Paper Citation Record · LEDGER

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

As of 21 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 9 inbound Pith citation observations for arXiv:2505.14139.

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

pith.paper-citation-record.v1
2505.14139 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:42:51.385352Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:32:46.531563Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:07:27.693869Z

Reference resolution

24 of 24 outbound references displayed

verified exact3
verified fuzzy1
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f42ccfc9-013a-4bc6-bd91-727df8aa24da · outbound

This paper cites Figure 5: Normalized return of FlowQ for the D4RL adroit environments using 5 seeds.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Figure 5: Normalized return of FlowQ for the D4RL adroit environments using 5 seeds

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:42:53.191140Z

Source-reported events for the cited work

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

Observation 3eb51ae0-f6dd-43b4-8f03-d419b8f68cdf · outbound

This paper cites Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.306851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca30f5ef-759b-47ad-97b6-76f6c65d8374 · outbound

This paper cites Diffusion Actor-Critic: Formulating Constrained Policy Iteration as Diffusion Noise Regression for Offline Reinforcement Learning.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Diffusion Actor-Critic: Formulating Constrained Policy Iteration as Diffusion Noise Regression for Offline Reinforcement Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.396954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d918cf25-0e55-4308-86f0-0e6d2bc130c4 · outbound

This paper cites an unresolved cited work.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:42:53.391076Z

Source-reported events for the cited work

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

Observation 2bbb50df-d400-456e-8af2-26c74709b86c · outbound

This paper cites Denoising Diffusion Probabilistic Models.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Denoising Diffusion Probabilistic Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.782023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f9416a0-23a7-464b-9886-546706d16168 · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Offline Reinforcement Learning with Implicit Q-Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.185601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4f97b07-d29c-440e-9072-8bd97f6c68f0 · outbound

This paper cites an unresolved cited work.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:42:53.607030Z

Source-reported events for the cited work

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

Observation 5ab699ca-464f-46fe-a9f0-25cc41be7228 · outbound

This paper cites Flow Matching for Generative Modeling.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Flow Matching for Generative Modeling

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.314458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccf2fe4e-d7b2-4ccc-9501-c01f458b10c6 · outbound

This paper cites Mish: A Self Regularized Non-Monotonic Activation Function.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Mish: A Self Regularized Non-Monotonic Activation Function

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.478554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6a33093-fd25-4670-ac65-277f2c2119fc · outbound

This paper cites Offline Reinforcement Learning from Images with Latent Space Models.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Offline Reinforcement Learning from Images with Latent Space Models

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:42:52.081987Z

Source-reported events for the cited work

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

Observation a72f762f-edd0-4573-b06c-85b28c7a4840 · outbound

This paper cites Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.747484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17afe07b-bccf-4af8-a79f-d6f9e52682bd · outbound

This paper cites Critic Regularized Regression.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Critic Regularized Regression

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.880303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 502d693a-a891-43e7-bbff-f76c055b7b81 · outbound

This paper cites MOPO: Model-based Offline Policy Optimization.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning MOPO: Model-based Offline Policy Optimization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.991836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d271efa-623e-408e-b0e4-e9b8cec62007 · outbound

This paper cites Guided Flows for Generative Modeling and Decision Making.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Guided Flows for Generative Modeling and Decision Making

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:51.079534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af01259c-5016-4578-a3d6-c356b6d41965 · outbound

This paper cites PLAS: Latent Action Space for Offline Reinforcement Learning.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning PLAS: Latent Action Space for Offline Reinforcement Learning

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:42:51.700274Z

Source-reported events for the cited work

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

Observation 59abff0a-f10e-4b17-94a5-2c47107fb8ce · outbound

This paper cites Gaussian Error Linear Units (GELUs).

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Gaussian Error Linear Units (GELUs)

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.723240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b69c49b-924d-46e2-ab2e-3f2b5d10b17d · outbound

This paper cites Adam: A Method for Stochastic Optimization.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Adam: A Method for Stochastic Optimization

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.038962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 832ce9c9-889f-4ad2-9cb1-0298b845ddf0 · outbound

This paper cites Off-Policy Deep Reinforcement Learning without Exploration.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Off-Policy Deep Reinforcement Learning without Exploration

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.667242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ad074b3-a6f5-4c12-80f5-3bfab2aa636f · outbound

This paper cites D4RL: Datasets for Deep Data-Driven Reinforcement Learning.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.466319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d26abf5-f678-4528-b515-ff9311f8250f · outbound

This paper cites A Minimalist Approach to Offline Reinforcement Learning.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning A Minimalist Approach to Offline Reinforcement Learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.563459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54ffd1f8-04c3-4452-b03d-54da3fb97846 · outbound

This paper cites DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.432520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f03702ea-474c-4204-8a39-dadc3920baeb · outbound

This paper cites Efficient Diffusion Policies for Offline Reinforcement Learning.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Efficient Diffusion Policies for Offline Reinforcement Learning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.907562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95aabe8e-02c7-4362-98ad-c9865fc5b5cd · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:49.234834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 438fe611-de93-454e-8dc2-8f5980d3e5ae · outbound

This paper cites an unresolved cited work.

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning Unresolved cited work

Reference 2025

Resolution: verified exact; raw_fallback, observed 2026-08-07T15:42:52.965404Z

Source-reported events for the cited work

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

Pith citing papers

Observation e874a85f-4a32-4f77-a3f8-c478d703a54b · inbound

Action Emergence from Streaming Intent cites this paper.

Action Emergence from Streaming Intent FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:02:59.187795Z

Source-reported events for the cited work

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

Observation fe907729-1795-43fd-91f1-a78dfba98a68 · inbound

Action Emergence from Streaming Intent cites this paper.

Action Emergence from Streaming Intent FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.985480Z

Source-reported events for the cited work

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

Observation 62d7a1be-0619-455e-9ff5-92a6f45ac329 · inbound

Driving Intents Amplify Planning-Oriented Reinforcement Learning cites this paper.

Driving Intents Amplify Planning-Oriented Reinforcement Learning FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T20:52:58.729137Z

Source-reported events for the cited work

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

Observation 98741778-00e8-48ec-8acf-970f908a4d18 · inbound

Driving Intents Amplify Planning-Oriented Reinforcement Learning cites this paper.

Driving Intents Amplify Planning-Oriented Reinforcement Learning FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T04:59:45.526358Z

Source-reported events for the cited work

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

Observation fd7edf9d-bae1-44d5-bba4-deb47f1c9f52 · inbound

Reinforcement Learning for Flow-Matching Policies with Density Transport cites this paper.

Reinforcement Learning for Flow-Matching Policies with Density Transport FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T22:27:25.812719Z

Source-reported events for the cited work

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

Observation 96d8a000-fbb2-4097-9f99-a61a5978c4eb · inbound

Counterfactual Transport Flows for Offline Conservative Trajectory Refinement cites this paper.

Counterfactual Transport Flows for Offline Conservative Trajectory Refinement FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:07:27.695520Z

Source-reported events for the cited work

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

Observation 01131813-7290-4a4f-9c57-d9c6c107e908 · inbound

ConFlow: Constraints-Guided Learning with Flow Matching for Motion Generation cites this paper.

ConFlow: Constraints-Guided Learning with Flow Matching for Motion Generation FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T02:10:24.308093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a705d2d-e3e4-42e3-aacb-279a33792de1 · inbound

Collaborative Weighting with Pessimistic Critic for Mitigating Overestimation in Off-Policy Reinforcement Learning cites this paper.

Collaborative Weighting with Pessimistic Critic for Mitigating Overestimation in Off-Policy Reinforcement Learning FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T14:19:59.991253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60624e1d-49e3-480b-8fb9-cd732ec8b0e6 · inbound

ReBRAC-v2: The Return of the King cites this paper.

ReBRAC-v2: The Return of the King FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-06T00:32:46.531563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.