Paper Citation Record · LEDGER

Adversarial Text Generation with Dynamic Contextual Perturbation

As of 7 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2506.09148.

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

pith.paper-citation-record.v1
2506.09148 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:00:56.854471Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

verified exact1
verified fuzzy17
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 21dc6890-ca83-4189-bad7-df7ce40fc421 · outbound

This paper cites Intriguing properties of neural networks.

Adversarial Text Generation with Dynamic Contextual Perturbation Intriguing properties of neural networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.160225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9b83410a-031a-4bd4-8c5a-7038da197ba5 · outbound

This paper cites Explaining and harnessing adversarial examples.

Adversarial Text Generation with Dynamic Contextual Perturbation Explaining and harnessing adversarial examples

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.150345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 219da673-5625-4e14-aecb-d575b3bdad4f · outbound

This paper cites Generating natural language adversarial examples.

Adversarial Text Generation with Dynamic Contextual Perturbation Generating natural language adversarial examples

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.140780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e8039b08-5823-47f5-bdaa-ff114c435a7e · outbound

This paper cites Are synonym substitution attacks really synonym substitution attacks?.

Adversarial Text Generation with Dynamic Contextual Perturbation Are synonym substitution attacks really synonym substitution attacks?

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.131177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 74a51cca-b41c-43b7-8acb-359328ade577 · outbound

This paper cites A semantic, syntactic, and context -aware natural language adversarial example generator.

Adversarial Text Generation with Dynamic Contextual Perturbation A semantic, syntactic, and context -aware natural language adversarial example generator

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.121488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 10e52d76-df95-4806-9efd-0fd3e94637e7 · outbound

This paper cites Adversarial Evasion Attack Efficiency against Large Language Models.

Adversarial Text Generation with Dynamic Contextual Perturbation Adversarial Evasion Attack Efficiency against Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:00:56.779798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5fe338a-1872-4578-9538-4e2395f9840a · outbound

This paper cites Word -level textual adversarial attack method based on differential evolution algorithm,.

Adversarial Text Generation with Dynamic Contextual Perturbation Word -level textual adversarial attack method based on differential evolution algorithm,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.111750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 15b334ef-6442-4d9f-bd08-374c675587a9 · outbound

This paper cites Towards query-limited adversarial attacks on graph neural networks,.

Adversarial Text Generation with Dynamic Contextual Perturbation Towards query-limited adversarial attacks on graph neural networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.101741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7fd77f9-a993-4067-8cb2-9b1e1028af9a · outbound

This paper cites FastTextDodger: Decision-based adversarial attack against black - box NLP models with extremely high efficiency,.

Adversarial Text Generation with Dynamic Contextual Perturbation FastTextDodger: Decision-based adversarial attack against black - box NLP models with extremely high efficiency,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.091596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 543ee702-0227-4396-8e12-d49db666813c · outbound

This paper cites Analyzing Adversarial Attacks on Sequence-to-Sequence Relevance Models.

Adversarial Text Generation with Dynamic Contextual Perturbation Analyzing Adversarial Attacks on Sequence-to-Sequence Relevance Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:00:56.796212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa74e983-35ce-40b8-90b4-4f49b2091ead · outbound

This paper cites A modified word saliency - based adversarial attack on text classification models,.

Adversarial Text Generation with Dynamic Contextual Perturbation A modified word saliency - based adversarial attack on text classification models,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.080968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 450ee00c-8d49-4673-a3fd-d9d45f55788f · outbound

This paper cites Saliency attention and semantic similarity-driven adversarial perturbation,.

Adversarial Text Generation with Dynamic Contextual Perturbation Saliency attention and semantic similarity-driven adversarial perturbation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.071087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 944aa7e5-f61c-4e0c-9b4a-0dd68efadb31 · outbound

This paper cites Generating natural language adversarial examples through probability weighted word saliency ,.

Adversarial Text Generation with Dynamic Contextual Perturbation Generating natural language adversarial examples through probability weighted word saliency ,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.059756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fae4d170-6a59-4d14-b2e2-09a158c8363e · outbound

This paper cites BERT -Attack: Adversarial attack against BERT using BERT,.

Adversarial Text Generation with Dynamic Contextual Perturbation BERT -Attack: Adversarial attack against BERT using BERT,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.048899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 538743d1-4f3a-4988-9b19-0715708c997e · outbound

This paper cites Convolutional neural networks for sentence classification,.

Adversarial Text Generation with Dynamic Contextual Perturbation Convolutional neural networks for sentence classification,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.038012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 404a2fa9-6c65-4c00-a507-561c093c76b0 · outbound

This paper cites Bidirectional LSTM networks for improved phoneme classification and recognition ,.

Adversarial Text Generation with Dynamic Contextual Perturbation Bidirectional LSTM networks for improved phoneme classification and recognition ,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.027270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9661619a-2145-4d8a-bb40-21a5827cbc2d · outbound

This paper cites Character -level Convolutional Networks for Text Classification,.

Adversarial Text Generation with Dynamic Contextual Perturbation Character -level Convolutional Networks for Text Classification,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:57.016434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 638b7d89-febb-4bf3-9f05-b9c80966fec4 · outbound

This paper cites Text Understanding from Scratch.

Adversarial Text Generation with Dynamic Contextual Perturbation Text Understanding from Scratch

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:00:56.913181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ff88fa59-9fdb-44cc-8714-6a691e5723a2 · outbound

This paper cites an unresolved cited work.

Adversarial Text Generation with Dynamic Contextual Perturbation Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:00:57.003982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4b75cf7e-9a9a-4605-be49-39fcde11f85f · outbound

This paper cites an unresolved cited work.

Adversarial Text Generation with Dynamic Contextual Perturbation Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:00:56.991540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fe6471da-8f70-4787-8798-c6780ef2e8d0 · outbound

This paper cites Fake news,.

Adversarial Text Generation with Dynamic Contextual Perturbation Fake news,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:56.980367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1018edc9-adca-4400-ae71-b0ed4a6cde25 · outbound

This paper cites A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.

Adversarial Text Generation with Dynamic Contextual Perturbation A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T05:00:56.839336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 736547d3-c966-4f6f-b1ed-3bff686f80f9 · outbound

This paper cites an unresolved cited work.

Adversarial Text Generation with Dynamic Contextual Perturbation Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:00:56.967928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 16f1e2cf-85c4-43c1-9d6e-778e0a611b99 · outbound

This paper cites Long short-term memory.

Adversarial Text Generation with Dynamic Contextual Perturbation Long short-term memory

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:00:56.955483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 68186a8c-045a-4fe5-8baf-73190fe8e89e · outbound

This paper cites an unresolved cited work.

Adversarial Text Generation with Dynamic Contextual Perturbation Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:00:56.944574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 18c1400a-d0eb-47f6-ac84-19d653b48a3a · outbound

This paper cites Enhanced LSTM for Natural Language Inference.

Adversarial Text Generation with Dynamic Contextual Perturbation Enhanced LSTM for Natural Language Inference

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T05:00:56.854471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.