasoning as a Resource: Optimizing Fast and Slow Thinking in Code Generation Models Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T04:54:20.438580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:54:20.438580Z digest=sha256:d62a5917612c99c7fec57fa2295650668d59d8bb374b72ee079119e222323f7b

Observation df35b2bc-d5b2-44e2-929d-a44a29a9fa90 · inbound

Position Paper: Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps cites this paper.

Position Paper: Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T18:07:13.053523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:07:13.053523Z digest=sha256:5c1b55634022b205812836388aebb6d2aec7a776889a4b96fab1b5849365e298

Observation 7aa12c0d-9953-4d7b-aa9d-bf045dfe5d63 · inbound

Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing cites this paper.

Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:56:05.749609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T02:35:55.075730Z digest=sha256:78f410d9854b2c825a73fc542867f00ce0117f1e6fd43356700fd38d0bf3690c

Observation 9e80ce22-4e55-46b6-ac74-2f4c4793067d · inbound

FuzzPilot: Plateau-Triggered Recipe Validation for Structured Text Fuzzing cites this paper.

FuzzPilot: Plateau-Triggered Recipe Validation for Structured Text Fuzzing Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-06-29T21:03:59.402972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-29T20:39:23.520700Z digest=sha256:257574ef1da7bee308142e6d03355d0f637d10b6a50c74d880fb1f0e6f1a7868

Observation 108e8a82-7f86-486f-979d-abb9df2084e9 · inbound

From Documentation to Zero-day Vulnerabilities: LLM-Driven Fuzzing of JavaScript Engines in PDF Readers cites this paper.

From Documentation to Zero-day Vulnerabilities: LLM-Driven Fuzzing of JavaScript Engines in PDF Readers Low-Cost and Comprehensive Non-textual Input Fuzzing with LLM-Synthesized Input Generators

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