Paper Citation Record · LEDGER

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating

As of 21 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2608.01112.

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

pith.paper-citation-record.v1
2608.01112 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:16:34.949172Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

24 of 24 outbound references displayed

verified exact0
verified fuzzy16
unresolved7
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ea054fc-d5a0-46d3-9c7f-1bde009fcf14 · outbound

This paper cites Chen, L.; Bian, Y.; Deng, Y.; Cai, D.; Li, S.; Zhao, P.; and Wong, K.-F.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Chen, L.; Bian, Y.; Deng, Y.; Cai, D.; Li, S.; Zhao, P.; and Wong, K.-F

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.261575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 78b77604-3b24-46d3-bacd-38aa271ef215 · outbound

This paper cites H.; Postma, D.; Hickerson, D.; McGaughran,J.;andKhuat,H.Q.2024.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating H.; Postma, D.; Hickerson, D.; McGaughran,J.;andKhuat,H.Q.2024

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.157562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d714eda8-b8d3-467d-8400-6dfed7560e26 · outbound

This paper cites Under the conditionally independent Bernoulli model, if the true null probabilities satisfy qfp i,j≤qfp i,j, calibrating the upper-tail threshold underqfp j is conservative.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Under the conditionally independent Bernoulli model, if the true null probabilities satisfy qfp i,j≤qfp i,j, calibrating the upper-tail threshold underqfp j is conservative

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.092145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 080750ee-020a-4eec-805f-fbe337f85dc8 · outbound

This paper cites Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T15:16:34.876410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33991960-a7bb-4395-b8b3-34e32dc1ef48 · outbound

This paper cites Surrogate parameters remain frozen, and gradients update onlyδi.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Surrogate parameters remain frozen, and gradients update onlyδi

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.052232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 52960f39-7b78-4090-abb2-b7c9bc0db35e · outbound

This paper cites an unresolved cited work.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-15T15:16:35.180248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f5ce7caa-72eb-4c68-9c39-4adb7483c3a0 · outbound

This paper cites SmolVLM: Redefining small and efficient multimodal models.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating SmolVLM: Redefining small and efficient multimodal models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T15:16:34.889489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebc6d5a7-f5d1-4f7e-aba9-bc3081def176 · outbound

This paper cites InThe Twelfth In- ternational Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11,.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating InThe Twelfth In- ternational Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.169063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b524d347-8f71-4dec-b3ec-ea0e0a8326d3 · outbound

This paper cites In Calandrino, J.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating In Calandrino, J

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.133092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 15703848-e166-4b2b-91d3-19a3beaceae3 · outbound

This paper cites InIEEESym- posium on Security and Privacy, SP 2024, San Francisco, CA, USA, May 19-23, 2024, 807–825.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating InIEEESym- posium on Security and Privacy, SP 2024, San Francisco, CA, USA, May 19-23, 2024, 807–825

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.120974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f70bd5c7-908f-4aa8-8a2f-fb6d1b7be57f · outbound

This paper cites Gemma 4 Technical Report.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Gemma 4 Technical Report

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T15:16:34.918285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73f1e7c8-ebdf-4ed1-9b31-78b1bf53b138 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T15:16:34.925242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1132a61-7307-43cf-85ea-d328deedf9e3 · outbound

This paper cites (15) Writingρi =|E i|−1, a conservative threshold is tα = min{t:P ρ (Ttgt≥t)≤α}.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating (15) Writingρi =|E i|−1, a conservative threshold is tα = min{t:P ρ (Ttgt≥t)≤α}

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.078749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f89a0a43-c790-4446-b684-338ff5527d29 · outbound

This paper cites The reported detector instead usesK= 30returned-answer calls for provider-independent calibration, so these probability-valued estimates do not enter the reported operating points.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating The reported detector instead usesK= 30returned-answer calls for provider-independent calibration, so these probability-valued estimates do not enter the reported operating points

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.065337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 91b1353b-5741-4396-9d94-7c196454f278 · outbound

This paper cites Adherence is the fraction of responses that contain a valid capital letter corresponding to an available option.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Adherence is the fraction of responses that contain a valid capital letter corresponding to an available option

Reference 24

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T15:16:35.039613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 72585eed-112a-4b68-9cc7-100e5ce63d76 · outbound

This paper cites In Bengio, Y.; and LeCun, Y., eds.,2nd International Conference on Learning Represen- tations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating In Bengio, Y.; and LeCun, Y., eds.,2nd International Conference on Learning Represen- tations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.107374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 60c37316-aa9b-41b7-8f15-5a388bb841ec · outbound

This paper cites InInternational Conference on Learning Representations.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating InInternational Conference on Learning Representations

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.190800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4b603af3-ce0f-4522-a49e-926da81792e7 · outbound

This paper cites In2018 IEEE Conference on Computer Vision and Pattern Recognition,CVPR2018,SaltLakeCity,UT,USA,June18- 22, 2018, 9185–9193.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating In2018 IEEE Conference on Computer Vision and Pattern Recognition,CVPR2018,SaltLakeCity,UT,USA,June18- 22, 2018, 9185–9193

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.249056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7c849d80-810c-4c3c-b3b6-3c27a822b92b · outbound

This paper cites In Costa-jussà, M.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating In Costa-jussà, M

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.237736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dabc2c75-7a5f-4c4f-8eb0-8364896ca8dd · outbound

This paper cites InProceedings of the AAAI Conference on Artificial Intelligence, volume 36, 10758–10766.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating InProceedings of the AAAI Conference on Artificial Intelligence, volume 36, 10758–10766

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.214495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 538a685d-9c7b-45a2-a9ad-4eb5f439cf47 · outbound

This paper cites an unresolved cited work.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-15T15:16:35.145900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d96a0700-9e7b-4948-85d4-6e1260f2f51e · outbound

This paper cites In Kim, B.; Yue, Y.; Chaudhuri, S.; Fragkiadaki, K.; Khan, M.;andSun,Y.,eds.,InternationalConferenceonLearning Representations, volume 2024, 38745–38768.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating In Kim, B.; Yue, Y.; Chaudhuri, S.; Fragkiadaki, K.; Khan, M.;andSun,Y.,eds.,InternationalConferenceonLearning Representations, volume 2024, 38745–38768

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.225794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 312c612f-1bd8-4d39-8a77-16cc2d442311 · outbound

This paper cites Qwen3-VL Technical Report.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating Qwen3-VL Technical Report

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-15T15:16:34.845672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0c56cda-fd64-4129-9b3a-5e9954c0a155 · outbound

This paper cites InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 42341–42351.

Fighting Fire with Fire: On the Feasibility of Protecting Exercises Against AI Cheating InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 42341–42351

Reference 2026

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:16:35.202851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.