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Paper Citation Record · LEDGER

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models

As of 6 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2605.05938.

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

pith.paper-citation-record.v1
2605.05938 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T05:20:43.593625Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:39:45.523518Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T00:39:53.559223Z

Reference resolution

35 of 35 outbound references displayed

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  • unresolved35
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External citation measurements

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Outbound references

Observation c2ea8fc6-7819-4c78-ad5c-09ffe34d57fe · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

Reference 1

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source=pdf_text observed=2026-08-04T05:20:43.323370Z digest=sha256:6779ed565fdea4d51170de6a0f332585fe48296180dc6695be1246f0fb773b4c

Observation afea450f-85a0-49bc-8a51-ee81a4a19555 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 2

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source=pdf_text observed=2026-08-04T05:20:43.376718Z digest=sha256:0806e1985522e6d385db5d0613aff89838959c9b5e49093241f6dd6ae9da0c5c

Observation 3ca2c889-523b-457b-9c43-4e405ebe3b22 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 3

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source=pdf_text observed=2026-08-04T05:20:43.473465Z digest=sha256:555374d55f06a1ab529a2e606a9b7d5229deca60e3376f1d45c1019ab4f5ec6e

Observation 72aaa357-9d65-4b0f-b511-d34c966df4e4 · outbound

This paper cites mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 4

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source=pdf_text observed=2026-08-04T05:20:43.477913Z digest=sha256:cb19419d326135e8ee20961a705bf3f2230b7508cab4364e88c142bd14ab4b34

Observation af321124-e8ef-4330-a542-aad214fc956a · outbound

This paper cites Protecting privacy in multimodal large language models with mllmu-bench.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Protecting privacy in multimodal large language models with mllmu-bench

Reference 5

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source=pdf_text observed=2026-08-04T05:20:43.482478Z digest=sha256:630eb0e984718e98472360e9d09fa931a1ae21f090bd99892355c103f3851a41

Observation 5120e51d-9f3e-4ea1-b373-32b9ad9e9b33 · outbound

This paper cites Single image unlearning: Efficient machine unlearning in multimodal large language models.Advances in Neural Information Processing Systems, 37:35414–35453, 2024.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Single image unlearning: Efficient machine unlearning in multimodal large language models.Advances in Neural Information Processing Systems, 37:35414–35453, 2024

Reference 6

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source=pdf_text observed=2026-08-04T05:20:43.486934Z digest=sha256:bb3931554a93ead80d9c490a2ee164c69e98db14ac9890ce6c1d170d826f7e96

Observation b4ddeef3-0c15-45fd-8df6-054f5bd6ffca · outbound

This paper cites A survey on large language model (llm) security and privacy: The good, the bad, and the ugly.High-Confidence Computing, 4(2):100211, 2024.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models A survey on large language model (llm) security and privacy: The good, the bad, and the ugly.High-Confidence Computing, 4(2):100211, 2024

Reference 7

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source=pdf_text observed=2026-08-04T05:20:43.491343Z digest=sha256:2e2b641773adc5fb18d99266b6a59693f7354b0dadf7e3abbc2e38be5df9bd07

Observation cdaf3382-6032-43bd-8330-7f84835209da · outbound

This paper cites The eu general data protection regulation (gdpr).A practical guide, 1st ed., Cham: Springer International Publishing, 10(3152676):10–5555, 2017.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models The eu general data protection regulation (gdpr).A practical guide, 1st ed., Cham: Springer International Publishing, 10(3152676):10–5555, 2017

Reference 8

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source=pdf_text observed=2026-08-04T05:20:43.494986Z digest=sha256:b8297bf6b6164a3caa7ee4d5991f1a4d23294197747376d94f6caf5b5d8d0727

Observation 743f0c2a-ab89-4a15-96a1-cb6bf446eeb9 · outbound

This paper cites Rethinking machine unlearning for large language models.Nature Machine Intelligence, 7(2):181–194, 2025.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Rethinking machine unlearning for large language models.Nature Machine Intelligence, 7(2):181–194, 2025

Reference 9

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source=pdf_text observed=2026-08-04T05:20:43.498717Z digest=sha256:b1b59b35e248ebae055eeff9809913d8421ff46076b33d0e4ba2aa21a9ec8424

Observation bd2cfd19-5ab2-44f2-a296-69f7b2c6b3fc · outbound

This paper cites Wagle: Strategic weight attribution for effective and modular unlearning in large language models.Advances in Neural Information Processing Systems, 37:55620–55646, 2024.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Wagle: Strategic weight attribution for effective and modular unlearning in large language models.Advances in Neural Information Processing Systems, 37:55620–55646, 2024

Reference 10

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source=pdf_text observed=2026-08-04T05:20:43.502226Z digest=sha256:b24a7fe2f7e72976891649e8fd2fc659efd52b2c8d028bbc1cdffb71c56522f8

Observation 9bab6036-20fd-4679-814b-62fede001e3d · outbound

This paper cites Videoeraser: Concept erasure in text-to-video diffusion models.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Videoeraser: Concept erasure in text-to-video diffusion models

Reference 11

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source=pdf_text observed=2026-08-04T05:20:43.505748Z digest=sha256:527f6718aa990c2e9aeb73548a3330065c0203cf9b0d13cc124998dc90496c4c

Observation 68737fc3-ad90-4d61-96ab-3876fdcca79c · outbound

This paper cites Yuan: Yielding unblemished aesthetics through a unified network for visual imperfections removal in generated images.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Yuan: Yielding unblemished aesthetics through a unified network for visual imperfections removal in generated images

Reference 12

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source=pdf_text observed=2026-08-04T05:20:43.509171Z digest=sha256:122aff00fd33309947736f7560ed2f92a50a4ed06f9b21368b85e966540a6aff

Observation 1e2b8c65-60f0-440d-a448-c80bf4f18eb5 · outbound

This paper cites MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning

Reference 13

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source=pdf_text observed=2026-08-04T05:20:43.512792Z digest=sha256:372de78395ddb0bc6c18a0d27627d4ae47267fd6b3d17cc33f166df10423796c

Observation 58a80f72-f34c-4e4a-989b-9dcb31fef34c · outbound

This paper cites Umu-bench: Closing the modality gap in multimodal unlearning evaluation.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Umu-bench: Closing the modality gap in multimodal unlearning evaluation

Reference 14

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source=pdf_text observed=2026-08-04T05:20:43.516458Z digest=sha256:2052775ea6cb92577e42749e995eec561e3bde088a291c1feefa86f3da30840e

Observation a0b40983-789b-4ab0-b924-cf14fdb75f2b · outbound

This paper cites Clear: Character unlearning in textual and visual modalities.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Clear: Character unlearning in textual and visual modalities

Reference 15

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source=pdf_text observed=2026-08-04T05:20:43.520178Z digest=sha256:9147cc523c7778608615e6dcd80e91d8537dc93d5f52cd4c9edb91d7cf5636ed

Observation 86ef9517-004c-4ac5-b484-7a7e6b72231c · outbound

This paper cites PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models

Reference 16

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source=pdf_text observed=2026-08-04T05:20:43.523689Z digest=sha256:f9169666d4f9590fa99ea67e75077cb4510fdfe64432d3646751ac202425b43f

Observation 4e77003a-d0c4-4567-ab69-ba6d48956e92 · outbound

This paper cites Forgetme: Benchmarking the selective forgetting capabilities of generative models.Engineering Applica- tions of Artificial Intelligence, 161:112087, 2025.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Forgetme: Benchmarking the selective forgetting capabilities of generative models.Engineering Applica- tions of Artificial Intelligence, 161:112087, 2025

Reference 17

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source=pdf_text observed=2026-08-04T05:20:43.527643Z digest=sha256:067136f3e492bc888d6fc128157d77d78d9443b66129aac5b57a6e54a8cfcef1

Observation 792ea008-f3d2-4d47-b3f5-bc57d98f457e · outbound

This paper cites Knowledge unlearning for mitigating privacy risks in language models.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Knowledge unlearning for mitigating privacy risks in language models

Reference 18

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source=pdf_text observed=2026-08-04T05:20:43.531048Z digest=sha256:fbe8931d222ff43b0da9951f9eda0c3289154f71ab8ccc2ce7bd5fd0c52599f3

Observation 454faf7c-3330-4db3-b0c6-bf315d62bebd · outbound

This paper cites Large language model unlearning.Advances in Neural Information Processing Systems, 37:105425–105475, 2024.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Large language model unlearning.Advances in Neural Information Processing Systems, 37:105425–105475, 2024

Reference 19

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source=pdf_text observed=2026-08-04T05:20:43.534422Z digest=sha256:390e005e78e131424e63864d46e57accb7fa61f35192ee18a70615d3dbce1365

Observation ba12fd68-9b33-4173-b217-67a43e6923a5 · outbound

This paper cites Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning

Reference 20

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source=pdf_text observed=2026-08-04T05:20:43.538160Z digest=sha256:0d503f4437cb3bae6c5a8bc414fb74aaee66b58055b118653218c2be3d77fde3

Observation 746fe0ad-204d-405f-a473-b86945b6afda · outbound

This paper cites Mmunlearner: Reformulating multimodal machine unlearning in the era of multimodal large language models.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Mmunlearner: Reformulating multimodal machine unlearning in the era of multimodal large language models

Reference 21

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source=pdf_text observed=2026-08-04T05:20:43.542143Z digest=sha256:ff232b394efa4d7025cd1bffd97566b72cd35a625cd7e5dadb046d4a7e4e065b

Observation 9caac341-d659-46ce-9a1f-99396dba341a · outbound

This paper cites Modality-aware neuron pruning for unlearning in multimodal large language models.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Modality-aware neuron pruning for unlearning in multimodal large language models

Reference 22

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source=pdf_text observed=2026-08-04T05:20:43.545573Z digest=sha256:3ad1e322ad5ed53265398b0010959ea7f39831c87cbf7ec205dcff2afc20d9aa

Observation 7251bc7c-ca5e-4895-be54-ce7c83c0cd98 · outbound

This paper cites Mllm machine unlearning via visual knowledge distillation.arXiv preprint arXiv:2512.11325, 2025.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Mllm machine unlearning via visual knowledge distillation.arXiv preprint arXiv:2512.11325, 2025

Reference 23

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source=pdf_text observed=2026-08-04T05:20:43.549197Z digest=sha256:046def9d78bd2e59729cbf337e27abb60d7edfd136bc4d0051e7427965669f0d

Observation dafb1378-515b-48f0-a6ef-2847971f1d2b · outbound

This paper cites On large language model continual unlearning.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models On large language model continual unlearning

Reference 24

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source=pdf_text observed=2026-08-04T05:20:43.552874Z digest=sha256:0a0d7951e473b15d45b16bf3d3c7388fcd31cc90bb3e7523bdc739ca38c30a0c

Observation f454bb1e-4c62-4236-b5da-52b36609da5c · outbound

This paper cites Pulse: Practical evaluation scenarios for large multimodal model unlearning.arXiv preprint arXiv:2507.01271, 2025.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Pulse: Practical evaluation scenarios for large multimodal model unlearning.arXiv preprint arXiv:2507.01271, 2025

Reference 25

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source=pdf_text observed=2026-08-04T05:20:43.556565Z digest=sha256:905d39689cfc5facdb816fb6de44503f0067b63827342680ed6181a37be65c12

Observation 8a9e81d0-39a4-48b3-88b1-6202daedc88a · outbound

This paper cites MUSE: Machine Unlearning Six-Way Evaluation for Language Models.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models MUSE: Machine Unlearning Six-Way Evaluation for Language Models

Reference 26

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source=pdf_text observed=2026-08-04T05:20:43.560527Z digest=sha256:b6d7177f47ccd98a753dbf29abce9fe623599ce78440c23aaf35e58b9d2f9aa0

Observation 638fb06b-9f9f-43c5-aac8-2f94351b5584 · outbound

This paper cites Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges

Reference 27

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source=pdf_text observed=2026-08-04T05:20:43.564415Z digest=sha256:08c7226dc5b7469e2ceaae769149ecdde17f5b437034bda8d8dc9f10c12de30d

Observation 5f7688e1-900b-462b-aaf7-4a7824410727 · outbound

This paper cites Unrolling sgd: Understanding factors influencing machine unlearning.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Unrolling sgd: Understanding factors influencing machine unlearning

Reference 28

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source=pdf_text observed=2026-08-04T05:20:43.567953Z digest=sha256:6225a9ebdd4a7d9b53c21efe1578055066231cbf7ecb37764efd03a165486616

Observation 5c27e179-1ee1-4d22-9484-2bcd52bcfd59 · outbound

This paper cites Continual learning and private unlearning.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Continual learning and private unlearning

Reference 29

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source=pdf_text observed=2026-08-04T05:20:43.572032Z digest=sha256:0f7f6d61b286b20c77184589245124ada254d1afea68323a52dfe2982def8b57

Observation 2c3d2ba1-6c70-442a-bfd6-e32134e67ebe · outbound

This paper cites TOFU: A Task of Fictitious Unlearning for LLMs.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models TOFU: A Task of Fictitious Unlearning for LLMs

Reference 30

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source=pdf_text observed=2026-08-04T05:20:43.575760Z digest=sha256:3923cb8b9d119ce8a61fc96e9137d39311f00d09b9fbaeb49de9fc16fdb9c553

Observation 33e78925-6805-4f91-9c9d-8dc759878a49 · outbound

This paper cites Variational bayesian unlearning.Advances in Neural Information Processing Systems, 33:16025–16036, 2020.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Variational bayesian unlearning.Advances in Neural Information Processing Systems, 33:16025–16036, 2020

Reference 31

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source=pdf_text observed=2026-08-04T05:20:43.579524Z digest=sha256:00bff0c3deabffe6310d8540e181700a32c3f01f92f120892800237e3c017c29

Observation a76152dc-5410-480b-ae9e-0c584ed6947a · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Direct preference optimization: Your language model is secretly a reward model

Reference 32

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source=pdf_text observed=2026-08-04T05:20:43.582973Z digest=sha256:15bdecd53cb6b31e5b3dc161c6b546b2c471c4a8574069e820bcc3103e50b8bc

Observation 905e01ff-c0e1-495c-b7f4-e35f9621f883 · outbound

This paper cites Efuf: Efficient fine-grained unlearning framework for mitigating hallucinations in multimodal large language models.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Efuf: Efficient fine-grained unlearning framework for mitigating hallucinations in multimodal large language models

Reference 33

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source=pdf_text observed=2026-08-04T05:20:43.586591Z digest=sha256:a6563c1290626a458f8200d72f7ec0c37227f47e1d98b4e1c67c0f1a0f5eee5a

Observation e97a8848-9b61-4545-953c-37b56d5ef62a · outbound

This paper cites Cross-modal safety alignment: Is textual unlearning all you need?arXiv preprint arXiv:2406.02575, 2024.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models Cross-modal safety alignment: Is textual unlearning all you need?arXiv preprint arXiv:2406.02575, 2024

Reference 34

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source=pdf_text observed=2026-08-04T05:20:43.589964Z digest=sha256:dbf3314f4a1b61308678a9491df042595e016a8ffb024df663892270a69657f6

Observation 9c43be5c-21b5-4d8d-9051-36104c1d7fc1 · outbound

This paper cites fluency_score.

ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models fluency_score

Reference 35

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no resolver link, observed 2026-08-04T05:20:43.593625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:20:43.593625Z digest=sha256:c9cb4217f576105378eb8a5a1f45c4e8023212638cfe56e1fe61cd1b96085c6c

Pith citing papers

Observation 14282def-55b9-455e-8fa7-626541181a77 · inbound

Toward Fine-Grained Forgetting:Attribute Unlearning for Multimodal Large Language Models cites this paper.

Toward Fine-Grained Forgetting:Attribute Unlearning for Multimodal Large Language Models ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models

Reference 15

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local_arxiv, observed 2026-08-06T00:39:53.610829Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-06T00:39:45.523518Z digest=sha256:7a69f672b9bc10c084c6dce3accbd4e327803669dc947ffb64be22ef38ad1973