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Paper Citation Record · LEDGER

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions

As of 7 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2509.23782.

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

pith.paper-citation-record.v1
2509.23782 v4

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T14:43:16.659316Z

measured 39 of 39 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T05:41:39.396469Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T05:44:38.784930Z

Reference resolution

38 of 38 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved37
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d4861c87-8192-4d0b-b3f9-7c44bdf9b39e · outbound

This paper cites Understanding intermediate layers using linear classifier probes, 2017.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Understanding intermediate layers using linear classifier probes, 2017

Reference 1

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source=arxiv_source observed=2026-08-04T14:43:10.834850Z digest=sha256:103b7ba2d4ade6189e729ced082598acb2d110e7ea58507539c32dece93c069e

Observation 4fdcf6f6-aa45-452a-be66-1db39a2491e9 · outbound

This paper cites Refusal in language models is mediated by a single direction.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Refusal in language models is mediated by a single direction

Reference 2

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source=arxiv_source observed=2026-08-04T14:43:10.991738Z digest=sha256:90941b52dff9f26d8ca03a71b7a871054b6d4852fefcb39da5e5a056b32dbb4f

Observation 32bc3b33-4855-4780-ac24-39eefbe48f88 · outbound

This paper cites The internal state of an LLM knows when it ' s lying.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions The internal state of an LLM knows when it ' s lying

Reference 3

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source=arxiv_source observed=2026-08-04T14:43:11.125807Z digest=sha256:2c880d55df2819d2d145f4faa31f2dcb7202cb1e464df1f05f30f3f32565f808

Observation a4dbe1c3-1615-497c-840c-7e3b527c8fd0 · outbound

This paper cites Probing the geometry of truth: Consistency and generalization of truth directions in LLM s across logical transformations and question answering tasks.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Probing the geometry of truth: Consistency and generalization of truth directions in LLM s across logical transformations and question answering tasks

Reference 4

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source=arxiv_source observed=2026-08-04T14:43:11.254749Z digest=sha256:a4d329a427b4446805762d7a91fd128242a35a3b060acf20b6cd6243841fecae

Observation e5cbb389-ec1f-41e0-a528-85b13efbd060 · outbound

This paper cites an unresolved cited work.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Unresolved cited work

Reference 5

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source=arxiv_source observed=2026-08-04T14:43:11.344855Z digest=sha256:8e3241a6b43bda9e2921bef0b1bf36ba7b1154a19f15f54437c7c8c1e5e7e484

Observation 7c5363e6-c712-4c37-aa28-cbdd340f86bd · outbound

This paper cites Answer Matching Outperforms Multiple Choice for Language Model Evaluation.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Answer Matching Outperforms Multiple Choice for Language Model Evaluation

Reference 6

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source=arxiv_source observed=2026-08-04T14:43:11.483898Z digest=sha256:3502a3e91c7b3f9dbeee999b1791aca8e47806ba2e1498186b7898c3ae0ed5ad

Observation b7cd00fa-fa5a-4de1-95df-e54156878fea · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Gonzalez, Ion Stoica, and Eric P

Reference 7

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source=arxiv_source observed=2026-08-04T14:43:11.584755Z digest=sha256:6766ef96c5d8cfda0a26c10bb25b782011c7b9444e687a33158bdf1308ae1b30

Observation a6265235-1739-4e7b-b4a7-88de8c1336db · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 8

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source=arxiv_source observed=2026-08-04T14:43:11.694751Z digest=sha256:ab4869a3acc0849ed5cdf355175f0b8b89622f0bb19eff2d558ae7c8427a9591

Observation f6895e65-dd42-46a4-929b-509c7c8bc0b1 · outbound

This paper cites Knowledge neurons in pretrained transformers.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Knowledge neurons in pretrained transformers

Reference 9

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source=arxiv_source observed=2026-08-04T14:43:11.774755Z digest=sha256:0d7e40900ae9787404c85a1d8c2590c624c43178db1ee7efa8a2151e88fdfa1b

Observation aa81f760-e8e4-4f17-8f7e-2121feb525a4 · outbound

This paper cites Plug and play language models: A simple approach to controlled text generation.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Plug and play language models: A simple approach to controlled text generation

Reference 10

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source=arxiv_source observed=2026-08-04T14:43:11.954755Z digest=sha256:1bf8058024e3b82dfbdb1fe8617be3ef7841b4572d683fce37197215014f239f

Observation bb0ef333-e192-411f-9aa1-fae9edeb02cb · outbound

This paper cites In-Context Learning Creates Task Vectors.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions In-Context Learning Creates Task Vectors

Reference 11

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source=arxiv_source observed=2026-08-04T14:43:12.104751Z digest=sha256:71825400a89bbaf893e10228816a2d6d42e44ace9963ff1f2e001aba64f5b950

Observation fb4b5cdf-99b3-4f2c-a364-4d2c26d97398 · outbound

This paper cites Measuring massive multitask language understanding.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Measuring massive multitask language understanding

Reference 12

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source=arxiv_source observed=2026-08-04T14:43:12.266840Z digest=sha256:2daae61b886010f58db856e72fb5e0104834de94b00b660c48f59b55092a3843

Observation 2d4ef28b-d407-497e-8804-bcffa2d9fc7a · outbound

This paper cites Lo RA : Low-rank adaptation of large language models.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Lo RA : Low-rank adaptation of large language models

Reference 13

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source=arxiv_source observed=2026-08-04T14:43:12.474741Z digest=sha256:9a8415afeeceeabde677765a93a081cca468651c604a40029df168c3bb6e4d14

Observation 4c8bab94-f220-462c-976b-10211c9efe78 · outbound

This paper cites Editing Models with Task Arithmetic.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Editing Models with Task Arithmetic

Reference 14

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source=arxiv_source observed=2026-08-04T14:43:12.554747Z digest=sha256:32f132a7162187e48127d0db7fb16cca3cf1d4d9ce1d2875ed8012e29662280e

Observation 8c20cf2e-6896-4ecb-8776-5cd00b577bf0 · outbound

This paper cites Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Erik Miehling, Pierre Dognin, Manish Nagireddy, and Amit Dhurandhar.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Erik Miehling, Pierre Dognin, Manish Nagireddy, and Amit Dhurandhar

Reference 15

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source=arxiv_source observed=2026-08-04T14:43:12.639855Z digest=sha256:1b2bacbd3271c4e8737492b69d21313e4abb5f08a695383cf36af9e0f127ee22

Observation 0e449c57-2bbf-41e4-a5c8-552fc7727168 · outbound

This paper cites Inference-time intervention: Eliciting truthful answers from a language model.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Inference-time intervention: Eliciting truthful answers from a language model

Reference 16

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source=arxiv_source observed=2026-08-04T14:43:12.724755Z digest=sha256:d8b8019cf5b2fc793a6bdf20a98eedcc3783d952e2751782fe0c6855d37ab267

Observation dfb45d73-c2fc-4ae4-8573-2f0168c57871 · outbound

This paper cites an unresolved cited work.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Unresolved cited work

Reference 17

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source=arxiv_source observed=2026-08-04T14:43:12.824752Z digest=sha256:648a049c10b98e77ceae0b43c3f5b8743d6a11f19d7d32441c0ae0deebd525ae

Observation bd241c84-4760-4714-894c-81c6e1b8090f · outbound

This paper cites Investigating Bias Representations in Llama 2 Chat via Activation Steering.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Investigating Bias Representations in Llama 2 Chat via Activation Steering

Reference 18

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source=arxiv_source observed=2026-08-04T14:43:12.984764Z digest=sha256:b5ac9355d6defaeb4630e7c97953002e1d916e3aed9db87b5933cab9293c8c63

Observation 8ef1facb-36b6-4280-aa62-f53b12ec9d0a · outbound

This paper cites The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Reference 19

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source=arxiv_source observed=2026-08-04T14:43:13.214435Z digest=sha256:b04233cbd5190096fa21808f8464c1169477614422c4ad63251087404ca801c6

Observation 12f9e328-d523-40cf-a968-0143306db352 · outbound

This paper cites Locating and editing factual associations in gpt.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Locating and editing factual associations in gpt

Reference 20

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source=arxiv_source observed=2026-08-04T14:43:13.414745Z digest=sha256:bd4aef4000fe34a2a2864bf5c966c887c23c370234f3d3be537873d2ee921558

Observation 6e949ff8-2c33-4a7a-a8d8-bee0c97f1101 · outbound

This paper cites Introducing gpt-5.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Introducing gpt-5

Reference 21

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source=arxiv_source observed=2026-08-04T14:43:13.554750Z digest=sha256:b41927895aab0ad47b37da757b62148080c0a68b7742dc1e9edffbc1dc4f6c94

Observation 769231bb-d2b5-4585-9799-61887f627ff2 · outbound

This paper cites LLM s know more than they show: On the intrinsic representation of LLM hallucinations.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions LLM s know more than they show: On the intrinsic representation of LLM hallucinations

Reference 22

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source=arxiv_source observed=2026-08-04T14:43:13.676180Z digest=sha256:a8718ea5a2b3da58b44b99c0ef859f409840ba70796cf3bf41003b7f9a77c776

Observation 89f8d6d1-c388-471b-901a-1952b944fca0 · outbound

This paper cites Large language models sensitivity to the order of options in multiple-choice questions.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Large language models sensitivity to the order of options in multiple-choice questions

Reference 23

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source=arxiv_source observed=2026-08-04T14:43:13.894756Z digest=sha256:973efb289bb575ea8cac0aa739cdb4cb44579d232f36090c531a16c12d339929

Observation 05c47a6d-4b5b-49c8-8907-a5480d2c89a6 · outbound

This paper cites Qwen2.5 Technical Report.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Qwen2.5 Technical Report

Reference 24

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source=arxiv_source observed=2026-08-04T14:43:14.064827Z digest=sha256:6e705d38812054ddcd67ad1ca7ea0e3ef45e0e73624f2643b9a8022eb0c1205b

Observation d8311e3c-ea13-4676-b1a3-10d99d7b1a63 · outbound

This paper cites Steering llama 2 via contrastive activation addition.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Steering llama 2 via contrastive activation addition

Reference 25

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source=arxiv_source observed=2026-08-04T14:43:14.245491Z digest=sha256:458e884c72e69cbbe104ab19258e3e5d8219f26a91e22b21399d86f35f0799e0

Observation 42bb0af7-1ac2-481a-b0e3-9d8bd3a65377 · outbound

This paper cites Layer by layer: Uncovering hidden representations in language models.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Layer by layer: Uncovering hidden representations in language models

Reference 26

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source=arxiv_source observed=2026-08-04T14:43:14.444798Z digest=sha256:92d24ceacc6717c0c6948fe1602fbe1398c295c1f7fd1d92e55c5f330844d9c0

Observation be4e53b3-807c-4d95-ad07-7ae34df46d9f · outbound

This paper cites Unsupervised real-time hallucination detection based on the internal states of large language models.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Unsupervised real-time hallucination detection based on the internal states of large language models

Reference 27

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source=arxiv_source observed=2026-08-04T14:43:14.604749Z digest=sha256:a3294a0ab99ce7944b81e216c806f627cd01c1b95c4b6dc85cc509916f4d2077

Observation de047cd8-163f-4db8-834e-aef3550c8341 · outbound

This paper cites Challenging BIG -bench tasks and whether chain-of-thought can solve them.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Challenging BIG -bench tasks and whether chain-of-thought can solve them

Reference 28

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source=arxiv_source observed=2026-08-04T14:43:14.784754Z digest=sha256:eb1f2985b7e0572192f921949f195323f1aea8daed1dda6486bada51e9a2e668

Observation e2e3c5ee-8a7c-4fc2-a8b9-8080c4ee664a · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 29

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source=arxiv_source observed=2026-08-04T14:43:14.974820Z digest=sha256:18b62c7c0f904c8d68be8afea77b42386ba4d8e65ac4670d72d7f1a103ee1df6

Observation e7997358-7fa8-421c-95c0-603d15ad6dfe · outbound

This paper cites Steering language models with activation engineering, 2025.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Steering language models with activation engineering, 2025

Reference 30

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source=arxiv_source observed=2026-08-04T14:43:15.134753Z digest=sha256:fa73afe671103d67cd8639282077bcb5d5275faeb6d59a5f98c00db8c918be8f

Observation f7e4287d-2a93-4639-bea7-5c0ce74d9d53 · outbound

This paper cites FacLens: Transferable Probe for Foreseeing Non-Factuality in Fact-Seeking Question Answering of Large Language Models.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions FacLens: Transferable Probe for Foreseeing Non-Factuality in Fact-Seeking Question Answering of Large Language Models

Reference 31

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local_arxiv, observed 2026-08-04T14:43:27.887348Z

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

source=arxiv_source observed=2026-08-04T14:43:15.220082Z digest=sha256:ba4293c9d96d195a82caf7c735509d53671c9ce85452f407b7a02740a8fe27c3

Observation b18fa2fb-756c-40fe-b15a-80ee93c497b5 · outbound

This paper cites Chi, Quoc V.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Chi, Quoc V

Reference 32

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source=arxiv_source observed=2026-08-04T14:43:15.404755Z digest=sha256:0d46b2b34483cf7f081e4199f9c3657c6aff6f9829b685b8d93669e60be964a7

Observation 2861dfea-6645-4832-901a-d4f7d7302003 · outbound

This paper cites Large language models are not robust multiple choice selectors.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Large language models are not robust multiple choice selectors

Reference 33

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source=arxiv_source observed=2026-08-04T14:43:15.575227Z digest=sha256:4098a2e144f1aa9a2612ec7b34b9008d9e3594d14f767799ce18f01b2853ef9f

Observation 1724327b-ea3d-412a-899c-f0b9ff65cad1 · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Representation Engineering: A Top-Down Approach to AI Transparency

Reference 34

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source=arxiv_source observed=2026-08-04T14:43:15.684752Z digest=sha256:26e016339a060d5ca9abda144a35e73458a577e6833950c47eae8bd6a79791ba

Observation acb733d1-9244-48e3-ba78-0aed45ec7483 · outbound

This paper cites write newline.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions write newline

Reference 35

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source=arxiv_source observed=2026-08-04T14:43:15.874752Z digest=sha256:9434aea921324f4dbe51f438c31c10ca76d2d9ef96fa8ca5be83723271486776

Observation 44f902df-2182-40a0-b442-5ef5e894cd62 · outbound

This paper cites @esa (Ref.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions @esa (Ref

Reference 36

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source=arxiv_source observed=2026-08-04T14:43:16.134895Z digest=sha256:70ac7d90784bc28ed41312aad0b361c79f5b7506e84f1e77e214c6d9bd18ef39

Observation 7a728661-918c-4066-9d0e-5049b5fe8a3d · outbound

This paper cites an unresolved cited work.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Unresolved cited work

Reference 37

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source=arxiv_source observed=2026-08-04T14:43:16.324755Z digest=sha256:ce986f9e474337fb8f6c9546a89df20f8133ed2781f4dbd14020e195248956a8

Observation 07a60ae9-8d01-490c-8a93-19b8e2ee472b · outbound

This paper cites an unresolved cited work.

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions Unresolved cited work

Reference 38

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unresolved
no resolver link, observed 2026-08-04T14:43:16.659316Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-04T14:43:16.659316Z digest=sha256:65cdd8e8c41b08832963a720f58152cefa77bbc62d5c8567cde41b1f23787d7a

Pith citing papers

Observation b0fd5d4b-2ae4-4e1d-ab70-815f025a85b4 · inbound

Which Way Did It Move? Diagnosing and Overcoming Directional Motion Blindness in Video-LLMs cites this paper.

Which Way Did It Move? Diagnosing and Overcoming Directional Motion Blindness in Video-LLMs Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions

Reference 51

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verified exact
arxiv_id, observed 2026-06-02T03:04:01.145620Z

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.

source=pdf_text observed=2026-05-22T05:41:39.396469Z digest=sha256:9882c1e19fda40e35954327e243b8732bc4a59476f5327e8533491d254c0eb31