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Paper Citation Record · LEDGER

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF

As of 15 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 3 inbound Pith citation observations for arXiv:2506.03234.

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

pith.paper-citation-record.v1
2506.03234 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:18:06.054981Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T16:26:34.918099Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T01:37:30.522097Z

Reference resolution

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved25
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c232ca51-e49b-4862-ba9d-ffcc20072146 · outbound

This paper cites Best-of-Venom: Attacking RLHF by Injecting Poisoned Preference Data.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Best-of-Venom: Attacking RLHF by Injecting Poisoned Preference Data

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:03.450932Z digest=sha256:855e918333c0cd4c85c268e6d3271560334ff5c74ecfd97627ee6478b509c499

Observation 4c5bc4b2-3cf6-451b-8f0e-fa0f87f8f7ff · outbound

This paper cites Poisoning Attacks against Support Vector Machines.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Poisoning Attacks against Support Vector Machines

Reference 2

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no resolver link, observed 2026-08-07T11:18:03.502246Z

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source=pdf_text observed=2026-08-07T11:18:03.502246Z digest=sha256:645e532437745cd896c3ed3d93164ec0ba7e4644ba58a7b1b1bba724f530356e

Observation 9a7d5036-1e5b-40ac-86eb-e677ced3f55f · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Training Diffusion Models with Reinforcement Learning

Reference 3

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no resolver link, observed 2026-08-07T11:18:03.581756Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:18:03.581756Z digest=sha256:aa06a8a5a5168c5b460dbb8eda79b3db7569dcbcb9af21722bd59955295ac21a

Observation cc6c3d91-5ef5-4e50-bae9-873226a676fc · outbound

This paper cites A survey on generative diffusion models.IEEE Transactions on Knowledge and Data Engineering, 2024.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF A survey on generative diffusion models.IEEE Transactions on Knowledge and Data Engineering, 2024

Reference 4

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no resolver link, observed 2026-08-07T11:18:03.657237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:03.657237Z digest=sha256:1dfab27375ba7225da846340f5cc4a04f5c84e3fac1f6a73d806ae90a6ade647

Observation 08bfd459-da94-4898-be9a-85e1de397f36 · outbound

This paper cites Trojdiff: Trojan attacks on diffusion models with diverse targets.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Trojdiff: Trojan attacks on diffusion models with diverse targets

Reference 5

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unresolved
no resolver link, observed 2026-08-07T11:18:03.750828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:03.750828Z digest=sha256:84ad0a9e1969fddbfd5ebf8b924ade5b02dded0c829ee89c60a20a130292f424

Observation 161f05ef-a822-4d0d-9935-86d69a731fc9 · outbound

This paper cites Amplifying membership exposure via data poisoning.Advances in Neural Information Processing Systems, 35:29830– 29844, 2022.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Amplifying membership exposure via data poisoning.Advances in Neural Information Processing Systems, 35:29830– 29844, 2022

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-07T11:18:08.561155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:03.836456Z digest=sha256:f1fe8a5072e032847eb3e64d4eeedca869d1993f5750c9d39a18b93aa6db5625

Observation e758bf7b-1171-43c7-83a9-775a9b3d7d14 · outbound

This paper cites Villandiffusion: A unified backdoor attack framework for diffusion models.Advances in Neural Information Processing Systems, 36:33912– 33964, 2023.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Villandiffusion: A unified backdoor attack framework for diffusion models.Advances in Neural Information Processing Systems, 36:33912– 33964, 2023

Reference 7

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:18:03.929697Z digest=sha256:af7188e13ae992ebfc62d96f0936a86b93d3378d7c830191a375bc024f8a3b90

Observation d73902d0-311e-4dd5-b6c3-8fe604230f35 · outbound

This paper cites Diffusion models in vision: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(9):10850–10869, 2023.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Diffusion models in vision: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(9):10850–10869, 2023

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:03.996111Z digest=sha256:e43eef4efe6b403d7c9943ec8533aae7eccea504ebd1917350e5d0b263aae5f7

Observation 37ae54e1-c492-41d2-9d81-98f72add11b5 · outbound

This paper cites A survey on data poisoning attacks and defenses.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF A survey on data poisoning attacks and defenses

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-07T11:18:08.342924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:04.089124Z digest=sha256:8e280d7df9c49972f4c7895296619d51bd738d03d36032f747233982e052c0e7

Observation 154ec68f-8638-40af-9e34-1f2dc9129a4a · outbound

This paper cites Dpok: Reinforcement learning for fine-tuning text-to-image diffusion models.Advances in Neural Information Processing Systems, 36:79858–79885, 2023.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Dpok: Reinforcement learning for fine-tuning text-to-image diffusion models.Advances in Neural Information Processing Systems, 36:79858–79885, 2023

Reference 10

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source=pdf_text observed=2026-08-07T11:18:04.152983Z digest=sha256:a23918c9ce9c14218e384e98e11d9fc4caa765fd587fce80a3b9fcf0d44b0958

Observation 8d7a39fa-b174-45d3-9f5e-7a4c4ddc7b8f · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.Advances in Neural Information Processing Systems, 36:36652–36663, 2023.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Pick-a-pic: An open dataset of user preferences for text-to-image generation.Advances in Neural Information Processing Systems, 36:36652–36663, 2023

Reference 11

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source=pdf_text observed=2026-08-07T11:18:04.220875Z digest=sha256:f9e413926915f57ca9a55fac9d4cf425f5dbccd42c1ce82666395bf20a4fccbc

Observation b37bad84-ff1b-432d-a2b4-af5336bffd74 · outbound

This paper cites Aligning Text-to-Image Models using Human Feedback.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Aligning Text-to-Image Models using Human Feedback

Reference 12

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no resolver link, observed 2026-08-07T11:18:04.275836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:04.275836Z digest=sha256:616bf9b0eb7af929e5e8a9047dbdebaa34547ff2b060610def92e2d22a812b5f

Observation ae670811-d078-4079-a6b9-4f6066a54382 · outbound

This paper cites Blip: Bootstrapping language- image pre-training for unified vision-language understanding and generation.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Blip: Bootstrapping language- image pre-training for unified vision-language understanding and generation

Reference 13

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source=pdf_text observed=2026-08-07T11:18:04.336470Z digest=sha256:3793713ee678d3a8bdd8289163a0a022a4428e8ac87d1ab84417c3ff395d17c3

Observation 48f08532-d743-47ae-a892-36c3f5f6222f · outbound

This paper cites Inform: Mitigating reward hacking in rlhf via information-theoretic reward modeling.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Inform: Mitigating reward hacking in rlhf via information-theoretic reward modeling

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-07T11:18:08.117549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:04.397499Z digest=sha256:c21c394ba8a6fa8e2382f20e1735df1b030efbca27cc50257734a61bf65683b8

Observation e2d3d101-2de6-41d1-ba22-f1a52ee1920b · outbound

This paper cites Backdooring Bias ($B^2$) into Stable Diffusion Models.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Backdooring Bias ($B^2$) into Stable Diffusion Models

Reference 15

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source=pdf_text observed=2026-08-07T11:18:04.459824Z digest=sha256:3dda2f44f9a4833da5b32b370d4843d0886ad7b6a833657a6ce897e86b45272f

Observation 7f949655-be9a-4032-8c9f-09a7e5a7ad61 · outbound

This paper cites From trojan horses to castle walls: Unveiling bilateral data poisoning effects in diffusion models.Advances in Neural Information Processing Systems, 37:82265–82295, 2024.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF From trojan horses to castle walls: Unveiling bilateral data poisoning effects in diffusion models.Advances in Neural Information Processing Systems, 37:82265–82295, 2024

Reference 16

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raw_fallback, observed 2026-08-07T11:18:07.974486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:04.508075Z digest=sha256:8b05e52e001edc7e83a341fc4591b47ed9bf5db2b1eae21053d2adf0ba308caf

Observation 59a7cbec-dd05-4dad-bc13-825bbfec08d6 · outbound

This paper cites Learning transferable visual models from natural language supervision.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Learning transferable visual models from natural language supervision

Reference 17

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:18:04.576132Z digest=sha256:fb13baa9911db3d863d4304f2c3bcceaf0ee3fc7a1c1f2237faa742054f5a2e6

Observation b6007439-ac16-4601-bf79-aefa8c707234 · outbound

This paper cites Universal Jailbreak Backdoors from Poisoned Human Feedback.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Universal Jailbreak Backdoors from Poisoned Human Feedback

Reference 18

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:18:04.647947Z digest=sha256:7a011effd9af584a5cde5900bfd608d71d4a663e470347916e129db27c147587

Observation 50d6e421-ac7a-49fb-9868-0ca8442a5a76 · outbound

This paper cites Laion- 5b: An open large-scale dataset for training next generation image-text models.Advances in neural information processing systems, 35:25278–25294, 2022.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Laion- 5b: An open large-scale dataset for training next generation image-text models.Advances in neural information processing systems, 35:25278–25294, 2022

Reference 19

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source=pdf_text observed=2026-08-07T11:18:04.739251Z digest=sha256:9a200b68957da0bcf5c2176ca663b5f2620d67e7bce93b190c1987dd1f9f57b9

Observation 5e05d140-3491-48fb-814f-a6e74ae761a1 · outbound

This paper cites Poison frogs! targeted clean-label poisoning attacks on neural networks.Advances in neural information processing systems, 31, 2018.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Poison frogs! targeted clean-label poisoning attacks on neural networks.Advances in neural information processing systems, 31, 2018

Reference 20

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raw_fallback, observed 2026-08-07T11:18:07.823975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:04.821469Z digest=sha256:40b9f14ca95d064c1d7206106088dc5dd824f9c7a60130c38a86579831ffede0

Observation 54f7eae3-a740-4c7a-ad9f-5aac9f7f5c47 · outbound

This paper cites Nightshade: Prompt-specific poisoning attacks on text-to-image generative models.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Nightshade: Prompt-specific poisoning attacks on text-to-image generative models

Reference 21

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raw_fallback, observed 2026-08-07T11:18:07.666359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:04.886395Z digest=sha256:c60e1702601e7c11b7ea4ea46d1864a6f585b3bc5406df7d99c473084858a8ae

Observation 9380d697-33e0-47d7-8aa8-f39f48fe80e4 · outbound

This paper cites Defining and characterizing reward gaming.Advances in Neural Information Processing Systems, 35:9460– 9471, 2022.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Defining and characterizing reward gaming.Advances in Neural Information Processing Systems, 35:9460– 9471, 2022

Reference 22

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source=pdf_text observed=2026-08-07T11:18:04.937273Z digest=sha256:d853c8fbd4f3b2f87085e033af895a9e7cb4943c53b47ec5f862df2fdb5c7f50

Observation ff8d6a03-ecc2-4516-9809-9da4766a8a65 · outbound

This paper cites Attacks and defenses for generative diffusion models: A comprehensive survey.ACM Computing Surveys, 57(8):1–44, 2025.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Attacks and defenses for generative diffusion models: A comprehensive survey.ACM Computing Surveys, 57(8):1–44, 2025

Reference 23

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raw_fallback, observed 2026-08-07T11:18:07.493436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:04.989332Z digest=sha256:44789e65ced993c6bc4c608a541a08bbf67e396b3aa3deb22a7f0de0e2c6a403

Observation c35545e0-c05a-4570-9d41-3a9605c58095 · outbound

This paper cites Rlhfpoi- son: Reward poisoning attack for reinforcement learning with human feedback in large language models.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Rlhfpoi- son: Reward poisoning attack for reinforcement learning with human feedback in large language models

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T11:18:07.285820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:05.061206Z digest=sha256:0be33d5b810e761df3ec12f56ec4b6ccdac2ab557b62d9ba8d19242b28af2ec4

Observation d7e337ca-da47-4492-90f3-2a6be172ac8c · outbound

This paper cites Preference Poisoning Attacks on Reward Model Learning.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Preference Poisoning Attacks on Reward Model Learning

Reference 25

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:18:05.136617Z digest=sha256:5be806ff03569a10603e82e1bf7ccae2b23a64bb77dddaa82b95397dc9e0c753

Observation 6c07524e-4b2d-4435-b510-47ce1c7e16e8 · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 26

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source=pdf_text observed=2026-08-07T11:18:05.209176Z digest=sha256:e8865a9de6e91836b15887270f5957ef6167558eb5a577956b3abd3a92b6a2cf

Observation 5955355f-aeb3-4f18-a634-ce49693845f4 · outbound

This paper cites Human preference score: Better aligning text-to-image models with human preference.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Human preference score: Better aligning text-to-image models with human preference

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:05.279581Z digest=sha256:4599b5a4e97904c4a7d0979e903c5f27fadf281a4447003f1576d953793371c4

Observation 180fd271-a4cc-4700-9b6f-c017fbcedf9d · outbound

This paper cites Adversarial label flips attack on support vector machines.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Adversarial label flips attack on support vector machines

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-07T11:18:07.088382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:05.358874Z digest=sha256:baa2a8d4c2a8a3d605a58656daefa05434ab8db67d3adab0efe1ae0ae8a8e669

Observation fd29907a-9f14-49c8-b5f2-e187b32ce0d1 · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 29

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no resolver link, observed 2026-08-07T11:18:05.433869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:05.433869Z digest=sha256:5174b51e0e7cbb0e6032e2bc43f406bac3eb5d96f5958375b0d6e4fd61cf6046

Observation 859bd800-3a36-4ae6-9149-195f24f1cdce · outbound

This paper cites Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models

Reference 30

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:18:05.514154Z digest=sha256:1db9ba999f323e5b2f3a6c65b0f0d4ab229876f0383b5bba27f541feae7ef881

Observation 3e6ebbea-9cba-46fe-a5b7-8c55c5a571cc · outbound

This paper cites Using human feedback to fine-tune diffusion models without any reward model.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Using human feedback to fine-tune diffusion models without any reward model

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:18:06.916979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:05.550741Z digest=sha256:48648bff905cac40e802564bd2f1b2969314ef76dc55e78ee2e3b6d95d070be0

Observation 65970768-5df4-4d28-8b38-2231aaf7b64e · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications.ACM Computing Surveys, 56(4):1–39, 2023.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Diffusion models: A comprehensive survey of methods and applications.ACM Computing Surveys, 56(4):1–39, 2023

Reference 32

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no resolver link, observed 2026-08-07T11:18:05.607651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:05.607651Z digest=sha256:a0e21980f6f6edf97400fbf1976a43578f12b34e4579c03a0f57d9bd158c33bb

Observation 3442542c-30c4-4352-af91-c631d8821e31 · outbound

This paper cites Poisonprompt: Backdoor attack on prompt-based large language models.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Poisonprompt: Backdoor attack on prompt-based large language models

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-07T11:18:06.732475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:05.679279Z digest=sha256:032879ceb972d6de4cbcfb467598b94f30860061b0d475cfb5a0cebc86b048d9

Observation 0341263c-6b8a-4661-8ce4-95d8a6a8b82d · outbound

This paper cites Text- to-image diffusion models can be easily backdoored through multimodal data poisoning.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Text- to-image diffusion models can be easily backdoored through multimodal data poisoning

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:05.729802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:05.729802Z digest=sha256:02d127bc875f4e0e31e318394d27c14dece762dca3b23dcd519aa1f8cf66c30d

Observation e7e926ed-4c2b-437d-bc93-608708a72727 · outbound

This paper cites Text-to-image Diffusion Models in Generative AI: A Survey.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Text-to-image Diffusion Models in Generative AI: A Survey

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:05.800563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:05.800563Z digest=sha256:5485a9628ddfc5726ac7c4ed557011de5d8522b445457be5df36cc615e8de658

Observation 2b07a20c-d990-48b9-a212-dd7b6110fd25 · outbound

This paper cites Aligning few-step diffusion models with dense reward difference learning.arXiv preprint arXiv:2411.11727, 2024.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Aligning few-step diffusion models with dense reward difference learning.arXiv preprint arXiv:2411.11727, 2024

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T11:18:05.875543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:05.875543Z digest=sha256:8f0ccbbaba0aa158ad285624f8ed4f30590ea6fbaf380713786668f718c168cd

Observation e09bfbe4-338b-43b7-8659-9d26de7da513 · outbound

This paper cites Shielding collaborative learning: Mitigating poisoning attacks through client-side detection.IEEE Transactions on Dependable and Secure Computing, 18(5):2029–2041, 2020.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Shielding collaborative learning: Mitigating poisoning attacks through client-side detection.IEEE Transactions on Dependable and Secure Computing, 18(5):2029–2041, 2020

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:18:06.433447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:05.936387Z digest=sha256:7a1d002358f3f8e845aebfbb9078fa279b82deea3e3bc4f815eeeb686d0b5546

Observation e9268e5d-894a-41da-860e-3e09c4e33196 · outbound

This paper cites Diffusion Models for Reinforcement Learning: A Survey.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Diffusion Models for Reinforcement Learning: A Survey

Reference 38

Resolution
malformed identifier
no resolver link, observed 2026-08-07T11:18:05.968907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:18:05.968907Z digest=sha256:7c15f41ddd685c5762305c6e30ecf9de236657252ba524f493f3e9d860282b6c

Observation c89c4aad-343c-4484-8241-cfbb1765f46e · outbound

This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:18:06.292128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:18:06.054981Z digest=sha256:1abe7dee220596c736eab4a5efc467066cb0cda4327c5c2cc00084cc5996919e

Pith citing papers

Observation 4b6439e1-8155-4c28-8686-855b5bee67a9 · inbound

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges cites this paper.

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF

Reference 221

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:00:28.455819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T13:58:53.430492Z digest=sha256:da9e58cbdd50f05c86284b00aa0a276bfceb245881165e33bae80b6dcb798620

Observation b58c985f-04cf-476f-ab99-e55e1c7a5c69 · inbound

Power Reinforcement Post-Training of Text-to-Image Models with Super-Linear Advantage Shaping cites this paper.

Power Reinforcement Post-Training of Text-to-Image Models with Super-Linear Advantage Shaping BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:16:29.437150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-12T03:33:40.994346Z digest=sha256:b0d943c67d14ead72358759b882feea1d66085e11730c93814f388d7c65feee1

Observation 2607aec9-0022-4ee2-95b0-b7697c054fc0 · inbound

Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization cites this paper.

Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF

Reference 295

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T01:37:30.523466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-27T16:26:34.918099Z digest=sha256:3795327500c049132c8cfa29a0925642b18d742d519531468c6a19bd1ddd4376