Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets | Paper Citation Record

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

Reference 6

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

Reference 10

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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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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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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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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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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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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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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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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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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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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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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

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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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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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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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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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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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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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This paper cites Laion aesthetic score predictor.

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

Reference 28

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

Reference 29

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

Reference 31

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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

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

Reference 33

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

Reference 34

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

Reference 35

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

Reference 36

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

Reference 37

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

Reference 38

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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

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

Reference 40

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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

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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

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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

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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

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

Reference 45

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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

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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

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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

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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

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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

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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

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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

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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 2026-08-15T06:32:42.880941+00:00.

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

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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

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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

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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

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

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

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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

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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

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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

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

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

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

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

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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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

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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

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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

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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

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

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

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

Source-reported events for the cited work

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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

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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

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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

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

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 2026-08-15T06:32:42.880941+00:00.

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

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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

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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

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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

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

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 2026-08-15T06:32:42.880941+00:00.

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

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

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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

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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 2026-08-15T06:32:42.880941+00:00.

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

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

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

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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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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Reference resolution

Outbound references

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