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Paper Citation Record · LEDGER

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets

As of 15 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 2 inbound Pith citation observations for arXiv:2412.07775.

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

pith.paper-citation-record.v1
2412.07775 v6

Coverage vector

measured 87 of 87 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:35:18.771109Z

measured 89 of 89 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T08:00:03.272296Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

87 of 87 outbound references displayed

  • verified exact1
  • verified fuzzy59
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69b52180-c45f-4c42-a2df-7f04418bd58d · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.173836Z digest=sha256:e79f37f0cbc47be517e336089714e69c26c9d236fe5e74f2e597087872e1d39f

Observation 946f1b02-da05-4847-b5a3-61bc5d2ed302 · outbound

This paper cites Gflownet foundations.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Gflownet foundations

Reference 2

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no resolver link, observed 2026-08-11T18:35:18.182647Z

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source=pdf_text observed=2026-08-11T18:35:18.182647Z digest=sha256:f9402d1fa14e3124115436b6e15cf8892fa68a09f1d4ca12e84ceba83ce9f8b7

Observation a5c3ea41-84f8-41ff-9dcc-87b83533ddb2 · outbound

This paper cites Training diffusion models with reinforcement learning.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Training diffusion models with reinforcement learning

Reference 3

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no resolver link, observed 2026-08-11T18:35:18.190913Z

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source=pdf_text observed=2026-08-11T18:35:18.190913Z digest=sha256:49d20d5bc3502d7287e8d9d8ee85a5ac03023ddec9cc02b985571c51a3d3f4fb

Observation 5742e584-ecc4-4338-bdd3-084b390058aa · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.198059Z digest=sha256:317dd1375c4dd807edb4e01475beea0a12c76bc7622087b9e07a4080eddd2be7

Observation 9cf2b8df-b28b-4afd-a035-34dfb97ba632 · outbound

This paper cites Deep reinforcement learning from human preferences.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Deep reinforcement learning from human preferences

Reference 5

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T18:35:18.206526Z digest=sha256:a8a3115e7cd395d8f81cca5188aa7df90cc0b50a94ca5605d6563eb00ffc752c

Observation 7b5161b1-2c9f-42b3-ab93-b6b5d1f2be98 · outbound

This paper cites an unresolved cited work.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Unresolved cited work

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.213651Z digest=sha256:82502ec48bd955cd6d8655f4c8316a24be62e58111f5c4ceb2129a1f52ae38aa

Observation fb8e5ee7-8a22-4a97-9c30-f1ae234fdb60 · outbound

This paper cites Generative Flow Networks: Theory and Applications to Structure Learning.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Generative Flow Networks: Theory and Applications to Structure Learning

Reference 7

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no resolver link, observed 2026-08-11T18:35:18.219836Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T18:35:18.219836Z digest=sha256:a5cc167158cc38703a30cbf05e99275c7fd5e962a2d10d682964dbe8a0ae05d9

Observation cb708f8d-9aae-4904-a6cc-df3f2476c6ce · outbound

This paper cites Bayesian structure learning with generative flow networks.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Bayesian structure learning with generative flow networks

Reference 8

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source=pdf_text observed=2026-08-11T18:35:18.232149Z digest=sha256:861a1038fc08e0eecf99df4c034735b03ff30039c3756e3371f6a8edbc2b2bb9

Observation 7f2a2744-ec30-4d91-bc98-7924d9054f47 · outbound

This paper cites Diffusion models beat gans on image synthesis.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Diffusion models beat gans on image synthesis

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.242260Z digest=sha256:e36c4433e1a6a42a8e781830e967c93577a959b7bcfda345a8d94dfb737b903a

Observation bff1b5ce-eb0d-4819-b4f7-b449d05b68c2 · outbound

This paper cites an unresolved cited work.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Unresolved cited work

Reference 10

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no resolver link, observed 2026-08-11T18:35:18.252074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.252074Z digest=sha256:bea91f60001caea4237b474fdb0f8ad94cbb5080106cc1a0a39d5baf195d2e29

Observation 7285e991-e1eb-48f3-a602-15a81b7783f2 · outbound

This paper cites RAFT: Reward ranked finetuning for generative foundation model alignment.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets RAFT: Reward ranked finetuning for generative foundation model alignment

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-11T18:35:21.281623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 47c6df52-225e-4349-8299-48dc1035c935 · outbound

This paper cites Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, and Kimin Lee.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, and Kimin Lee

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-11T18:35:21.244732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 464e5ef4-4145-4d53-8039-b2f23a24709d · outbound

This paper cites Graph- dreamer: Compositional 3d scene synthesis from scene graphs.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Graph- dreamer: Compositional 3d scene synthesis from scene graphs

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-11T18:35:21.201591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 34e65e5f-8a98-4c0a-b78c-3bfde3151121 · outbound

This paper cites Gradient guidance for diffusion models: An optimization perspective.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Gradient guidance for diffusion models: An optimization perspective

Reference 14

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raw_fallback, observed 2026-08-11T18:35:21.163740Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.297510Z digest=sha256:6c125cfe8d22ea8071e6794cf11529bd2c8e42efb71d9a9b05707d7d73f30954

Observation b094d3b7-7235-4067-ac48-5c0b7af52d0a · outbound

This paper cites Reinforcement learning with deep energy-based policies.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Reinforcement learning with deep energy-based policies

Reference 15

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raw_fallback, observed 2026-08-11T18:35:21.134259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.304143Z digest=sha256:2c06c74fa0df8aa851e30e17e3a24c21aece6155c27f4a2b4733ce7c9de8da3b

Observation 76a31a8e-9bbd-4529-9846-3e0a96359d1e · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 16

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.309475Z digest=sha256:ebbd8ac795e1b63c59e89a70338ad2dadee4ef7d009d8e9ad8f4abf986fd0513

Observation d09bc8d1-cd94-4f3d-8478-1ac6cbced053 · outbound

This paper cites Denoising diffusion probabilistic models.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Denoising diffusion probabilistic models

Reference 17

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raw_fallback, observed 2026-08-11T18:35:21.073540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f3372637-6dee-4e89-b9dd-bbd845a589f4 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Imagen Video: High Definition Video Generation with Diffusion Models

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.320618Z digest=sha256:e7cadc6011f38b6c2d99df5b89558774c0fecbb02b900ccacb5774be8cc12385

Observation c2897163-7dbe-427e-89a4-b632f94a93a4 · outbound

This paper cites Video diffusion models.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Video diffusion models

Reference 19

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source=pdf_text observed=2026-08-11T18:35:18.329422Z digest=sha256:6e74ea1ed949745c976e41356ecc1b32130ab77b00ae4dd05977e9b10b50909f

Observation e9fea3f7-658f-4c99-83ce-066b7ebd6a46 · outbound

This paper cites Equivariant diffusion for molecule generation in 3d.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Equivariant diffusion for molecule generation in 3d

Reference 20

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raw_fallback, observed 2026-08-11T18:35:21.012995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.341294Z digest=sha256:a82e4e05f410ff8952f4fd0a44db0202bcf0972b8ffc76b24db6f4ef06cdbc5d

Observation 983bf681-0626-4cd5-a6c5-85aeb5a66211 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 21

Resolution
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raw_fallback, observed 2026-08-11T18:35:20.982692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.346474Z digest=sha256:a415c589c8cf6824a32e497ad6b416f3a59ba4e50687e6b9e206ee85e31518ff

Observation 4e622dcc-8b86-4068-ac65-423c76536334 · outbound

This paper cites Re- ward learning from human preferences and demonstrations in atari.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Re- ward learning from human preferences and demonstrations in atari

Reference 22

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raw_fallback, observed 2026-08-11T18:35:20.952981Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 0bb46774-fedf-4234-bb55-475d8a319aea · outbound

This paper cites Biological sequence design with gflownets.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Biological sequence design with gflownets

Reference 23

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raw_fallback, observed 2026-08-11T18:35:20.922488Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.363563Z digest=sha256:93e14f2c670c56fb1b37100ad7a461caca6a6925e7004fefda8328917471112e

Observation faee9562-9285-410f-90a4-841b00f63087 · outbound

This paper cites Hartford, Cheng-Hao Liu, Alex Hernández-García, and Yoshua Bengio.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Hartford, Cheng-Hao Liu, Alex Hernández-García, and Yoshua Bengio

Reference 24

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raw_fallback, observed 2026-08-11T18:35:20.895526Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.373356Z digest=sha256:61cb084f139a13f5b9a40377e3571a09588cb5c32e65cb73c8bb1e4e0df10b60

Observation 384114d7-80c2-43e5-b2dd-45b848ff9f27 · outbound

This paper cites Information theory and the central limit theorem.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Information theory and the central limit theorem

Reference 25

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raw_fallback, observed 2026-08-11T18:35:20.856296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.379503Z digest=sha256:95db94518b284a5fb7cfd7fc1d932a4eb9230aa95cc0420318a981a2e6c5def8

Observation 1cf8561f-e97b-4001-bc50-5c809d56e6ec · outbound

This paper cites Diffusion models as constrained samplers for optimization with unknown constraints.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Diffusion models as constrained samplers for optimization with unknown constraints

Reference 26

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raw_fallback, observed 2026-08-11T18:35:20.832667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.385435Z digest=sha256:076bf755cfe63129792713146c851b6016c91492af764c943b3af2056abe2624

Observation 44710081-dbe3-4508-a84d-6cd75d507b3e · outbound

This paper cites A theory of continuous generative flow networks.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets A theory of continuous generative flow networks

Reference 27

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raw_fallback, observed 2026-08-11T18:35:20.804938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.390866Z digest=sha256:fc32ddd60e1997cc05a9c946171abc8ce3683ead6d5db2097c83971ea3c79ab0

Observation 48d6aab0-6e08-4a07-aa32-18162eb31140 · outbound

This paper cites Laion aesthetic score predictor.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Laion aesthetic score predictor

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.769145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.396686Z digest=sha256:7755674fb95f3b5787776e03fe17790201167d12f030d4feeaffe800cad2c5a6

Observation 21d8d3c2-d335-4199-bab7-72bc95904e60 · outbound

This paper cites Qgfn: Controllable greediness with action values.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Qgfn: Controllable greediness with action values

Reference 29

Resolution
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raw_fallback, observed 2026-08-11T18:35:20.740801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.401928Z digest=sha256:32ec74043d5f5fc2078001f33a50eeccc642f21c64a0b9aaab6bd77365fdaf36

Observation 0df7fb52-0cf6-41f6-bdda-18605a8b0fa6 · outbound

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

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Aligning Text-to-Image Models using Human Feedback

Reference 30

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unresolved
no resolver link, observed 2026-08-11T18:35:18.407562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.407562Z digest=sha256:51abb6ae6aae2720b34925f09e074373e948135a7ffe736e106f0bd4062c3577

Observation 1c7c8552-3bb8-4771-8d6e-1cf572997de4 · outbound

This paper cites Flow matching for generative modeling.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Flow matching for generative modeling

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.713310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.413457Z digest=sha256:59fe927994770022bffa7597c60bfa7a16400edf124668578438139c774ecee3

Observation 4a131da6-f282-445f-ae9b-556e1fa7a975 · outbound

This paper cites Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design

Reference 32

Resolution
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local_arxiv, observed 2026-08-11T18:35:19.134500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.418787Z digest=sha256:2e9cf5ca8b1f631378eb6e3f6f45f4c1fe1aca427e86a824b1a3c09fff65c369

Observation 5d590b0f-1d7e-4d60-ab35-8c7092d34b92 · outbound

This paper cites Parameter-efficient orthogonal finetuning via butterfly factorization.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Parameter-efficient orthogonal finetuning via butterfly factorization

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.686570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.426207Z digest=sha256:d80b36f1089652ffa2d1312ce25a9cebc4a0a65144b99dcec0597298086e5a79

Observation 2102ba86-cdf6-446f-9422-2bbb835f619c · outbound

This paper cites Meshdiffusion: Score-based generative 3d mesh modeling.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Meshdiffusion: Score-based generative 3d mesh modeling

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.655876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.431585Z digest=sha256:6b4fc3634a34a17670c356bd159f5d0ce7b4bb4476b4802848b22e949363f645

Observation dc8fc3f2-e72f-4206-86e2-e56bbdcf6b91 · outbound

This paper cites Ghost on the shell: An expressive representation of general 3d shapes.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Ghost on the shell: An expressive representation of general 3d shapes

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.637191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.436913Z digest=sha256:ac88d464a64f74859ca64f9383b8fd700ceac7e0a2ff50b6d10e58db5ad0253a

Observation 1a92e135-9d5b-43cd-b5ed-e836fcfbfba5 · outbound

This paper cites Discrete diffusion modeling by estimating the ratios of the data distribution.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Discrete diffusion modeling by estimating the ratios of the data distribution

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.586855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.447925Z digest=sha256:0fc45f96ea3bee15ae8486babbd9b281abcb33ddef7a9e0ca7c4e1d2ac971575

Observation 7fc01c3a-374e-4218-becf-76f139af1cc7 · outbound

This paper cites La- tent diffusion for language generation.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets La- tent diffusion for language generation

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.556304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.453315Z digest=sha256:f6897d2faf7ba41f38928ec985e7454c126fbbf05d52014e421d8027c6a461dc

Observation 0162070b-e704-4692-a67d-0bf3650d4f58 · outbound

This paper cites Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.530105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.459740Z digest=sha256:135dbe6d57c05822f579caad341b22bf0e539918783dffbac96e693cb8319820

Observation 71d918c1-e608-4437-b860-ba46bac91c01 · outbound

This paper cites Trajectory balance: Improved credit assignment in gflownets.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Trajectory balance: Improved credit assignment in gflownets

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.505599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.466572Z digest=sha256:55b329dc77dfc6df370c54a5aec8b8532470f39b4d1bf18f0f0bfbf4b34fb080

Observation 13af2f25-af3b-41f2-b53a-16eb32cbb835 · outbound

This paper cites GFlowNets and variational inference.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets GFlowNets and variational inference

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.472968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.471561Z digest=sha256:845a7a2425faf82c11fea1808170a1563004260f797402962c2cc299da9b394d

Observation 0c6a089c-8937-42ff-80a7-314447ea7eed · outbound

This paper cites Chip Placement with Deep Reinforcement Learning.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Chip Placement with Deep Reinforcement Learning

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.477397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.477397Z digest=sha256:97a272ecf3a638d87e0875b6d2bbc6e2a0a7122e05188dac72b54f2d4aa39714

Observation 9d5671e6-571e-4a0e-80f9-e8615a05dbc6 · outbound

This paper cites Bridging the gap be- tween value and policy based reinforcement learning.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Bridging the gap be- tween value and policy based reinforcement learning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.435133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.483549Z digest=sha256:5779576f9c57613d6540a4a4048f2a87745eb83f4ee06ec04c28e122458fbeed

Observation 65798b6a-c463-4972-a6e8-556e40c094ab · outbound

This paper cites Training language models to follow instructions with human feedback.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Training language models to follow instructions with human feedback

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.392500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.489564Z digest=sha256:5885b52d67ebf100f9c897cc7faa24977b4fe23a6b43a4e13c44835d792688e7

Observation c841f567-a427-4783-b095-02151f059fa6 · outbound

This paper cites Better training of gflownets with local credit and incomplete trajectories.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Better training of gflownets with local credit and incomplete trajectories

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.358260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.494414Z digest=sha256:1ffcf08c9901b6c5c31e9416fd9be95ef90bf7b9414b0a0b0898c20d2ab3c60a

Observation 066c170e-927a-448c-9b84-79be1f3bae98 · outbound

This paper cites Generative augmented flow networks.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Generative augmented flow networks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.326389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.499119Z digest=sha256:5a316308ac76462b299fb656aad014b75216f85bfed706aa8458b0a09d08945b

Observation ba384a4c-0fab-4814-81cf-e518a4925b6d · outbound

This paper cites Stochastic gen- erative flow networks.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Stochastic gen- erative flow networks

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.293921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.504031Z digest=sha256:24bfe52919a337c0c3eefe0ec5d4e15c307533b3c5e78729cc6fcf96f33b9235

Observation 6c11da50-123a-41b0-bb62-808da6902716 · outbound

This paper cites Dreamfusion: Text-to-3d using 2d diffusion.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Dreamfusion: Text-to-3d using 2d diffusion

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.260133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.508994Z digest=sha256:164169855fd70270a2fd09443b73e8731b554c9d1b04afda0c9ad94a903e1bcb

Observation 33625d77-f48e-4add-b96a-eb739beec1e9 · outbound

This paper cites Aligning Text-to-Image Diffusion Models with Reward Backpropagation.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Aligning Text-to-Image Diffusion Models with Reward Backpropagation

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.514408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.514408Z digest=sha256:309adc0f4ccfef4534dc3e8248a4ed69cd0a660b769acb236088ff1395b02b7d

Observation 82d54430-66ca-4ae1-8a75-81b5b1bd7537 · outbound

This paper cites Controlling text-to-image diffusion by orthogonal finetuning.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Controlling text-to-image diffusion by orthogonal finetuning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.227792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.519709Z digest=sha256:dbb073bbdef554b73405f798135c144600e55f1f00a99a54824b1ed312130128

Observation e0fd1586-c1d1-47ac-a318-0fe00de4a241 · outbound

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

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Direct preference optimization: Your language model is secretly a reward model

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.191105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.525095Z digest=sha256:7253c029066127a110315e2c48b625979cdf1f44d4391b695962ad81f50ae58b

Observation d957ecb6-118a-4178-bab5-28ada0ed4bc8 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets High-resolution image synthesis with latent diffusion models

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.157310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.529856Z digest=sha256:1a294429221fa21da377a95877f8e7a477eacb8d8a6b99eb2b180a2106b71a27

Observation 9bced8fc-c7e3-493b-8622-9e598dc1076b · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets U-net: Convolutional networks for biomedical image segmentation

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.534689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.534689Z digest=sha256:0f2a8ec70e7ff19cbb65cec657fc6481f7eb10ea484fa18fa7c5c1c81d4a2af9

Observation 47317b1d-338e-44d8-a957-b03343f0427b · outbound

This paper cites Photo- realistic text-to-image diffusion models with deep language understanding.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Photo- realistic text-to-image diffusion models with deep language understanding

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.108942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.539368Z digest=sha256:16ad30c6bfd7e3a5342fbc84bd22803ae4b2aafcac17487e618680569945f982

Observation cd1044e4-c028-4d8c-a98a-e68ac5fc2eff · outbound

This paper cites Trust region policy optimization.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Trust region policy optimization

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.071782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.544933Z digest=sha256:ad86dc99113c4ced485f6c0dfd622baf8f862bac434048bb905c2135c6d180fa

Observation df4645e5-087c-4c46-a410-3b8dc9d9bc27 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Proximal Policy Optimization Algorithms

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.550336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.550336Z digest=sha256:fac40f056b5c48beabc3eed13a5eef321a49f94b329f255252afa6f313f3ac05

Observation d03ca208-cef2-463a-8278-41d45dac72e5 · outbound

This paper cites Improved off-policy training of diffusion samplers.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Improved off-policy training of diffusion samplers

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.041634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.560831Z digest=sha256:af01bf4d1810cb42c7bd7701e3336910e18fc8c86193f254597d7c51889e2ea2

Observation 0c2b181a-6e09-4ec1-96ee-f5347e5f72de · outbound

This paper cites Towards understanding and improving gflownet training.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Towards understanding and improving gflownet training

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:20.011962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.566457Z digest=sha256:c0e54b4bb5b4d7d927a8e9c25a1d4e49ba65c9140d0e14c025cec4194e86c519

Observation 33de117c-c195-4889-a2c2-dfbf894fe135 · outbound

This paper cites Maddison, Arthur Guez, L.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Maddison, Arthur Guez, L

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.987899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.573835Z digest=sha256:c7bed989f7b40d248fc4a3e2b12bceaeb47b14eb474545f8915c5df55077afeb

Observation 4e963957-c07d-4825-ba72-bb6b57d9fdec · outbound

This paper cites Denoising diffusion implicit models.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Denoising diffusion implicit models

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.960626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.579019Z digest=sha256:8d9924e5fcdb398554d87082219e19992be383a2af1f1efdc5833a344e2ca438

Observation e1e90915-cf7f-4ad7-8d52-f89b71db14e0 · outbound

This paper cites Loss-guided diffusion models for plug-and-play controllable generation.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Loss-guided diffusion models for plug-and-play controllable generation

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.935649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.584212Z digest=sha256:a18ce42ec4d877c7942cc882d076885ec0db91fda4d4f23e386a71806cce730a

Observation 366b44fd-3eb0-4252-8806-b664facfa4b4 · outbound

This paper cites Score-based generative modeling through stochastic differential equations.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Score-based generative modeling through stochastic differential equations

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.910607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.589418Z digest=sha256:7c5d65164fad04825642ed5af7e63b3ab0c59facb8d785ebf5f6c40fb7c3dd64

Observation 2c805000-849b-49ec-8f99-af1406600a50 · outbound

This paper cites Ziegler, Ryan Lowe, Chelsea V oss, Alec Radford, Dario Amodei, and Paul Christiano.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Ziegler, Ryan Lowe, Chelsea V oss, Alec Radford, Dario Amodei, and Paul Christiano

Reference 62

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verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.881278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.594810Z digest=sha256:cc4b8d068cb7399319a22407f260b5f330a906708960d0d74441e3b716c1da6d

Observation c1a260e3-8e29-4619-85fb-1b8b8457ebf9 · outbound

This paper cites an unresolved cited work.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Unresolved cited work

Reference 63

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unresolved
raw_fallback, observed 2026-08-11T18:35:19.852274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.599619Z digest=sha256:a5e5017672f5e494ae865b27212e18f9815f7347ac90292bd85f9ddf95b41fb7

Observation 4f8d17fa-6086-4d62-b6f5-154cca553e50 · outbound

This paper cites Generative flow net- works as entropy-regularized rl.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Generative flow net- works as entropy-regularized rl

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.825650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.604633Z digest=sha256:5238f8463a7f5ab0514a452886ed846234475753045e5f31dd36afe5b2051260

Observation 2318703c-9446-4614-8758-70adfcf8b413 · outbound

This paper cites Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.610551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.610551Z digest=sha256:590bf8f9b33bc9c3da6aad1e10ccb6b9c8830f52b2fdc0dcbb33adc60bffc6ca

Observation db4c5ba9-37a8-4e69-8d8e-f47d8238d01a · outbound

This paper cites Deep Reinforcement Learning and the Deadly Triad.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Deep Reinforcement Learning and the Deadly Triad

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.617069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.617069Z digest=sha256:97f040969fbdbd7829041683b64feed118ccc2b63f47dfec5a5e4901c87b1865

Observation 0f50c6f5-0fe1-49df-bb9a-8cbcadce62f7 · outbound

This paper cites Amortizing in- tractable inference in diffusion models for vision, language, and control.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Amortizing in- tractable inference in diffusion models for vision, language, and control

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.798626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.623394Z digest=sha256:fd3cfb82988609da2ae682427db44e54938b7a35402a6d05bcbd7a82703e9652

Observation e7ded8a3-d280-458a-a3b6-ef8f8ee78c2b · outbound

This paper cites Practical and asymptotically exact conditional sampling in diffusion models.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Practical and asymptotically exact conditional sampling in diffusion models

Reference 68

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verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.760273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.628968Z digest=sha256:cb3419e46a4c9fd5f58a26ba745a81e0399a87b2593ce0651995780cbbebf8cb

Observation cc1fa72f-6c18-4fc9-937d-8c4b9c13aa01 · outbound

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

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.635309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.635309Z digest=sha256:133f13eb6e1757a298cd2d873c2f35d866518a5b2fb794b032b3d51a6c002ef7

Observation a94bfefe-5a7d-46e5-95de-80ff83783e7b · outbound

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

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Human preference score: Better aligning text-to-image models with human preference

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.729529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.640507Z digest=sha256:7da305778990236285ea47f712e17e39abe1e30e16771cfafa6e5ca97b6e7e0a

Observation b70928c2-1688-44fb-8bf6-9c196b72d033 · outbound

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

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.698523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.645961Z digest=sha256:585c985b296774954920c6979ab650a8382108bcda5cc28ba4b4f04d72857039

Observation 306b460c-c75e-422c-86d3-53c5d47a1fd7 · outbound

This paper cites Geodiff: A geometric diffusion model for molecular conformation generation.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Geodiff: A geometric diffusion model for molecular conformation generation

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.668235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.652579Z digest=sha256:c7a442215a094977347be18cda5bed9041f9969365d72f4d4c443e80efaa8a74

Observation d5f0f9ed-d324-43ad-a61c-88454b785bdf · outbound

This paper cites Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.661080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.661080Z digest=sha256:e31c7aec811794533e49f1ccd6c12e63a63405f69da3b31ef697a4352f1b007c

Observation 307b6616-6247-4eb6-9de3-d8ac1be3b9ea · outbound

This paper cites Robust scheduling with gflownets.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Robust scheduling with gflownets

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.643903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.668817Z digest=sha256:3d9834f21dd7434d74a71c5581239fe393d7dcba4f054a9d76d0ff86dd6b186e

Observation fca2d1d5-2904-4c80-a582-1981c148027a · outbound

This paper cites Unifying Generative Models with GFlowNets and Beyond.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Unifying Generative Models with GFlowNets and Beyond

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.674727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.674727Z digest=sha256:e0a8a743e1f79d5f79337dcbb75e9d380d45c584e00571f2cb0971cc81988432

Observation 52960b56-ab56-4590-ba76-41f8d1c57bc0 · outbound

This paper cites Generative flow networks for discrete probabilistic modeling.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Generative flow networks for discrete probabilistic modeling

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.619715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.681541Z digest=sha256:37dfddede0f98ace8f8c8019434ff366ea1b449cef84261700c1fddc9849081b

Observation 51d3a807-4764-468f-ae47-1baeacd56396 · outbound

This paper cites Let the flows tell: Solving graph combinatorial problems with gflownets.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Let the flows tell: Solving graph combinatorial problems with gflownets

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.589778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.687695Z digest=sha256:1c8a898d7343f4ef085f00d86531daf59ca31f4aae7ff4d389f870bd82e5db8b

Observation 8e55a842-3181-440d-9f95-bdd6d4f504ea · outbound

This paper cites an unresolved cited work.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Unresolved cited work

Reference 78

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:35:19.554400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.696320Z digest=sha256:7afcb0807983b37fe7b5382f482e11534a5f34a84cda99ae0ad8eadff8de4b79

Observation 932f3e2c-b708-4d54-a3e7-8bdd860df6b9 · outbound

This paper cites an unresolved cited work.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Unresolved cited work

Reference 79

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:35:19.525604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.703724Z digest=sha256:8367e0c7b45e695f6f2dee944dc21dd6703d6f4564598b870414156b562409dc

Observation 0d45cab9-75c9-44a6-be76-6f9e38ebc57a · outbound

This paper cites Susskind, Navdeep Jaitly, and Shuangfei Zhai.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Susskind, Navdeep Jaitly, and Shuangfei Zhai

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.500635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.722997Z digest=sha256:874b1c52c58f19bb6d7d9d5afab2ff0d7c796a38d65ce922fcabd30490770d8a

Observation a5c9b028-f3d3-4d36-a792-7387c9f3ef40 · outbound

This paper cites Clay: A controllable large-scale generative model for creating high- quality 3d assets.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Clay: A controllable large-scale generative model for creating high- quality 3d assets

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.470923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.730492Z digest=sha256:e2e14208da4e7a14e7b297ebdbb09bf8882670f2e5e58ad95c501c71ea02a2f9

Observation 7531604c-6e53-4fe4-91a8-6c22419b8c25 · outbound

This paper cites Probabilistic inference in language models via twisted sequential monte carlo.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Probabilistic inference in language models via twisted sequential monte carlo

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.445092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.736074Z digest=sha256:da70e1c3d8675ed349736768642d4fbffa6806887ac65dc44ae417e9a7724f0c

Observation 688d0892-0aa1-454a-99e8-99a7c59a3659 · outbound

This paper cites PhyloGFN: Phylogenetic inference with generative flow networks.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets PhyloGFN: Phylogenetic inference with generative flow networks

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.416685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.744808Z digest=sha256:0eb93a29ab414fb635fc98a42e7bb2a0119f66d8ce953da456119a5f9a7c01ce

Observation ca1faffe-7a93-477a-8ebd-24914cc7e90a · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Fine-Tuning Language Models from Human Preferences

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:18.752294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:18.752294Z digest=sha256:9fb966244e2778861b6e3bb03356527ff49489dbdcb1080ddc868b17ea126d39

Observation 06d4690a-5ab8-4380-b140-e2e688179c05 · outbound

This paper cites ˆxT = f (xt, t).

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets ˆxT = f (xt, t)

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.381747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.760505Z digest=sha256:cbd6260a6335b48e99ef33f446c437a6bbc9b1f92735183035f8cf9831ed87c6

Observation 41dffeeb-4fdc-44b4-a814-dec77585ebac · outbound

This paper cites xt+1 ∼ N(g(ˆxT , t+ 1), σt+1I) The MDP for diffusion models can therefore be simply constructed as: • State: (xt, t).

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets xt+1 ∼ N(g(ˆxT , t+ 1), σt+1I) The MDP for diffusion models can therefore be simply constructed as: • State: (xt, t)

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:35:19.338319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.771109Z digest=sha256:b31f9cd1d80f21e37e70c6cbca5e8a5821bd22f4494cb0e6b194fc0a80c57652

Observation a29b80b7-d457-41f7-b183-a12d3a7122c4 · outbound

This paper cites an unresolved cited work.

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Unresolved cited work

Reference 2024

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:35:20.612673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:35:18.442421Z digest=sha256:beab6d91b28453edc7f5e48da119186299a1c834036c10c60281afabc4bcdbe1

Pith citing papers

Observation d6bf38e5-01db-45ab-9ec1-15364db5d25e · inbound

TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology cites this paper.

TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-13T06:39:26.167502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T06:39:26.167502Z digest=sha256:0835f16bc50d5aae01feb8a040fe3241e5c11e4b13a1763f2af59d0453947499

Observation 7a1e273a-95ff-4dbd-bba2-475dca42fa30 · inbound

TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology cites this paper.

TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-02T08:00:03.272296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:00:03.272296Z digest=sha256:f63d6ce5bc8f07c2e343f8d73f9bb284f362aeedfd61c1bcc418f3ca1405b3a1