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Advances in Neural Information Processing Systems , volume=

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it

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2026 3 2023 1

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representative citing papers

Long-Text-to-Image Generation via Compositional Prompt Decomposition

cs.CV · 2026-04-20 · unverdicted · novelty 7.0

PRISM lets pre-trained text-to-image models handle long prompts by breaking them into compositional parts, predicting noise separately, and merging outputs via energy-based conjunction, matching fine-tuned models while generalizing better to prompts over 500 tokens.

Learning Interactive Real-World Simulators

cs.AI · 2023-10-09 · conditional · novelty 7.0

UniSim learns a universal real-world simulator from orchestrated diverse datasets, enabling zero-shot deployment of policies trained purely in simulation.

Energy Generative Modeling: A Lyapunov-based Energy Matching Perspective

cs.LG · 2026-05-07 · unverdicted · novelty 6.0

Training and sampling in static scalar energy generative models are two instances of the same Lyapunov-driven density transport dynamics on Wasserstein space, differing only by initial condition, which yields a finite stopping criterion for Langevin sampling and additive composition rules that keep

citing papers explorer

Showing 4 of 4 citing papers.

  • Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model cs.LG · 2026-05-20 · unverdicted · none · ref 35

    Extends equilibrium propagation to skew-gradient Fitzhugh-Nagumo systems and derives an explicit layer-wise Hamiltonian recurrence for inference in deep residual topologies.

  • Long-Text-to-Image Generation via Compositional Prompt Decomposition cs.CV · 2026-04-20 · unverdicted · none · ref 16

    PRISM lets pre-trained text-to-image models handle long prompts by breaking them into compositional parts, predicting noise separately, and merging outputs via energy-based conjunction, matching fine-tuned models while generalizing better to prompts over 500 tokens.

  • Learning Interactive Real-World Simulators cs.AI · 2023-10-09 · conditional · none · ref 192

    UniSim learns a universal real-world simulator from orchestrated diverse datasets, enabling zero-shot deployment of policies trained purely in simulation.

  • Energy Generative Modeling: A Lyapunov-based Energy Matching Perspective cs.LG · 2026-05-07 · unverdicted · none · ref 17

    Training and sampling in static scalar energy generative models are two instances of the same Lyapunov-driven density transport dynamics on Wasserstein space, differing only by initial condition, which yields a finite stopping criterion for Langevin sampling and additive composition rules that keep