dMoE: dLLMs with Learnable Block Experts | Paper Citation Record

Observation 60f09b77-d54f-4be0-8a60-6ee85e971b39 · outbound

This paper cites Diffusion models in text generation: a survey.PeerJ Computer Science, 2024.

dMoE: dLLMs with Learnable Block Experts Diffusion models in text generation: a survey.PeerJ Computer Science, 2024

Reference 1

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Observation c4a03d13-6c9f-453b-8ba4-f020cad61b1f · outbound

This paper cites A survey on parallel text generation: From parallel decoding to diffusion language models.

dMoE: dLLMs with Learnable Block Experts A survey on parallel text generation: From parallel decoding to diffusion language models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.079405Z

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Observation bcf93b68-da33-4821-9777-0728f4568e90 · outbound

This paper cites Large Language Diffusion Models.

dMoE: dLLMs with Learnable Block Experts Large Language Diffusion Models

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.069274Z

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Observation 5cf7b828-1bb3-49fe-949e-d8f46fe8e926 · outbound

This paper cites Dream 7B: Diffusion Large Language Models.

dMoE: dLLMs with Learnable Block Experts Dream 7B: Diffusion Large Language Models

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.081707Z

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Observation f7c3f169-2953-4843-ba67-82a0b1772112 · outbound

This paper cites Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding.

dMoE: dLLMs with Learnable Block Experts Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.109759Z

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Observation 60435e1b-0fe0-4958-be65-d740bbf2d1bd · outbound

This paper cites GPT-4 Technical Report.

dMoE: dLLMs with Learnable Block Experts GPT-4 Technical Report

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.151112Z

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Observation acdf9394-4b2e-4820-8d19-7412646d89e2 · outbound

This paper cites Qwen Technical Report.

dMoE: dLLMs with Learnable Block Experts Qwen Technical Report

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.093401Z

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Observation 4f863aa9-7ea0-4a25-8c70-a26fd50d142c · outbound

This paper cites The Llama 3 Herd of Models.

dMoE: dLLMs with Learnable Block Experts The Llama 3 Herd of Models

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.081901Z

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Observation d7b4951c-36ba-4853-8e55-1f641baf9f1d · outbound

This paper cites Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference.

dMoE: dLLMs with Learnable Block Experts Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.092678Z

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Observation 86e27ef6-ced1-4a3a-8f79-2f7660d6b884 · outbound

This paper cites Mercury: Ultra-Fast Language Models Based on Diffusion.

dMoE: dLLMs with Learnable Block Experts Mercury: Ultra-Fast Language Models Based on Diffusion

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.084117Z

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Observation b0b19b3c-6c06-4cd6-8eb0-5236d28d8b7c · outbound

This paper cites LLaDA2.0: Scaling Up Diffusion Language Models to 100B.

dMoE: dLLMs with Learnable Block Experts LLaDA2.0: Scaling Up Diffusion Language Models to 100B

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.017324Z

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Observation 4d62f37f-6d9e-4b6f-ace9-7b0781aabd46 · outbound

This paper cites Llada2.1: Speeding up text diffusion via token editing, 2026.

dMoE: dLLMs with Learnable Block Experts Llada2.1: Speeding up text diffusion via token editing, 2026

Reference 12

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Observation 6774d0a5-b5ed-4618-9e8c-1038dfbf9742 · outbound

This paper cites Llada-moe: A sparse moe diffusion language model.arXiv preprint arXiv:2509.24389.

dMoE: dLLMs with Learnable Block Experts Llada-moe: A sparse moe diffusion language model.arXiv preprint arXiv:2509.24389

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.028861Z

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Observation 7bbc8153-2034-48ab-97b3-5a6905d1ee98 · outbound

This paper cites Sdar: A syn- ergistic diffusion-autoregression paradigm for scalable sequence generation.arXiv preprint arXiv:2510.06303.

dMoE: dLLMs with Learnable Block Experts Sdar: A syn- ergistic diffusion-autoregression paradigm for scalable sequence generation.arXiv preprint arXiv:2510.06303

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.125308Z

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Observation 766b9bdb-34d6-4120-81cb-26839bba6125 · outbound

This paper cites Openmoe 2: Sparse diffusion language models.

dMoE: dLLMs with Learnable Block Experts Openmoe 2: Sparse diffusion language models

Reference 15

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Observation 89eaa1b7-1d7e-450c-8ede-800de14161d0 · outbound

This paper cites Block diffusion: Interpolating between autoregressive and diffusion language models.

dMoE: dLLMs with Learnable Block Experts Block diffusion: Interpolating between autoregressive and diffusion language models

Reference 16

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Observation e62a1f1a-b2f7-4f84-b6dc-bdce1d046c27 · outbound

This paper cites Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs.

dMoE: dLLMs with Learnable Block Experts Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.115735Z

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Observation 750724b4-e72b-4f90-a591-17ccc1ec5577 · outbound

This paper cites Task-Specific Expert Pruning for Sparse Mixture-of-Experts.

dMoE: dLLMs with Learnable Block Experts Task-Specific Expert Pruning for Sparse Mixture-of-Experts

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T22:52:45.118672Z

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Observation 3bc4c394-8b2b-4471-9367-b887d33043e3 · outbound

This paper cites A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts.

dMoE: dLLMs with Learnable Block Experts A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.130360Z

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Observation da3b8b08-ce24-410f-85a2-23461080d5d9 · outbound

This paper cites Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language Models.

dMoE: dLLMs with Learnable Block Experts Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.144776Z

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Observation 443bc417-9566-4821-9188-faa0047dcff7 · outbound

This paper cites BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity.

dMoE: dLLMs with Learnable Block Experts BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.095922Z

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Observation 7c137020-99f5-4736-9db0-97569797b837 · outbound

This paper cites Merging experts into one: Improving computational efficiency of mixture of experts.

dMoE: dLLMs with Learnable Block Experts Merging experts into one: Improving computational efficiency of mixture of experts

Reference 22

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Observation dd9abeb9-e557-41f2-99aa-1b338c9ed586 · outbound

This paper cites Learning More Generalized Experts by Merging Experts in Mixture-of-Experts.

dMoE: dLLMs with Learnable Block Experts Learning More Generalized Experts by Merging Experts in Mixture-of-Experts

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.107047Z

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Observation f7b65535-c760-47ee-ad3b-cbc694684ff3 · outbound

This paper cites Sub-moe: Efficient mixture-of-expert llms compression via subspace expert merging.

dMoE: dLLMs with Learnable Block Experts Sub-moe: Efficient mixture-of-expert llms compression via subspace expert merging

Reference 24

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Observation a3035e5a-639b-4524-93f7-9df70b713721 · outbound

This paper cites Not all experts are equal: Efficient expert pruning and skipping for mixture-of-experts large language models.

dMoE: dLLMs with Learnable Block Experts Not all experts are equal: Efficient expert pruning and skipping for mixture-of-experts large language models

Reference 25

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Observation ea4de0d8-6a6c-4243-bb0b-2c8c889a12c6 · outbound

This paper cites arXiv preprint arXiv:2511.15690 , year=.

dMoE: dLLMs with Learnable Block Experts arXiv preprint arXiv:2511.15690 , year=

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.103851Z

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Observation 8d27f3e0-0598-4e9a-9ae4-314ca7c41741 · outbound

This paper cites DA-MoE: Towards Dynamic Expert Allocation for Mixture-of-Experts Models.

dMoE: dLLMs with Learnable Block Experts DA-MoE: Towards Dynamic Expert Allocation for Mixture-of-Experts Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.059089Z

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Observation 20c9f837-6813-4417-87fa-7f07eba35551 · outbound

This paper cites Eac-moe: Expert-selection aware compressor for mixture-of-experts large language models.

dMoE: dLLMs with Learnable Block Experts Eac-moe: Expert-selection aware compressor for mixture-of-experts large language models

Reference 28

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Observation 002143b6-538c-4951-83f6-16c39a9623de · outbound

This paper cites Rexmoe: Reusing experts with minimal overhead in mixture-of-experts.

dMoE: dLLMs with Learnable Block Experts Rexmoe: Reusing experts with minimal overhead in mixture-of-experts

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.047801Z

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Observation ed6d3b79-4016-43f3-956b-5de2e1ee12f0 · outbound

This paper cites Opportunistic expert activation: Batch-aware expert routing for faster decode without retraining.arXiv preprint arXiv:2511.02237, 2025.

dMoE: dLLMs with Learnable Block Experts Opportunistic expert activation: Batch-aware expert routing for faster decode without retraining.arXiv preprint arXiv:2511.02237, 2025

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.099977Z

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Observation 589ce929-a2a2-4c58-99f0-c8f71dfcf261 · outbound

This paper cites Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models.

dMoE: dLLMs with Learnable Block Experts Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-08-04T03:26:42.507894Z

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Observation cc2cc0ba-a77c-456e-aa30-5833f9e0169f · outbound

This paper cites TEAM: Temporal-Spatial Consistency Guided Expert Activation for MoE Diffusion Language Model Acceleration.

dMoE: dLLMs with Learnable Block Experts TEAM: Temporal-Spatial Consistency Guided Expert Activation for MoE Diffusion Language Model Acceleration

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.066882Z

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Observation e3b85eb1-9013-4316-8e68-4d2fd54bd013 · outbound

This paper cites Dynamic expert sharing: Decoupling memory from parallelism in mixture-of-experts diffusion llms.arXiv preprint arXiv:2602.00879, 2026.

dMoE: dLLMs with Learnable Block Experts Dynamic expert sharing: Decoupling memory from parallelism in mixture-of-experts diffusion llms.arXiv preprint arXiv:2602.00879, 2026

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.023185Z

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Observation 94f40e8e-f01f-4221-abb8-22f127a33d48 · outbound

This paper cites Let’s verify step by step.

dMoE: dLLMs with Learnable Block Experts Let’s verify step by step

Reference 34

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Observation cf209860-4e7e-4ddf-9ce7-a6a5baf76384 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

dMoE: dLLMs with Learnable Block Experts Training Verifiers to Solve Math Word Problems

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.040992Z

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Observation c1a320b0-5b4b-4ee8-84f8-83a5cdb962c5 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

dMoE: dLLMs with Learnable Block Experts Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.053268Z

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Observation 5d80d2d3-40c1-4b2b-9faf-75ffbea15b5d · outbound

This paper cites Measuring massive multitask language understanding.

dMoE: dLLMs with Learnable Block Experts Measuring massive multitask language understanding

Reference 37

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Observation 745a04e6-0adc-4b2a-8528-164141933463 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

dMoE: dLLMs with Learnable Block Experts High-resolution image synthesis with latent diffusion models

Reference 38

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Observation e60315ee-d4a5-4011-803e-40476e14e3b7 · outbound

This paper cites Scalable diffusion models with transformers.

dMoE: dLLMs with Learnable Block Experts Scalable diffusion models with transformers

Reference 39

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Observation ba03a254-e0a9-465d-8e95-708e799bea06 · outbound

This paper cites Video diffusion models.

dMoE: dLLMs with Learnable Block Experts Video diffusion models

Reference 40

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Observation 1bf8bfd2-9781-4e03-9144-b47a53634ee8 · outbound

This paper cites Video generation models as world simulators.OpenAI Blog, 1(8):1, 2024.

dMoE: dLLMs with Learnable Block Experts Video generation models as world simulators.OpenAI Blog, 1(8):1, 2024

Reference 41

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Observation d8b7e1ac-56f6-48d5-9137-35997613f8c2 · outbound

This paper cites AudioLDM: Text-to-Audio Generation with Latent Diffusion Models.

dMoE: dLLMs with Learnable Block Experts AudioLDM: Text-to-Audio Generation with Latent Diffusion Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.089912Z

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Observation bb616b29-3bd3-4b95-9d54-9ba4a3f38f36 · outbound

This paper cites Fast timing-conditioned latent audio diffusion.

dMoE: dLLMs with Learnable Block Experts Fast timing-conditioned latent audio diffusion

Reference 43

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Observation 837a96aa-b93f-47fd-9a27-44c0f3cfea77 · outbound

This paper cites Denoising diffusion probabilistic models.

dMoE: dLLMs with Learnable Block Experts Denoising diffusion probabilistic models

Reference 44

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Observation 2fb89607-e2ad-477e-83f5-343f217de10d · outbound

This paper cites Generative modeling by estimating gradients of the data distribution.

dMoE: dLLMs with Learnable Block Experts Generative modeling by estimating gradients of the data distribution

Reference 45

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Observation b1aaa8ae-de63-472e-bfbc-591e12337c5d · outbound

This paper cites Denoising Diffusion Implicit Models.

dMoE: dLLMs with Learnable Block Experts Denoising Diffusion Implicit Models

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.026191Z

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Observation fa092506-52eb-4ff9-8e7e-8688c0e21167 · outbound

This paper cites Structured denoising diffusion models in discrete state-spaces.

dMoE: dLLMs with Learnable Block Experts Structured denoising diffusion models in discrete state-spaces

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-28T22:50:51.900169Z

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Observation 19c7444a-1880-4bcd-88a6-2c5ee4b69167 · outbound

This paper cites Simple and effective masked diffusion language models.

dMoE: dLLMs with Learnable Block Experts Simple and effective masked diffusion language models

Reference 48

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Observation 5f36f101-476b-436c-aa5d-03dab7f99630 · outbound

This paper cites Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution.

dMoE: dLLMs with Learnable Block Experts Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.018190Z

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Observation bae76a04-7a4d-40e3-a56c-ab8f666535e3 · outbound

This paper cites Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling.

dMoE: dLLMs with Learnable Block Experts Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.009032Z

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Observation b96fecb9-184c-4972-8f1a-2e88775f9980 · outbound

This paper cites LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models.

dMoE: dLLMs with Learnable Block Experts LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.011857Z

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Observation e39905c6-0a80-403e-992b-40487d217b6b · outbound

This paper cites d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning.

dMoE: dLLMs with Learnable Block Experts d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.087047Z

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Observation d7ddf474-6dc3-4b0f-802c-c3c9644fa8f9 · outbound

This paper cites wd1: Weighted policy optimization for reasoning in diffusion language models.arXiv preprint arXiv:2507.08838.

dMoE: dLLMs with Learnable Block Experts wd1: Weighted policy optimization for reasoning in diffusion language models.arXiv preprint arXiv:2507.08838

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.034643Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 88a79c40-5ca8-4ad1-a4da-a42158ee6fa6 · outbound

This paper cites Boundary-Guided Policy Optimization for Memory-efficient RL of Diffusion Large Language Models.

dMoE: dLLMs with Learnable Block Experts Boundary-Guided Policy Optimization for Memory-efficient RL of Diffusion Large Language Models

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.140872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 369f6c19-6d0e-4a61-bf92-8da3223737cc · outbound

This paper cites dvoting: Fast voting for dllms.

dMoE: dLLMs with Learnable Block Experts dvoting: Fast voting for dllms

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.052147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ae53f91f-459a-4eb9-a811-0660bc53df32 · outbound

This paper cites Efficient reasoning models: A survey.

dMoE: dLLMs with Learnable Block Experts Efficient reasoning models: A survey

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.020718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6939d29e-488c-4439-aea2-ed4237fc773b · outbound

This paper cites MMaDA: Multimodal Large Diffusion Language Models.

dMoE: dLLMs with Learnable Block Experts MMaDA: Multimodal Large Diffusion Language Models

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.090923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fd99a98f-a9e7-4732-b85d-664f1c3a7ae7 · outbound

This paper cites LaViDa: A Large Diffusion Language Model for Multimodal Understanding.

dMoE: dLLMs with Learnable Block Experts LaViDa: A Large Diffusion Language Model for Multimodal Understanding

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.004416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9ae228eb-72a0-4e85-a531-164d1de881bb · outbound

This paper cites LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning.

dMoE: dLLMs with Learnable Block Experts LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.042761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8f1b375b-00ca-4521-9b9a-889899d0de85 · outbound

This paper cites DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation.

dMoE: dLLMs with Learnable Block Experts DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.144554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 33381d50-e5d6-43a9-8aa3-0b118810b646 · outbound

This paper cites contributors.

dMoE: dLLMs with Learnable Block Experts contributors

Reference 61

Resolution: unresolved; no resolver link, observed 2026-06-28T22:50:51.900169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 557ddb97-068f-48fd-865d-2006575d4d09 · outbound

This paper cites Discrete diffusion in large language and multimodal models: A survey.

dMoE: dLLMs with Learnable Block Experts Discrete diffusion in large language and multimodal models: A survey

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.133729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 212b589b-0cd3-4c28-886d-61984ddd3a37 · outbound

This paper cites A Survey on Diffusion Language Models.

dMoE: dLLMs with Learnable Block Experts A Survey on Diffusion Language Models

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.088162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 284a7712-27d3-41e7-8778-07cb93c37838 · outbound

This paper cites DMax: Aggressive Parallel Decoding for dLLMs.

dMoE: dLLMs with Learnable Block Experts DMax: Aggressive Parallel Decoding for dLLMs

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.153989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ab488afc-5451-4c6a-a46c-aeb37f1a0893 · outbound

This paper cites Edge-moe: Memory-efficient multi-task vision transformer architecture with task-level sparsity via mixture-of-experts.

dMoE: dLLMs with Learnable Block Experts Edge-moe: Memory-efficient multi-task vision transformer architecture with task-level sparsity via mixture-of-experts

Reference 65

Resolution: unresolved; no resolver link, observed 2026-06-28T22:50:51.900169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6e87b32-4e92-42ca-bfa7-29e71684af2a · outbound

This paper cites Fastermoe: modeling and optimizing training of large-scale dynamic pre-trained models.

dMoE: dLLMs with Learnable Block Experts Fastermoe: modeling and optimizing training of large-scale dynamic pre-trained models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-06-28T22:50:51.900169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d41c42f3-c0dd-4398-94b2-597ab419374f · outbound

This paper cites Self-distillation: Towards efficient and compact neural networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(8):4388–4403, 2021.

dMoE: dLLMs with Learnable Block Experts Self-distillation: Towards efficient and compact neural networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(8):4388–4403, 2021

Reference 67

Resolution: unresolved; no resolver link, observed 2026-06-28T22:50:51.900169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df22d61c-05bf-465c-a469-d18a23d2d37b · outbound

This paper cites Numinamath: The largest public dataset in ai4maths with 860k pairs of competition math problems and solutions.Hugging Face repository, 13(9):9, 2024.

dMoE: dLLMs with Learnable Block Experts Numinamath: The largest public dataset in ai4maths with 860k pairs of competition math problems and solutions.Hugging Face repository, 13(9):9, 2024

Reference 68

Resolution: unresolved; no resolver link, observed 2026-06-28T22:50:51.900169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbbcf078-403d-4e97-b734-e92d41980569 · outbound

This paper cites OpenThoughts: Data Recipes for Reasoning Models.

dMoE: dLLMs with Learnable Block Experts OpenThoughts: Data Recipes for Reasoning Models

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.132201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ee5a556f-7e5d-4f09-aec6-01a3d16038b7 · outbound

This paper cites Can mllms guide me home? a benchmark study on fine-grained visual reasoning from transit maps.

dMoE: dLLMs with Learnable Block Experts Can mllms guide me home? a benchmark study on fine-grained visual reasoning from transit maps

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.122181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8984aee7-a022-4d46-a75e-02077e4df300 · outbound

This paper cites arXiv preprint arXiv:2507.20198 , year=.

dMoE: dLLMs with Learnable Block Experts arXiv preprint arXiv:2507.20198 , year=

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.148231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d2c2f2df-9c25-481f-8b07-596682f91add · outbound

This paper cites arXiv preprint arXiv:2510.06751 (2025).

dMoE: dLLMs with Learnable Block Experts arXiv preprint arXiv:2510.06751 (2025)

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.134927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b4667d7c-378e-429e-b8b9-b24a84da5f66 · outbound

This paper cites Rewardmap: Tackling sparse rewards in fine-grained visual reasoning via multi-stage rein- forcement learning.

dMoE: dLLMs with Learnable Block Experts Rewardmap: Tackling sparse rewards in fine-grained visual reasoning via multi-stage rein- forcement learning

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.141475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 01159aa5-88b2-4c1e-ad75-536ccc556805 · outbound

This paper cites OmniZip: Audio-Guided Dynamic Token Compression for Fast Omnimodal Large Language Models.

dMoE: dLLMs with Learnable Block Experts OmniZip: Audio-Guided Dynamic Token Compression for Fast Omnimodal Large Language Models

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.065126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c1238e7c-a097-4e82-af97-6cca990b00b3 · outbound

This paper cites Mergemix: A unified augmentation paradigm for visual and multi-modal understanding.

dMoE: dLLMs with Learnable Block Experts Mergemix: A unified augmentation paradigm for visual and multi-modal understanding

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.073076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 26618440-c9a9-4ec9-8a58-fa9f5fd9c738 · outbound

This paper cites PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks.

dMoE: dLLMs with Learnable Block Experts PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-06-28T22:52:45.075925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d7a3aeeb-16be-42d6-8fb4-b9c661167415 · outbound

This paper cites Which heads matter for reasoning? rl-guided kv cache compression.

dMoE: dLLMs with Learnable Block Experts Which heads matter for reasoning? rl-guided kv cache compression

Reference 77

Resolution: unresolved; no resolver link, observed 2026-06-28T22:50:51.900169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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