Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:24:58.264367Z
Paper Citation Record · LEDGER
Unifying Generative Models with Path Integrals
As of 20 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2608.12438.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
32 of 32 outbound references displayed
- verified exact1
- verified fuzzy7
- unresolved24
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f9583d2f-5c75-4937-92fd-6d879ad13dee · outbound
This paper cites Machine Learning and LHC Event Generation.
Unifying Generative Models with Path Integrals Machine Learning and LHC Event Generation
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.123917Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 65aefa24-1551-4e55-81a4-f27d5c3d3781 · outbound
This paper cites Symmetries of generating functionals of Langevin processes with colored multiplicative noise.
Unifying Generative Models with Path Integrals Symmetries of generating functionals of Langevin processes with colored multiplicative noise
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.184092Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 330dc932-8f8d-4058-bf59-c1a871c2222a · outbound
This paper cites Generative Adversarial Networks.
Unifying Generative Models with Path Integrals Generative Adversarial Networks
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.210474Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 07adfff5-2432-493b-a9d5-eeee8c808f43 · outbound
This paper cites Stabilizing Training of Generative Adversarial Networks through Regularization.
Unifying Generative Models with Path Integrals Stabilizing Training of Generative Adversarial Networks through Regularization
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.220030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 79c5dd2f-a1e1-42ea-ac8c-7311ad32c734 · outbound
This paper cites Spectral Normalization for Generative Adversarial Networks.
Unifying Generative Models with Path Integrals Spectral Normalization for Generative Adversarial Networks
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.230042Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 74646452-1bc9-4e33-a36f-a9b2431b9466 · outbound
This paper cites Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models.
Unifying Generative Models with Path Integrals Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.239796Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a17ae5ed-d21a-4201-a086-1ffc52b53037 · outbound
This paper cites Weinberg,Phenomenological Lagrangians, Physica A96(1979) 1-2,.
Unifying Generative Models with Path Integrals Weinberg,Phenomenological Lagrangians, Physica A96(1979) 1-2,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:24:58.594922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d62a4b80-1095-4323-ab14-c0323813228c · outbound
This paper cites An Effective Field Theory of Gravity for Extended Objects.
Unifying Generative Models with Path Integrals An Effective Field Theory of Gravity for Extended Objects
Reference 288
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.264367Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fe0a88d-560d-4c59-a013-7b7d93bc1ba4 · outbound
This paper cites an unresolved cited work.
Unifying Generative Models with Path Integrals Unresolved cited work
Reference 313
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:24:58.678197Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 28da0806-5b2e-4d5d-9e70-c4f50ff8466f · outbound
This paper cites Weinberg,Nuclear forces from chiral Lagrangians, Phys.
Unifying Generative Models with Path Integrals Weinberg,Nuclear forces from chiral Lagrangians, Phys
Reference 327
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:24:58.580498Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation dfd00d31-fa11-4e52-a2dc-5036625c99c8 · outbound
This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.
Unifying Generative Models with Path Integrals Score-Based Generative Modeling through Stochastic Differential Equations
Reference 377
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.146306Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83eb7d0a-3f65-42cf-ad73-d354f79de145 · outbound
This paper cites Hubbard,Calculation of partition functions, Phys.
Unifying Generative Models with Path Integrals Hubbard,Calculation of partition functions, Phys
Reference 416
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:24:58.608720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7bc37107-12ff-4cd1-bdc0-0418de3413cf · outbound
This paper cites [11]H.-K.
Reference 423
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.140829Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f42b6ef9-bf25-406d-8c89-6ba0dc8cbbef · outbound
This paper cites Maruyama,Continuous markov processes and stochastic equations, Rendiconti del Circolo Matematico di Palermo4(1955).
Unifying Generative Models with Path Integrals Maruyama,Continuous markov processes and stochastic equations, Rendiconti del Circolo Matematico di Palermo4(1955)
Reference 1188
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:24:58.664561Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a9af921a-26f0-4ead-9b42-ef4a80df90d5 · outbound
This paper cites Machlup and L.
Unifying Generative Models with Path Integrals Machlup and L
Reference 1505
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:24:58.718868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9a3359b4-3e49-41cf-890a-64c9a4d8c4e0 · outbound
This paper cites A Guide to Constraining Effective Field Theories with Machine Learning.
Unifying Generative Models with Path Integrals A Guide to Constraining Effective Field Theories with Machine Learning
Reference 1661
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.191440Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 78581eaa-2d17-4211-9f87-03512077556f · outbound
This paper cites Zinn-Justin,Quantum field theory and critical phenomena, Int.
Unifying Generative Models with Path Integrals Zinn-Justin,Quantum field theory and critical phenomena, Int
Reference 1965
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:24:58.636698Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 318bdc09-75fd-4e61-b77e-574a4e059030 · outbound
This paper cites A survey of the Schr\"odinger problem and some of its connections with optimal transport.
Unifying Generative Models with Path Integrals A survey of the Schr\"odinger problem and some of its connections with optimal transport
Reference 1984
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.205393Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6dc7acb-0348-4223-bd5e-25d8551b0eae · outbound
This paper cites an unresolved cited work.
Unifying Generative Models with Path Integrals Unresolved cited work
Reference 1989
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:24:58.691592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation aaa3784d-642c-464c-96d0-6dfea1db0a96 · outbound
This paper cites an unresolved cited work.
Unifying Generative Models with Path Integrals Unresolved cited work
Reference 1992
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:24:58.650916Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 80056a02-0c4a-418b-ba88-53f8cb361853 · outbound
This paper cites an unresolved cited work.
Unifying Generative Models with Path Integrals Unresolved cited work
Reference 2006
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T00:24:58.705323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ee0ef04e-0183-4b6d-80dd-e30ba0b8c0ca · outbound
This paper cites Vincent,A connection between score matching and denoising autoencoders, Neural Computation23(2011) 7,.
Unifying Generative Models with Path Integrals Vincent,A connection between score matching and denoising autoencoders, Neural Computation23(2011) 7,
Reference 2009
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T00:24:58.622467Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 84e931a6-4326-4fd3-bd4d-f1dedcb553fb · outbound
This paper cites Auto-Encoding Variational Bayes.
Unifying Generative Models with Path Integrals Auto-Encoding Variational Bayes
Reference 2014
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.161934Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ebf1ca19-5bd8-42c8-8732-5f462c0c96e9 · outbound
This paper cites Towards Principled Methods for Training Generative Adversarial Networks.
Unifying Generative Models with Path Integrals Towards Principled Methods for Training Generative Adversarial Networks
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.215180Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7bf1665-78bd-4e92-9b61-0961e24976fd · outbound
This paper cites Which Training Methods for GANs do actually Converge?.
Unifying Generative Models with Path Integrals Which Training Methods for GANs do actually Converge?
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.225123Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9538ec6-78b9-4fda-935a-0dc2a689957c · outbound
This paper cites SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows.
Unifying Generative Models with Path Integrals SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.151608Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0522edc0-25af-4ffd-b334-9fdbc447d982 · outbound
This paper cites Maximum Likelihood Training of Score-Based Diffusion Models.
Unifying Generative Models with Path Integrals Maximum Likelihood Training of Score-Based Diffusion Models
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.195822Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e4892bb5-6b54-4613-9385-675efd7b5077 · outbound
This paper cites Elucidating the Design Space of Diffusion-Based Generative Models.
Unifying Generative Models with Path Integrals Elucidating the Design Space of Diffusion-Based Generative Models
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.244977Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 80fe97e9-77a4-492a-bf16-8ee90abea708 · outbound
This paper cites Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation.
Unifying Generative Models with Path Integrals Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.200497Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d8b6a54e-9001-4822-8fd9-141eedbd7721 · outbound
This paper cites AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models.
Unifying Generative Models with Path Integrals AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.249835Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6dadd1db-97f3-48a4-b27e-3b817830f7a7 · outbound
This paper cites Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control.
Unifying Generative Models with Path Integrals Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:24:58.253593Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 641fbd72-42b2-4488-b7ce-20f4a134b8a9 · outbound
This paper cites The Living Guide of Machine Learning for Particle Physics.
Unifying Generative Models with Path Integrals The Living Guide of Machine Learning for Particle Physics
Reference 2026
- Resolution
- verified exact
- local_arxiv, observed 2026-08-16T00:24:58.551390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.