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Paper Citation Record · LEDGER

Confidence Elicitation: A New Attack Vector for Large Language Models

As of 23 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 0 inbound Pith citation observations for arXiv:2502.04643.

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

pith.paper-citation-record.v1
2502.04643 v2

Coverage vector

measured 73 of 73 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T22:06:39.050277Z

measured 73 of 73 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

73 of 73 outbound references displayed

  • verified exact8
  • verified fuzzy19
  • unresolved45
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b06ff1ef-cc73-47e3-bf4c-128628083815 · outbound

This paper cites an unresolved cited work.

Confidence Elicitation: A New Attack Vector for Large Language Models Unresolved cited work

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.786466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.786466Z digest=sha256:23a7f56b1ee03da0457fb780f50a688f4a6795a963a6d2384fb338ef87900672

Observation 9d78a881-b929-4b82-b8f6-6469f15a48ef · outbound

This paper cites Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei W Koh, Daphne Ippolito, Florian Tramer, and Ludwig Schmidt.

Confidence Elicitation: A New Attack Vector for Large Language Models Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei W Koh, Daphne Ippolito, Florian Tramer, and Ludwig Schmidt

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.879718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.790888Z digest=sha256:c00a6d054f9f1237f533100d8235f79534a107e55d5b3768cc155da338eeed52

Observation 13509d42-e3dc-46ba-a3a4-e80328a353ef · outbound

This paper cites Universal Sentence Encoder.

Confidence Elicitation: A New Attack Vector for Large Language Models Universal Sentence Encoder

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.795141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.795141Z digest=sha256:c5b6bb59e47b0481cf95e29d5f3d8d092713fcffbf6b6969d0c8cf120b2205e6

Observation 6f5518d8-9e12-4b3c-ab47-27144f0e0c99 · outbound

This paper cites Pappas, and Eric Wong.

Confidence Elicitation: A New Attack Vector for Large Language Models Pappas, and Eric Wong

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.799248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.799248Z digest=sha256:4a6639ab689fa393698d71b265c1ff161b810cdb05356ff542af11d2e15985d6

Observation 698754f5-71db-40fe-9147-92c75dbee5aa · outbound

This paper cites Finetuning Language Models to Emit Linguistic Expressions of Uncertainty.

Confidence Elicitation: A New Attack Vector for Large Language Models Finetuning Language Models to Emit Linguistic Expressions of Uncertainty

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.802830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.802830Z digest=sha256:85065d0ec3cb58fbb286068a5e21fcb61e420100314d19e47335561a3ccdaab2

Observation f747824e-f6cf-402f-841d-310002afad40 · outbound

This paper cites BERT : Pre-training of deep bidirectional transformers for language understanding.

Confidence Elicitation: A New Attack Vector for Large Language Models BERT : Pre-training of deep bidirectional transformers for language understanding

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.806757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.806757Z digest=sha256:b5eae19714e9793efb2362740691301bf21fa5ba6873f52ba17ac1031e78bc5c

Observation 0105b3d3-142b-445d-940d-862a4c6102c8 · outbound

This paper cites Towards robustness against natural language word substitutions.

Confidence Elicitation: A New Attack Vector for Large Language Models Towards robustness against natural language word substitutions

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.861734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.810657Z digest=sha256:a0dbfa974ceab897cb4cc59d8038a15f66eee05cb49bd8ebb3234623457fe7be

Observation ff964c0e-4dec-4fd9-8d9e-96eef66c61f7 · outbound

This paper cites Towards Robustness Against Natural Language Word Substitutions.

Confidence Elicitation: A New Attack Vector for Large Language Models Towards Robustness Against Natural Language Word Substitutions

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-08T22:07:24.575044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.814057Z digest=sha256:f6457a6d8d1c88eca445d12c32fa29e64f82f6532c1634d9b0f7ee97cb9274ea

Observation 557450ae-0a2c-4b93-b625-7500fe980c65 · outbound

This paper cites H ot F lip: White-box adversarial examples for text classification.

Confidence Elicitation: A New Attack Vector for Large Language Models H ot F lip: White-box adversarial examples for text classification

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.817712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.817712Z digest=sha256:8340e40e2ddc73d18e1d499e3c6d3ccb5d68332fee8503b413c472445e443385

Observation 1878716a-2ee4-41ab-85b1-e5a46d1f514b · outbound

This paper cites o zde G \.

Confidence Elicitation: A New Attack Vector for Large Language Models o zde G \

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.850770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.821288Z digest=sha256:548dc5e3d4b9bf16ec5ecf6ca52f0f5ab94ba59bc8ec16e8339ca68b8725e581

Observation faaf7918-2760-45d2-875d-41120c98f2c1 · outbound

This paper cites Special symbol attacks on nlp systems.

Confidence Elicitation: A New Attack Vector for Large Language Models Special symbol attacks on nlp systems

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.824941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.824941Z digest=sha256:4e4809947c9871b799d520dd15635fe7c8af9305bb471a41049ada2626afcc86

Observation 79102f9c-7e52-4b15-b45c-47f1a5845976 · outbound

This paper cites Using punctuation as an adversarial attack on deep learning-based NLP systems: An empirical study.

Confidence Elicitation: A New Attack Vector for Large Language Models Using punctuation as an adversarial attack on deep learning-based NLP systems: An empirical study

Reference 12

Resolution
verified exact
doi, observed 2026-08-08T22:06:39.243622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.828361Z digest=sha256:7d1fbc43af49678aeb388fa0109040f47d35ff947f43d6293c37b1e8dc65f82b

Observation 554d9ae5-9e89-4a8d-8989-a237fb7c291d · outbound

This paper cites S em R o D e: Macro adversarial training to learn representations that are robust to word-level attacks.

Confidence Elicitation: A New Attack Vector for Large Language Models S em R o D e: Macro adversarial training to learn representations that are robust to word-level attacks

Reference 13

Resolution
verified exact
doi, observed 2026-08-08T22:07:24.840072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.831769Z digest=sha256:f9cea32bb71ed5ef14aa7ed463495a8db22f58a06e1ba382d4011a2a84276c01

Observation 651766c1-64e2-4ee2-a943-b1632ffd0f2a · outbound

This paper cites Reasoning robustness of LLM s to adversarial typographical errors.

Confidence Elicitation: A New Attack Vector for Large Language Models Reasoning robustness of LLM s to adversarial typographical errors

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.835312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.835312Z digest=sha256:45ad2ad68d1c367da5c19e2051f09d7ba7a7632b46605ff841d4d4413924fd22

Observation 318cd17a-cb4b-4cbd-8a52-24675324cfeb · outbound

This paper cites Improving the robustness of question answering systems to question paraphrasing.

Confidence Elicitation: A New Attack Vector for Large Language Models Improving the robustness of question answering systems to question paraphrasing

Reference 15

Resolution
verified exact
doi, observed 2026-08-08T22:06:39.225930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.838746Z digest=sha256:f057da12d4d03b6fedb066c436aa3ed5c8ad685e40c8ac9a8b1651c1494ecdb6

Observation 1a62c797-d0f2-4036-abc4-36d2fa0c4b57 · outbound

This paper cites Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies.

Confidence Elicitation: A New Attack Vector for Large Language Models Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.841995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.841995Z digest=sha256:d849baedcd0200510f1240175addd77ef397c49323a5d6a6be762da32f10545e

Observation f6a6f372-b76c-4e68-816c-a5f989fc19be · outbound

This paper cites Buelow, Rupert Langer, Bastian Dislich, Peter Boor, Volkmar Schulz, and Jakob Nikolas Kather.

Confidence Elicitation: A New Attack Vector for Large Language Models Buelow, Rupert Langer, Bastian Dislich, Peter Boor, Volkmar Schulz, and Jakob Nikolas Kather

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.829538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.845472Z digest=sha256:abf07db584ad07181fb92fc4905c05b7cf8ab9d7561650db44544f1cd497d1e7

Observation 4bc83bd7-03db-49b4-bc60-21748889d076 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Confidence Elicitation: A New Attack Vector for Large Language Models Explaining and Harnessing Adversarial Examples

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.848950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.848950Z digest=sha256:c499490059a9fd08347c0e108ee6c33f664f2a5fd0383b7d13cae96b4bfee928

Observation 67c9e2f2-fe89-4d1e-aafe-f34da834eaab · outbound

This paper cites Weinberger.

Confidence Elicitation: A New Attack Vector for Large Language Models Weinberger

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.820356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.853079Z digest=sha256:6b981309f4db0ce65afcc38cc126d3ce66da0f0ea8b9e89b7a293961b81bae8a

Observation 23e68a1c-ffa6-40a4-bc1c-a6b263fae991 · outbound

This paper cites Weinberger.

Confidence Elicitation: A New Attack Vector for Large Language Models Weinberger

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.811122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.856702Z digest=sha256:4562d4f9e1a15b08e3aaee0bbb9a7296660c4231c3a62335790bbaf4639eb4d6

Observation 186e16d7-425a-4409-b80b-e489ede6ae96 · outbound

This paper cites Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation.

Confidence Elicitation: A New Attack Vector for Large Language Models Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.860489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.860489Z digest=sha256:09c32cbbd09bcffe930c7fae3e2504c83e7beac6052894b971229cee4aad217a

Observation 74b954e2-70f9-4fe4-8811-2180b2b28597 · outbound

This paper cites Adversarial example generation with syntactically controlled paraphrase networks.

Confidence Elicitation: A New Attack Vector for Large Language Models Adversarial example generation with syntactically controlled paraphrase networks

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.864286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.864286Z digest=sha256:01298f245bcc2f26469bfafb8fdf5113854c3d748ff660b6995ebaa4b1e2e4da

Observation 647e80db-2238-4247-b5ac-5712ba10c4ae · outbound

This paper cites Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation.

Confidence Elicitation: A New Attack Vector for Large Language Models Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.867893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.867893Z digest=sha256:ba63d9f8429effaca878be83b6592efcd3fd581d6e824fc934ed7724ca9d79bc

Observation a58d39df-2145-446f-9607-a5fde0f7adc7 · outbound

This paper cites an unresolved cited work.

Confidence Elicitation: A New Attack Vector for Large Language Models Unresolved cited work

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.871884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.871884Z digest=sha256:ad5017a3dd107bc79e931e95844d8c5a8897f0119b0a72e52dc81f40bd405722

Observation bb3c12cf-08a3-4207-8db7-166d8ce8c966 · outbound

This paper cites How can we know when language models know? on the calibration of language models for question answering, 2021.

Confidence Elicitation: A New Attack Vector for Large Language Models How can we know when language models know? on the calibration of language models for question answering, 2021

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.794848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.875365Z digest=sha256:ee248c0cbb660dfb0f39ca70dab672a769e889bb95d2cd8fef59b156afd5a5cc

Observation d6c5a754-7370-4648-884e-ba0ce5eb0735 · outbound

This paper cites Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment.

Confidence Elicitation: A New Attack Vector for Large Language Models Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.878882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.878882Z digest=sha256:817378e9e1aa4e10a1c0ac6caf674d8f589a121d34e9b834d1e939f52c529201

Observation a9dbee5e-3d42-4649-9284-433a09178362 · outbound

This paper cites T rivia QA : A large scale distantly supervised challenge dataset for reading comprehension.

Confidence Elicitation: A New Attack Vector for Large Language Models T rivia QA : A large scale distantly supervised challenge dataset for reading comprehension

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.882645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.882645Z digest=sha256:d194d209a095a0d4b30d0a8631ccd494d0ead5da36a751012cfa8a8cecea3bb5

Observation 1a369df4-247b-49f8-ba17-be4026cad235 · outbound

This paper cites Language models (mostly) know what they know, 2022.

Confidence Elicitation: A New Attack Vector for Large Language Models Language models (mostly) know what they know, 2022

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.886231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.886231Z digest=sha256:5c898d42c29ee76b49f7754a6384e72e31aeab516ffb6516cad01a113fc4d899

Observation aebd11f4-4d22-4b0c-9f9f-f4a8ac384a84 · outbound

This paper cites Adversarial examples in the physical world.

Confidence Elicitation: A New Attack Vector for Large Language Models Adversarial examples in the physical world

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.889683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.889683Z digest=sha256:c9ca7fb3085dee32c533ab15d478065db7f1636e0a0524559399f49831c76b3f

Observation 3c3f464f-b1e8-4181-9921-8fb557c36dfd · outbound

This paper cites TextBugger : Generating adversarial text against real-world applications.

Confidence Elicitation: A New Attack Vector for Large Language Models TextBugger : Generating adversarial text against real-world applications

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.893679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.893679Z digest=sha256:8f14416e85750bb3ee947dba4012f9d695120dd53efb31471013ec4716d22505

Observation 60f91f8c-2ee1-48d2-b3f0-44a98023b594 · outbound

This paper cites BERT - ATTACK : Adversarial attack against BERT using BERT.

Confidence Elicitation: A New Attack Vector for Large Language Models BERT - ATTACK : Adversarial attack against BERT using BERT

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.897124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.897124Z digest=sha256:faabbca5606c2ba6b266c5289e7799ef96138a21852bf3fb7e5df512c52f2604

Observation 539674aa-627c-4674-b010-3dab3568cdc1 · outbound

This paper cites Teaching models to express their uncertainty in words, 2022.

Confidence Elicitation: A New Attack Vector for Large Language Models Teaching models to express their uncertainty in words, 2022

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.778000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.900822Z digest=sha256:3a811ca92688be7b989219aeee19c634a192806c529f22a80c38e40dc3dcd3bf

Observation 3dbed84e-2b53-4fa3-a8bf-19d53fac7d06 · outbound

This paper cites Sspattack: A simple and sweet paradigm for black-box hard-label textual adversarial attack.

Confidence Elicitation: A New Attack Vector for Large Language Models Sspattack: A simple and sweet paradigm for black-box hard-label textual adversarial attack

Reference 33

Resolution
verified exact
doi, observed 2026-08-08T22:06:39.187299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.904446Z digest=sha256:26d0eaa493386fcae8c9d5cd41fe0daea8c715a86f5638f4b9d8aa1c1a0871bd

Observation 6d2cdb81-a076-488c-b72b-0b8d5f0ce0bd · outbound

This paper cites Uncertainty Estimation and Quantification for LLMs: A Simple Supervised Approach.

Confidence Elicitation: A New Attack Vector for Large Language Models Uncertainty Estimation and Quantification for LLMs: A Simple Supervised Approach

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.908043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.908043Z digest=sha256:ce987c220ae49f01369422b8d8d4cb91d0f76cb203108e150766c3c03c9818b8

Observation 0863056b-d110-442d-911b-973bb4d2c7a9 · outbound

This paper cites Autodan: Generating stealthy jailbreak prompts on aligned large language models, 2024 b.

Confidence Elicitation: A New Attack Vector for Large Language Models Autodan: Generating stealthy jailbreak prompts on aligned large language models, 2024 b

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.767514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.911862Z digest=sha256:940ee4a9e8a02c7c1ecacc0aec8f37e9dec0fe445a27a98e444651eef9f3acee

Observation fb786464-b4e3-4e5a-9f41-8d8f5ac31202 · outbound

This paper cites FlipAttack: Jailbreak LLMs via Flipping.

Confidence Elicitation: A New Attack Vector for Large Language Models FlipAttack: Jailbreak LLMs via Flipping

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.915187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.915187Z digest=sha256:e9fbd7b8110a5e825ed4f796e0b89f3bbbf8ecd366614f640f233c5337b95eb2

Observation de135ef2-6a5a-4b40-939a-a6aca5ecf6ca · outbound

This paper cites At which training stage does code data help LLM s reasoning? In The Twelfth International Conference on Learning Representations, 2024.

Confidence Elicitation: A New Attack Vector for Large Language Models At which training stage does code data help LLM s reasoning? In The Twelfth International Conference on Learning Representations, 2024

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.756811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.918567Z digest=sha256:7b045cb05b38e2ee31896f54606d879e97555cf6686f8e823506b9fa99d1bb29

Observation ba503021-ae33-4e33-938c-31770087a4ac · outbound

This paper cites Towards deep learning models resistant to adversarial attacks, 2019.

Confidence Elicitation: A New Attack Vector for Large Language Models Towards deep learning models resistant to adversarial attacks, 2019

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.922029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.922029Z digest=sha256:f20a47685618966e0f1473044608917facf1d18ca5ece653fe54471ed891455a

Observation 09dbc5ae-324f-42b1-b5ec-8c873be4c4a9 · outbound

This paper cites Generating Natural Language Attacks in a Hard Label Black Box Setting.

Confidence Elicitation: A New Attack Vector for Large Language Models Generating Natural Language Attacks in a Hard Label Black Box Setting

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.929089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.929089Z digest=sha256:bdd604ad27735d0ee6dc5ce1616d7342672f0da0ddb0c4f08880e233bcb322b7

Observation 2165e54e-bd21-48eb-a214-d6044b134154 · outbound

This paper cites Tree of attacks: Jailbreaking black-box LLM s automatically.

Confidence Elicitation: A New Attack Vector for Large Language Models Tree of attacks: Jailbreaking black-box LLM s automatically

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.739968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.932553Z digest=sha256:7d044e7bbd81b0d2ba01dc8653bbf557e527116d0cba0bfcfd3a6e4d5cfc0b99

Observation ccc52258-f62b-4fa7-84cd-293a857cff19 · outbound

This paper cites TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP.

Confidence Elicitation: A New Attack Vector for Large Language Models TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.935952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.935952Z digest=sha256:74d4391408b28359de325c93f87bdbefcd592d2c6045ce2eefe9460d4179ab8c

Observation d9da8935-d51f-4a9b-a792-c83e8760fea0 · outbound

This paper cites Counter-fitting word vectors to linguistic constraints, 2016.

Confidence Elicitation: A New Attack Vector for Large Language Models Counter-fitting word vectors to linguistic constraints, 2016

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.729303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.939857Z digest=sha256:648c923be1815385617282682503e86fbd0cb08a2eacaf58e8895c42051e0712

Observation 99814762-4a55-427c-bb9e-0018b059dc82 · outbound

This paper cites Strength in numbers: Estimating confidence of large language models by prompt agreement.

Confidence Elicitation: A New Attack Vector for Large Language Models Strength in numbers: Estimating confidence of large language models by prompt agreement

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.943199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.943199Z digest=sha256:8e5782868bd96b8fe0e9c53b962f60b8588eca3209ec791b066d596f90af3922

Observation 0b692972-5525-4574-90fd-5ffd3812d1a7 · outbound

This paper cites Extreme miscalibration and the illusion of adversarial robustness.

Confidence Elicitation: A New Attack Vector for Large Language Models Extreme miscalibration and the illusion of adversarial robustness

Reference 45

Resolution
verified exact
doi, observed 2026-08-08T22:06:39.165669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.946560Z digest=sha256:7515f721789bec90776bc385d4ee16062c5648f0d83867625ec3a2a6bf89e2c5

Observation fb22cb1e-c1df-40a0-88fb-5a1eecd3561d · outbound

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

Confidence Elicitation: A New Attack Vector for Large Language Models Generating natural language adversarial examples through probability weighted word saliency

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.949980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.949980Z digest=sha256:e41437e94919af22f84423ef9e1dbdfff3e01e2a4a2a37615ad52b11e6f534e9

Observation 433787ed-819e-4146-bb6d-81caca8aeef3 · outbound

This paper cites Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack.

Confidence Elicitation: A New Attack Vector for Large Language Models Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.953361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.953361Z digest=sha256:cb632693f1db68160a0474f25d44cdd2b2e3f481ea7027eb2fdbbdf2f6272946

Observation 698caa8c-9494-43b5-a1a5-1b55f3df3fe6 · outbound

This paper cites Second-order uncertainty quantification: A distance-based approach.

Confidence Elicitation: A New Attack Vector for Large Language Models Second-order uncertainty quantification: A distance-based approach

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.713315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.957004Z digest=sha256:db913f07b37f6d30ec0583072088ba2614585a43828cd22f94aab98258ded402

Observation 1187fd41-1ccc-40ab-8e97-9cca394ffeb1 · outbound

This paper cites Large language model uncertainty measurement and calibration for medical diagnosis and treatment.

Confidence Elicitation: A New Attack Vector for Large Language Models Large language model uncertainty measurement and calibration for medical diagnosis and treatment

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.960140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.960140Z digest=sha256:5a98c512acca6ca71d20908d571296acc2d4e07d1e4bd6fcb6a4a51463aa9611

Observation af0b722a-1a5b-4b47-8dd2-e27701252ace · outbound

This paper cites Logan IV, Eric Wallace, and Sameer Singh.

Confidence Elicitation: A New Attack Vector for Large Language Models Logan IV, Eric Wallace, and Sameer Singh

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.963359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.963359Z digest=sha256:9c3e2e8286b2ad46c2d2635ae8dba9124369817af7d9bb6590baccdf9b21e2ab

Observation 97c1b163-8670-4db1-842e-93bcfb764115 · outbound

This paper cites Intriguing properties of neural networks.

Confidence Elicitation: A New Attack Vector for Large Language Models Intriguing properties of neural networks

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.968013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.968013Z digest=sha256:7ed801abc85013dba91420ae5ce8f24dac704ad5126a53543777a6add5802b53

Observation 84ec1773-6229-4829-8f1f-5bcab717b160 · outbound

This paper cites It’s morphin’ time! combating linguistic discrimination with inflectional perturbations.

Confidence Elicitation: A New Attack Vector for Large Language Models It’s morphin’ time! combating linguistic discrimination with inflectional perturbations

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.971928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.971928Z digest=sha256:cb1c77ad99decc3c40aba7edd8f9bf1d03b3ae12369c02b0dad3031c6683509f

Observation 0a22275b-c838-4bd1-9d2e-7ee053dd98dc · outbound

This paper cites Just ask for calibration: Strategies for eliciting calibrated confidence scores from language models fine-tuned with human feedback.

Confidence Elicitation: A New Attack Vector for Large Language Models Just ask for calibration: Strategies for eliciting calibrated confidence scores from language models fine-tuned with human feedback

Reference 53

Resolution
malformed identifier
no resolver link, observed 2026-08-08T22:06:38.975593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.975593Z digest=sha256:7c25df204262cfdeaffb3d628990675b617a2979140be92eee17635648468e1f

Observation 72cc1b2a-8af4-49c4-bf2d-9aee28587879 · outbound

This paper cites Llama: Open and efficient foundation language models, 2023.

Confidence Elicitation: A New Attack Vector for Large Language Models Llama: Open and efficient foundation language models, 2023

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.979076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.979076Z digest=sha256:bc87c302799f33680a322e9347641e49e7298a20d92a026d86ca9f0764c66357

Observation 7b15e501-be15-409a-bf6b-c9a51a6c8859 · outbound

This paper cites Calibrating large language models using their generations only, 2024.

Confidence Elicitation: A New Attack Vector for Large Language Models Calibrating large language models using their generations only, 2024

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.696891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.982491Z digest=sha256:54a7facd0920042c3e1615def630e501acec9e93ab0da71ed06a164fbe7769c2

Observation 8fdd3a8c-99ef-4bb1-af56-75cd58f315b1 · outbound

This paper cites CAT -gen: Improving robustness in NLP models via controlled adversarial text generation.

Confidence Elicitation: A New Attack Vector for Large Language Models CAT -gen: Improving robustness in NLP models via controlled adversarial text generation

Reference 56

Resolution
verified exact
doi, observed 2026-08-08T22:06:39.122881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.986041Z digest=sha256:e09ab669925ec354d2f4ea6a1f5e5a9b55939d1fd52796fb2184a19880817899

Observation b36c88fd-7cd2-49cd-8d5c-8157d288a653 · outbound

This paper cites Adversarial training with fast gradient projection method against synonym substitution based text attacks, 2020 b.

Confidence Elicitation: A New Attack Vector for Large Language Models Adversarial training with fast gradient projection method against synonym substitution based text attacks, 2020 b

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.686114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.989513Z digest=sha256:4fc68c2f0b2350d21b575c899e2c62ad52899245198fda1a0c01393784b5689c

Observation f6e96565-c004-4fc0-aa07-445f497f4a33 · outbound

This paper cites Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou.

Confidence Elicitation: A New Attack Vector for Large Language Models Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:38.993023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:38.993023Z digest=sha256:67db2864bde550c46da2eeb65975dae6dcb0601c86f1f6911d6e56452de9ee00

Observation 8ab5336a-f3f1-4843-bcaa-f1f2059bf598 · outbound

This paper cites Stop reasoning! when multimodal LLM with chain-of-thought reasoning meets adversarial image.

Confidence Elicitation: A New Attack Vector for Large Language Models Stop reasoning! when multimodal LLM with chain-of-thought reasoning meets adversarial image

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.668721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:38.996680Z digest=sha256:738895a86592474e65d6dcbfac9767c507f35801b97ca8a9d2535d540a264085

Observation 6ebfcde3-9af6-40d6-8439-04f0f2a2fb40 · outbound

This paper cites Efficient Adversarial Training in LLMs with Continuous Attacks.

Confidence Elicitation: A New Attack Vector for Large Language Models Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.000036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.000036Z digest=sha256:3959c5dc4fddea03e4cc1b8630efc1b6f9894adc767a4f11a84d3218d2164ec4

Observation 9b033b79-1eba-46b0-823d-662a5c48207b · outbound

This paper cites Can LLM s express their uncertainty? an empirical evaluation of confidence elicitation in LLM s.

Confidence Elicitation: A New Attack Vector for Large Language Models Can LLM s express their uncertainty? an empirical evaluation of confidence elicitation in LLM s

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.003724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.003724Z digest=sha256:2b3ebfc0c1739099d7a1c1e37325439963ef7edaae7d43510e61341465972acf

Observation 094b0dbb-05e5-4da2-8b18-b13170dce54f · outbound

This paper cites An LLM can fool itself: A prompt-based adversarial attack.

Confidence Elicitation: A New Attack Vector for Large Language Models An LLM can fool itself: A prompt-based adversarial attack

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.652477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:39.007141Z digest=sha256:c53af160e2f5bb561636a53bb3f0d26d41489474a9c55ee72c089e9d7b5a66fc

Observation 75b5120f-16f1-4b63-9b73-d351c7b6e6cb · outbound

This paper cites Texthoaxer: Budgeted hard-label adversarial attacks on text.

Confidence Elicitation: A New Attack Vector for Large Language Models Texthoaxer: Budgeted hard-label adversarial attacks on text

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.010457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.010457Z digest=sha256:4304c04b2fe32b44f07b1d07ddd02019cdcaa56e0e6c4aff3240dfaeadf74310

Observation 7396e07c-d9fa-4b27-9dfb-febd8771e42d · outbound

This paper cites Robust LLM safeguarding via refusal feature adversarial training.

Confidence Elicitation: A New Attack Vector for Large Language Models Robust LLM safeguarding via refusal feature adversarial training

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.013987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.013987Z digest=sha256:0bfe1845c40c566ca82190ff5de887d1f5323e6fa304d84f6df5dbd4007907d1

Observation 47a522f8-7b57-46dd-8f34-f847782b88ae · outbound

This paper cites T ext H acker: Learning based hybrid local search algorithm for text hard-label adversarial attack.

Confidence Elicitation: A New Attack Vector for Large Language Models T ext H acker: Learning based hybrid local search algorithm for text hard-label adversarial attack

Reference 65

Resolution
verified exact
doi, observed 2026-08-08T22:06:39.104300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:39.017575Z digest=sha256:71477643407dbcea643fb55b1e299c7fcd7d976559ae591fffeed619b956077f

Observation a5cc5fbb-c26f-452c-9afd-9f88e7193be6 · outbound

This paper cites Word-level textual adversarial attacking as combinatorial optimization.

Confidence Elicitation: A New Attack Vector for Large Language Models Word-level textual adversarial attacking as combinatorial optimization

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.021017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.021017Z digest=sha256:0ebfdccdd8292978b2aa983c721f4037e116eb277c88742405b39c9630a048d7

Observation 2ed9ab0e-3aec-4809-979b-34f74362d5ad · outbound

This paper cites Weak-to-Strong Jailbreaking on Large Language Models.

Confidence Elicitation: A New Attack Vector for Large Language Models Weak-to-Strong Jailbreaking on Large Language Models

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.024687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.024687Z digest=sha256:87666224bfc67d9292df4d15fe9eeab4247239a95151dd2cb78a7aa024b16d1b

Observation 8c052fa2-8a76-449a-970c-d50b95a4944b · outbound

This paper cites Freelb: Enhanced adversarial training for natural language understanding, 2020.

Confidence Elicitation: A New Attack Vector for Large Language Models Freelb: Enhanced adversarial training for natural language understanding, 2020

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.642273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:39.028166Z digest=sha256:e41306bbbad7b10c28758364fb85f80666a2b5d464b7d5c78601d2a2a70fa222

Observation 5909f52b-7a61-4cee-a95b-1cf22e6a19ae · outbound

This paper cites Auto DAN : Automatic and interpretable adversarial attacks on large language models, 2024.

Confidence Elicitation: A New Attack Vector for Large Language Models Auto DAN : Automatic and interpretable adversarial attacks on large language models, 2024

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T22:07:24.632898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-08T22:06:39.031566Z digest=sha256:4fa093b2a8b38a612f33de577e1355f6846cab5c881e81253f625bd0afabdda6

Observation 1bc43655-8808-4513-998e-d5b7dcfab70d · outbound

This paper cites Zico Kolter, and Matt Fredrikson.

Confidence Elicitation: A New Attack Vector for Large Language Models Zico Kolter, and Matt Fredrikson

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.035313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.035313Z digest=sha256:13a311941c25e5719078e1a690134849f83ac1479a0046998e62190d8e3d84f1

Observation 2c472bca-1d33-47c5-8e4a-fc6c6a62b05c · outbound

This paper cites write newline.

Confidence Elicitation: A New Attack Vector for Large Language Models write newline

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.038666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.038666Z digest=sha256:b782adcdbcda5d4a2a624904ec644773989332a5d9fe8725d9e334a9ee1734f4

Observation d9f9e5ad-4f3b-4f20-8dec-611662b5b6ca · outbound

This paper cites @esa (Ref.

Confidence Elicitation: A New Attack Vector for Large Language Models @esa (Ref

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.042566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.042566Z digest=sha256:5efb93aa48e56d5441f3f09aec924863a05541d3716de3fe197fd684901392f3

Observation 99608ef3-78f9-46d0-aa74-a3e6914258a8 · outbound

This paper cites an unresolved cited work.

Confidence Elicitation: A New Attack Vector for Large Language Models Unresolved cited work

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.046484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.046484Z digest=sha256:210d80574c6452f23ff412c2627d2fe2009f58f462f4fb96db94627029a6bd5c

Observation 58a96e54-cd1f-4ab0-b98f-c6899f1930fd · outbound

This paper cites jq5 ǝ.s] 5 o<tTK XXʵ 5? ouqͼς i 5צD.Vw \ b> ? E Bj< &_z r, Sփ p.

Confidence Elicitation: A New Attack Vector for Large Language Models jq5 ǝ.s] 5 o<tTK XXʵ 5? ouqͼς i 5צD.Vw \ b> ? E Bj< &_z r, Sփ p

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-08T22:06:39.050277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:06:39.050277Z digest=sha256:6326e404ac847b511a045b013fa8e9ae68f82ce9f3391dacce50ea4e477b80d3

Pith citing papers

No inbound Pith citation observations are available.