Pith. sign in

Paper Citation Record · LEDGER

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models

As of 6 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2605.26013.

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

pith.paper-citation-record.v1
2605.26013 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T22:44:25.152451Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

  • verified exact13
  • verified fuzzy0
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a36f42a4-0278-4470-847c-ab4a5a28a551 · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-06-29T22:54:01.614664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:b494c027e0fe634d1fb6bb2b6ae6ad88efa4b50450cf8ffbea19213c1468a13a

Observation d83a728d-623f-4bc2-b1ee-0baaaeea8ce5 · outbound

This paper cites Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.620053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:fc0cf179564d87d0eacc90942dcae6d4d1ad312990a0b15a2632bbf492187873

Observation 195e1f9d-4ada-425c-bf82-1066156f70db · outbound

This paper cites Fine-tuning flow matching generative models with intermediate feedback.arXiv preprint arXiv:2510.18072, 2025a.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Fine-tuning flow matching generative models with intermediate feedback.arXiv preprint arXiv:2510.18072, 2025a

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.612457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:9528eea994c81fe347c46dbbbeed4a9b055decf3e6633cba4f3096c032543f80

Observation 4a557aa6-a763-4854-a3a6-bfba55cb2f24 · outbound

This paper cites TempFlow-GRPO: When Timing Matters for GRPO in Flow Models.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models TempFlow-GRPO: When Timing Matters for GRPO in Flow Models

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-06-29T22:54:01.617374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:8df99bfab91306a77047611136b24e03613c822dd59d7adac091b9f40cd781dd

Observation ba1d0972-f01e-4102-a6de-ae0d8986d4d9 · outbound

This paper cites CLIPScore: A reference-free evaluation metric for image captioning.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models CLIPScore: A reference-free evaluation metric for image captioning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-06-29T22:44:25.152451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:dbcbd6f8437157a2fe3866a09aee07399e2a372b223b22fb1246c6c31e3f9c8b

Observation 4e86341b-76a5-4802-990f-6c6a485c0651 · outbound

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

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Aligning Text-to-Image Models using Human Feedback

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-06-29T22:54:01.622449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:b28b38591ed9d06a42b2c5d85d011a10355c87632b779212582c560bcd0c0a74

Observation b4459e72-fced-4a42-a3fc-3296ee2c0b17 · outbound

This paper cites MixGRPO: Unlocking Flow-based GRPO Efficiency with Mixed ODE-SDE.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models MixGRPO: Unlocking Flow-based GRPO Efficiency with Mixed ODE-SDE

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-06-29T22:54:01.609833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:96c9ae066ac2a119e0f46df172c973799479e7d246db099f9ab5461b8701c0d0

Observation e0616927-8ee7-4111-930b-8bc43d153589 · outbound

This paper cites Flow-GRPO: Training Flow Matching Models via Online RL.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Flow-GRPO: Training Flow Matching Models via Online RL

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-06-29T22:54:01.606928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:5a08c35e59ace70a190b8f902dd6a7a09afae1ced65dd9eebff7feedb1110314

Observation a64017b0-2a58-48de-a8bd-7b78e7f43515 · outbound

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

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Aligning Text-to-Image Diffusion Models with Reward Backpropagation

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.604475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:22bdb54e9921646e343ebcbd5da81bb15d03e880b79bd3307b699b7338ea23d8

Observation 87fe6953-3c25-45ca-8ef7-e64179792c6c · outbound

This paper cites Stepwise credit assignment for grpo on flow- matching models.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Stepwise credit assignment for grpo on flow- matching models

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.596226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:d1bfd7381fca29e6ce9ab93931378642b2107d2095a44daa8f879241ac9a4e76

Observation fc3c30c5-b2e3-432d-b3f0-c48a7cb8423f · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-06-29T22:54:01.590277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:a3a42263ecc29359d0f37bb082c09114475f4b83280b4e0c7ffc6998ae2c9b50

Observation d81c8b19-71a5-4086-bdf2-8c03a87b9b62 · outbound

This paper cites Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.593464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:f89ae138bf76d00085115f3bdb4138da24a171ac6c505b2d6a6448054e7d49c4

Observation a9e414b3-e654-4d3e-b1e9-b5345b9c9b03 · outbound

This paper cites Advantage weighted matching: Aligning rl with pretraining in diffusion models.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Advantage weighted matching: Aligning rl with pretraining in diffusion models

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.599110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:a58dfd84609ae68d8a7bc18d4bb6e115b54184f4540b04ebe398ddab79a3fe28

Observation 6d82f758-7150-47f3-ae3b-571ab367f929 · outbound

This paper cites DiffusionNFT: Online Diffusion Reinforcement with Forward Process.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models DiffusionNFT: Online Diffusion Reinforcement with Forward Process

Reference 14

Resolution
metadata mismatch
local_arxiv, observed 2026-06-29T22:54:01.601778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:27d5cd0d55429c0302859de5eab718b3afb364808afd20cfb338e3c923901dc1

Observation b4a22a5f-00fb-4fb4-abeb-d4e5a4d4eb25 · outbound

This paper cites Diffusion reinforcement learning via centered reward distillation.arXiv preprint arXiv:2603.14128, 2026.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models Diffusion reinforcement learning via centered reward distillation.arXiv preprint arXiv:2603.14128, 2026

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.587929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:a28b8c23f32a0c879d5afef54a5ea5d742b09150169150f4a3c9778cd9200d69

Observation 05ed8acd-41ef-4f20-8785-dd71f6052a47 · outbound

This paper cites We report the combined reward, as well as HPSv2.1 and CLIPScore.

AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models We report the combined reward, as well as HPSv2.1 and CLIPScore

Reference 16

Resolution
unresolved
no resolver link, observed 2026-06-29T22:44:25.152451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-29T22:44:25.152451Z digest=sha256:c3f57150749ec4f3d8ea493b4dc0a059b6287c44e020cd7dc1eb614cf6377fb3

Pith citing papers

No inbound Pith citation observations are available.