Paper Citation Record · LEDGER

How to Train Your Energy-Based Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 50 inbound Pith citation observations for arXiv:2101.03288.

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pith.paper-citation-record.v1
2101.03288 v2

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measured 50 of 50 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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81
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Pith citing papers

Observation 3e876788-eaf1-4a14-94f2-fe03a3b09efa · inbound

SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations cites this paper.

SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations How to Train Your Energy-Based Models

Reference 12

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Observation b417fc76-0d88-4c54-ba73-3d47ab4d7f49 · inbound

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

Stochastic Interpolants: A Unifying Framework for Flows and Diffusions How to Train Your Energy-Based Models

Reference 11

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Observation 706d6b86-33c5-43fc-91be-8dcf9bd58642 · inbound

The Score-Difference Flow for Implicit Generative Modeling cites this paper.

The Score-Difference Flow for Implicit Generative Modeling How to Train Your Energy-Based Models

Reference 12

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Observation fdc8a931-4580-4b3f-954a-bbd70659ff33 · inbound

Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model cites this paper.

Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model How to Train Your Energy-Based Models

Reference 41

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Observation 37e8dd6c-65df-42c4-acd3-8f0132001af9 · inbound

Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation cites this paper.

Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation How to Train Your Energy-Based Models

Reference 51

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Observation 914299c6-c907-4963-99bc-4542f8eaa6a5 · inbound

Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation cites this paper.

Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation How to Train Your Energy-Based Models

Reference 2020

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Observation 56ef37b0-abb6-4256-b698-c14aafb16c1b · inbound

Joint Learning of Energy-based Models and their Partition Function cites this paper.

Joint Learning of Energy-based Models and their Partition Function How to Train Your Energy-Based Models

Reference 41

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Observation aa3c3aa5-314f-495d-86f7-bc5ef99a42b0 · inbound

Efficient Online Reinforcement Learning for Diffusion Policy cites this paper.

Efficient Online Reinforcement Learning for Diffusion Policy How to Train Your Energy-Based Models

Reference 41

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Observation 561b6391-920c-402c-91dc-7359ac5533d9 · inbound

Deep Neural Cellular Potts Models cites this paper.

Deep Neural Cellular Potts Models How to Train Your Energy-Based Models

Reference 1997

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Field Matching: an Electrostatic Paradigm to Generate and Transfer Data cites this paper.

Field Matching: an Electrostatic Paradigm to Generate and Transfer Data How to Train Your Energy-Based Models

Reference 3

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Observation 763bf06d-7772-41e8-a45b-ef8956072daf · inbound

Complexity Analysis of Normalizing Constant Estimation: from Jarzynski Equality to Annealed Importance Sampling and beyond cites this paper.

Complexity Analysis of Normalizing Constant Estimation: from Jarzynski Equality to Annealed Importance Sampling and beyond How to Train Your Energy-Based Models

Reference 91

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Observation c1112610-36d7-4848-9694-c19430886e79 · inbound

From Action Labels to Sets: Rethinking Action Supervision for Imitation Learning from Corrective Feedback cites this paper.

From Action Labels to Sets: Rethinking Action Supervision for Imitation Learning from Corrective Feedback How to Train Your Energy-Based Models

Reference 17

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Observation e5b3a66e-b2da-4a80-aca5-83e3a841fbbe · inbound

Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold cites this paper.

Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold How to Train Your Energy-Based Models

Reference 45

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Flow Along the K-Amplitude for Generative Modeling cites this paper.

Flow Along the K-Amplitude for Generative Modeling How to Train Your Energy-Based Models

Reference 6

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Observation c1bad49d-549f-4511-8b39-2a6ee2a8bba3 · inbound

Future-Oriented Navigation: Dynamic Obstacle Avoidance with One-Shot Energy-Based Multimodal Motion Prediction cites this paper.

Future-Oriented Navigation: Dynamic Obstacle Avoidance with One-Shot Energy-Based Multimodal Motion Prediction How to Train Your Energy-Based Models

Reference 28

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Observation 7ab00468-f793-4cef-bcf3-a98f31f822b6 · inbound

Incorporating Inductive Biases to Energy-based Generative Models cites this paper.

Incorporating Inductive Biases to Energy-based Generative Models How to Train Your Energy-Based Models

Reference 2019

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Observation 2d127f2e-a9ec-43ec-afda-2c4faa0a6198 · inbound

Heterosynaptic Circuits Are Universal Gradient Machines cites this paper.

Heterosynaptic Circuits Are Universal Gradient Machines How to Train Your Energy-Based Models

Reference 41

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Observation e3ca6f2e-a1c7-43e1-b5c5-a2d0ad775eb5 · inbound

Score-Based Training for Energy-Based TTS Models cites this paper.

Score-Based Training for Energy-Based TTS Models How to Train Your Energy-Based Models

Reference 19

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Observation cb7d4042-b237-4ba4-bf94-d370b640dba1 · inbound

An Affective-Taxis Hypothesis for Alignment and Interpretability cites this paper.

An Affective-Taxis Hypothesis for Alignment and Interpretability How to Train Your Energy-Based Models

Reference 72

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Observation 115f3f96-c5a5-4fa8-a011-4c76a345b5b9 · inbound

Contrastive Residual Energy Test-time Adaptation cites this paper.

Contrastive Residual Energy Test-time Adaptation How to Train Your Energy-Based Models

Reference 8

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Navigating the Latent Space Dynamics of Neural Models cites this paper.

Navigating the Latent Space Dynamics of Neural Models How to Train Your Energy-Based Models

Reference 54

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Jarzynski Reweighting and Sampling Dynamics for Training Energy-Based Models: Theoretical Analysis of Different Transition Kernels cites this paper.

Jarzynski Reweighting and Sampling Dynamics for Training Energy-Based Models: Theoretical Analysis of Different Transition Kernels How to Train Your Energy-Based Models

Reference 12

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Observation 2058c489-10d9-412d-a8e5-ea1f615ac0f9 · inbound

Time-dependent density estimation using binary classifiers cites this paper.

Time-dependent density estimation using binary classifiers How to Train Your Energy-Based Models

Reference 56

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Observation 523e888c-bbfb-45a4-a82f-b31f2d9487f1 · inbound

ToxBench: A Binding Affinity Prediction Benchmark with AB-FEP-Calculated Labels for Human Estrogen Receptor Alpha cites this paper.

ToxBench: A Binding Affinity Prediction Benchmark with AB-FEP-Calculated Labels for Human Estrogen Receptor Alpha How to Train Your Energy-Based Models

Reference 63

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Estimating Rate-Distortion Functions Using the Energy-Based Model cites this paper.

Estimating Rate-Distortion Functions Using the Energy-Based Model How to Train Your Energy-Based Models

Reference 19

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Transferable Direct Prompt Injection via Activation-Guided MCMC Sampling cites this paper.

Transferable Direct Prompt Injection via Activation-Guided MCMC Sampling How to Train Your Energy-Based Models

Reference 28

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Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics cites this paper.

Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics How to Train Your Energy-Based Models

Reference 45

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Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications cites this paper.

Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications How to Train Your Energy-Based Models

Reference 32

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Observation e168c9f0-d2e1-439e-992e-345fab2ed5bd · inbound

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction cites this paper.

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction How to Train Your Energy-Based Models

Reference 39

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Observation 50a9886e-8df5-4aaa-8a56-4d799a4d7e3f · inbound

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction cites this paper.

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction How to Train Your Energy-Based Models

Reference 39

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Diffusion-based Annealed Boltzmann Generators : benefits, pitfalls and hopes cites this paper.

Diffusion-based Annealed Boltzmann Generators : benefits, pitfalls and hopes How to Train Your Energy-Based Models

Reference 33

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Stochastic Attention via Langevin Dynamics on the Modern Hopfield Energy cites this paper.

Stochastic Attention via Langevin Dynamics on the Modern Hopfield Energy How to Train Your Energy-Based Models

Reference 10

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Observation 0c8ebc9f-1eb0-403e-93a5-7974d0f16355 · inbound

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis cites this paper.

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis How to Train Your Energy-Based Models

Reference 7

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Observation c487ff27-7ad6-4eee-a66d-cde13470d338 · inbound

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis cites this paper.

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis How to Train Your Energy-Based Models

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T10:51:25.872360Z

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Observation bda39447-b9b3-456f-94e3-f35bfe4ef30e · inbound

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis cites this paper.

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis How to Train Your Energy-Based Models

Reference 7

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Observation 123e233c-5328-46b9-b0cf-7ca1ecabbfeb · inbound

Energy Generative Modeling: A Lyapunov-based Energy Matching Perspective cites this paper.

Energy Generative Modeling: A Lyapunov-based Energy Matching Perspective How to Train Your Energy-Based Models

Reference 31

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Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning cites this paper.

Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning How to Train Your Energy-Based Models

Reference 9

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Observation fbf82489-1de2-4782-bed8-859b803c79a6 · inbound

Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation cites this paper.

Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation How to Train Your Energy-Based Models

Reference 75

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Discovering interpretable low-dimensional dynamics using maximum entropy cites this paper.

Discovering interpretable low-dimensional dynamics using maximum entropy How to Train Your Energy-Based Models

Reference 79

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ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs cites this paper.

ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs How to Train Your Energy-Based Models

Reference 32

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Observation 5bf03812-6894-43f3-9f15-f2015531a33e · inbound

Text Dictates, Music Decorates: Energy-based Attention for Editable Dance Motion Generation cites this paper.

Text Dictates, Music Decorates: Energy-based Attention for Editable Dance Motion Generation How to Train Your Energy-Based Models

Reference 59

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Text Dictates, Music Decorates: Energy-based Attention for Editable Dance Motion Generation cites this paper.

Text Dictates, Music Decorates: Energy-based Attention for Editable Dance Motion Generation How to Train Your Energy-Based Models

Reference 59

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Observation b8e728f5-59d5-43b1-97cd-5d6103ca14f8 · inbound

Error bounds for simultaneous Wasserstein contractive adaptive increasingly rare MCMC cites this paper.

Error bounds for simultaneous Wasserstein contractive adaptive increasingly rare MCMC How to Train Your Energy-Based Models

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T15:15:47.763279Z

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Revisiting the Volume Hypothesis cites this paper.

Revisiting the Volume Hypothesis How to Train Your Energy-Based Models

Reference 183

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Observation d4b2c698-ee2c-4f55-ba92-82612bb84e43 · inbound

Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space cites this paper.

Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space How to Train Your Energy-Based Models

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:58:46.830662Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 63d5f1fb-7ff1-4e1d-87a8-e11bd1065c34 · inbound

Projected Energy Matching for Generative 3D Priors cites this paper.

Projected Energy Matching for Generative 3D Priors How to Train Your Energy-Based Models

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T19:47:32.491309Z

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Observation 835319d8-d4a0-44b7-806a-60b05c5af4b5 · inbound

Bayesian Experimental Design via Score Matching cites this paper.

Bayesian Experimental Design via Score Matching How to Train Your Energy-Based Models

Reference 166

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T09:16:59.340343Z

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Observation cd7033e1-d4b7-4d83-a086-66767b9bd9b0 · inbound

A Blueprint for Equilibrium-Based Differentiable Continuous-Variable Thermodynamic Computing cites this paper.

A Blueprint for Equilibrium-Based Differentiable Continuous-Variable Thermodynamic Computing How to Train Your Energy-Based Models

Reference 20

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Observation 13dc7f3e-adc2-425c-8c7d-910aedff62c4 · inbound

Joint Flow Matching for Generator-Consistent Classification cites this paper.

Joint Flow Matching for Generator-Consistent Classification How to Train Your Energy-Based Models

Reference 41

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Observation a56ec84a-0440-4e95-8179-50d2bc1abf33 · inbound

Particle-based Generalised Stochastic Optimisation cites this paper.

Particle-based Generalised Stochastic Optimisation How to Train Your Energy-Based Models

Reference 407

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