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Paper Citation Record · LEDGER

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts

As of 7 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2508.20991.

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

pith.paper-citation-record.v1
2508.20991 v1

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measured 57 of 57 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

57 of 57 outbound references displayed

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External citation measurements

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Outbound references

Observation 07801ec9-7838-4f34-aa4a-dedb65854314 · outbound

This paper cites The ALICE Zero Degree Calorimeters.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts The ALICE Zero Degree Calorimeters

Reference 1

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Observation 6f866b7a-a838-4dd9-9ef3-8143b533888b · outbound

This paper cites PonderNet: Learning to Pon- der.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts PonderNet: Learning to Pon- der

Reference 2

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Observation 9ec704fb-e174-40b5-a9fc-5f0be8c91b06 · outbound

This paper cites Deep Generative Models for Proton Zero Degree Calorimeter Simulations in ALICE, CERN.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Deep Generative Models for Proton Zero Degree Calorimeter Simulations in ALICE, CERN

Reference 3

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Observation ba3a03e1-1f0c-49f6-ae1b-23a11023b3cb · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 4

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Observation f8e22c74-d045-46ff-a2e7-f82efa1cda38 · outbound

This paper cites Worldwide LHC Computing Grid Resources Report.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Worldwide LHC Computing Grid Resources Report

Reference 5

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Observation 57fe2ce6-b2e4-4f76-8230-79acc33073d7 · outbound

This paper cites Mod-Squad: Designing Mixtures of Experts As Mod- ular Multi-Task Learners.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Mod-Squad: Designing Mixtures of Experts As Mod- ular Multi-Task Learners

Reference 6

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Observation 925d74d3-b9ff-4277-be2a-f8832fd9dd26 · outbound

This paper cites Unified scaling laws for routed language models.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Unified scaling laws for routed language models

Reference 7

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Observation 662f8501-209d-43ca-b85c-d6e2313cae36 · outbound

This paper cites CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds

Reference 8

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Observation 764c4fcd-3d5f-4b9d-8696-6475b52b4d2e · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 9

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Observation cfb9872f-6a34-4cad-a63a-93f4eae25e72 · outbound

This paper cites Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts

Reference 10

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Observation bc6e1fb4-5a11-4ff0-b5e0-a2bafb0ad4e8 · outbound

This paper cites Universal Transformers.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Universal Transformers

Reference 11

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Observation e1be136f-02f7-499b-8fb9-d470046f1c73 · outbound

This paper cites End-to-end Sinkhorn Autoencoder with Noise Generator.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts End-to-end Sinkhorn Autoencoder with Noise Generator

Reference 12

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Observation 2e8fd1bb-9ebe-4e13-8d38-129bba7576d3 · outbound

This paper cites Generative models for fast cluster simulations in the TPC for the ALICE experiment.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Generative models for fast cluster simulations in the TPC for the ALICE experiment

Reference 13

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Observation ba9ae54c-a747-4238-a8b6-c2ae9b7696a1 · outbound

This paper cites ALICE technical design report of the zero degree calorimeter (ZDC).

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts ALICE technical design report of the zero degree calorimeter (ZDC)

Reference 14

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Observation acf89482-4215-4988-b54e-0c02c9900854 · outbound

This paper cites DijetGAN: a generative-adversarial network ap- proach for the simulation of QCD dijet events at the LHC.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts DijetGAN: a generative-adversarial network ap- proach for the simulation of QCD dijet events at the LHC

Reference 15

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Observation e2727b4c-3ee2-4ef6-b987-fd1401f16272 · outbound

This paper cites Glam: Efficient scaling of language models with mixture- of-experts.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Glam: Efficient scaling of language models with mixture- of-experts

Reference 16

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Observation 2df43d93-9c04-4c5c-9d73-ec26730c44e9 · outbound

This paper cites Machine Learning methods for simulating particle response in the Zero Degree Calorimeter at the ALICE experiment, CERN.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Machine Learning methods for simulating particle response in the Zero Degree Calorimeter at the ALICE experiment, CERN

Reference 17

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Observation a8f726e4-7183-481f-9f68-140e31aed3b5 · outbound

This paper cites Selectively Increasing the Diversity of GAN- Generated Samples.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Selectively Increasing the Diversity of GAN- Generated Samples

Reference 18

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Observation 0740c6c0-9849-4d42-af7e-179254ef78c5 · outbound

This paper cites Depth-Adaptive Transformer.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Depth-Adaptive Transformer

Reference 19

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Observation fea0c89e-0833-4397-a60b-0e47d2132846 · outbound

This paper cites Precise simulation of electromagnetic calorimeter showers using a Wasserstein Generative Adversarial Network.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Precise simulation of electromagnetic calorimeter showers using a Wasserstein Generative Adversarial Network

Reference 20

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Observation 1a374c28-bd03-4a0f-b26f-cd5aa8d2c8f9 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 21

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Observation d2870b43-6ae3-4f18-a75b-ee7285224f44 · outbound

This paper cites Spatially adaptive computation time for residual networks.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Spatially adaptive computation time for residual networks

Reference 22

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Observation 398a64de-03b4-4727-bfa2-3c0d4d3decf4 · outbound

This paper cites Generative Adversarial Nets.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Generative Adversarial Nets

Reference 23

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Observation c349f621-aec4-4447-8250-c7474c3afc0e · outbound

This paper cites Adaptive Computation Time for Recurrent Neural Networks.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Adaptive Computation Time for Recurrent Neural Networks

Reference 24

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Observation 7a1a0758-d194-41fd-83e8-7611b756c0c0 · outbound

This paper cites DEMix Layers: Disentangling Domains for Modular Language Modeling.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts DEMix Layers: Disentangling Domains for Modular Language Modeling

Reference 25

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Observation ee2efed5-8b88-49e8-9497-a5a23add0c81 · outbound

This paper cites Channel selection us- ing gumbel softmax.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Channel selection us- ing gumbel softmax

Reference 26

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Observation 798163c7-b2dd-4688-a6f6-fe72f7c66562 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Distilling the Knowledge in a Neural Network

Reference 27

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Observation 56eb7669-303b-4671-933e-c6cff0359da7 · outbound

This paper cites Learning to simulate high energy particle colli- sions from unlabeled data.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Learning to simulate high energy particle colli- sions from unlabeled data

Reference 28

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Observation b528a7df-80d4-4159-aa60-0a9810ad6199 · outbound

This paper cites Three Dimensional Energy Parametrized Generative Adversarial Networks for Electro- magnetic Shower Simulation.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Three Dimensional Energy Parametrized Generative Adversarial Networks for Electro- magnetic Shower Simulation

Reference 29

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Observation e6f70581-a27c-45e8-b9b3-c4fb115f63b5 · outbound

This paper cites Auto-Encoding Variational Bayes.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Auto-Encoding Variational Bayes

Reference 30

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Observation 3e6eadd2-a80a-41c7-b06e-b5fdc9937c36 · outbound

This paper cites Generative Diffusion Models for Fast Simulations of Particle Collisions at CERN.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Generative Diffusion Models for Fast Simulations of Particle Collisions at CERN

Reference 31

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Observation 970bd6f9-b60e-4fb7-a656-c1b6e174415f · outbound

This paper cites Improving Expert Specialization in Mixture of Experts.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Improving Expert Specialization in Mixture of Experts

Reference 32

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Observation 94fe4d05-0a57-41c6-80bd-c7bcb740922a · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 82d3886f-69c3-409f-b147-668b6aca19b0 · outbound

This paper cites Pruning and quantization for deep neural network ac- celeration: A survey.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Pruning and quantization for deep neural network ac- celeration: A survey

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 560255a9-03b0-44bc-bf3f-a0f0f6858438 · outbound

This paper cites Runtime Neural Pruning.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Runtime Neural Pruning

Reference 35

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b834a1fb-3184-4a07-9fbf-20d7a251d74d · outbound

This paper cites Learning instance-wise sparsity for accelerating deep models.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Learning instance-wise sparsity for accelerating deep models

Reference 36

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 49fa2553-c5f9-4690-ab90-93bb33447564 · outbound

This paper cites Split computing and early exiting for deep learning applications: Survey and research chal- lenges.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Split computing and early exiting for deep learning applications: Survey and research chal- lenges

Reference 37

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3ccc9126-c31e-4147-9308-8ef32a0b2326 · outbound

This paper cites EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8ce2d05a-5702-4fd4-863c-b67a332f9a4e · outbound

This paper cites CaloGAN: Simulat- ing 3D high energy particle showers in multilayer electromagnetic calorimeters.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts CaloGAN: Simulat- ing 3D high energy particle showers in multilayer electromagnetic calorimeters

Reference 39

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 620e71b0-47a7-4d80-8ef9-da50af4b8094 · outbound

This paper cites MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation

Reference 40

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ee91e5ff-dabc-4130-bf5a-4acfdef764a8 · outbound

This paper cites Scaling vision with sparse mixture of experts.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Scaling vision with sparse mixture of experts

Reference 41

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 16b1ed53-dbc7-45fb-8e41-ace5f22cbc2f · outbound

This paper cites Particle physics DL-simulation with control over generated data properties.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Particle physics DL-simulation with control over generated data properties

Reference 42

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3d268104-8721-42b9-98fc-9b0a6b42cce6 · outbound

This paper cites Hash layers for large sparse models.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Hash layers for large sparse models

Reference 43

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3e234551-d324-4db3-8386-d27f803cccf0 · outbound

This paper cites Why should we add early exits to neural net- works?.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Why should we add early exits to neural net- works?

Reference 44

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 1c15d071-c1d0-472e-b590-a619e2c4f2b0 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 45

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation aa975a16-f886-4829-9698-e7c44f5caf29 · outbound

This paper cites Variational Mixture-of-Experts Autoencoders for Multi- Modal Deep Generative Models.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Variational Mixture-of-Experts Autoencoders for Multi- Modal Deep Generative Models

Reference 46

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 420178aa-118c-4e2d-aca5-5b16ddbe2b3f · outbound

This paper cites Efficientnet: Rethinking model scaling for con- volutional neural networks.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Efficientnet: Rethinking model scaling for con- volutional neural networks

Reference 47

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a258ed71-8c08-4eaa-8545-e710374bbb11 · outbound

This paper cites Tolstikhin et al.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Tolstikhin et al

Reference 48

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5ffe3d67-6606-4d66-94a4-38df30b79ec7 · outbound

This paper cites Dynamic convolutions: Exploiting spa- tial sparsity for faster inference.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Dynamic convolutions: Exploiting spa- tial sparsity for faster inference

Reference 49

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 309fde67-2985-4a03-ac5c-845a8dfb71a4 · outbound

This paper cites Skipnet: Learning dynamic routing in convolutional networks.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Skipnet: Learning dynamic routing in convolutional networks

Reference 50

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6b6f953e-6120-4213-b496-68254f077f91 · outbound

This paper cites Zero time waste in pre-trained early exit neural net- works.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Zero time waste in pre-trained early exit neural net- works

Reference 51

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 01a581ed-1dbe-4e80-99d2-0d7fddf7e451 · outbound

This paper cites Applying generative neural networks for fast simulations of the ALICE (CERN) experiment.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Applying generative neural networks for fast simulations of the ALICE (CERN) experiment

Reference 52

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 420fd8b3-536c-45e8-8100-020cfb1c4dcf · outbound

This paper cites an unresolved cited work.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Unresolved cited work

Reference 53

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6f00af5a-f3ef-4e31-b7d2-43abdf64e89b · outbound

This paper cites Fast simulation of the Zero Degree Calorimeter responses with generative neural networks.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Fast simulation of the Zero Degree Calorimeter responses with generative neural networks

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:43:02.176627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d41400b5-d4bf-419b-b8d9-57f656a05da0 · outbound

This paper cites MoEfication: Transformer Feed-forward Layers are Mixtures of Experts.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts MoEfication: Transformer Feed-forward Layers are Mixtures of Experts

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:43:02.167556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9113bd34-7f85-4dba-b9a2-c605b82c1a63 · outbound

This paper cites Mixture-of-experts with expert choice routing.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts Mixture-of-experts with expert choice routing

Reference 56

Resolution
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raw_fallback, observed 2026-08-05T14:43:02.158011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 02022475-d46e-430b-ad4e-624ad3c08f62 · outbound

This paper cites MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation.

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:43:02.149212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Pith citing papers

No inbound Pith citation observations are available.