Paper Citation Record · LEDGER

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training

As of 11 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 5 inbound Pith citation observations for arXiv:2604.19241.

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

pith.paper-citation-record.v1
2604.19241 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T02:20:00.625923Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T00:15:48.899045Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-11T01:07:44.019959Z

Reference resolution

53 of 53 outbound references displayed

verified exact16
verified fuzzy21
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch16

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 66da6c2a-8253-448c-90bc-d1da9e8aac1e · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-11T13:06:05.187960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7b8c0ef6-f223-4c54-b625-3e2e11f521ed · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T12:48:40.999279Z

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Observation ffe8079c-8fd9-4c9a-a816-aab4f65cdc85 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Kimi K2: Open Agentic Intelligence

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T17:49:28.234076Z

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Observation 910f05ab-7cef-48c3-8bba-b180ff9a316a · outbound

This paper cites Sid-Lakhdar, Osni Marques, Xinran Zhu, Chang Meng, James W.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Sid-Lakhdar, Osni Marques, Xinran Zhu, Chang Meng, James W

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:22:20.753701Z

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Observation 07f0e3c7-1f59-4311-8ea7-3f5818b42a26 · outbound

This paper cites FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:22:20.756427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 771d797e-eda7-40e0-86a8-aae9ec9c5309 · outbound

This paper cites Dtc-spmm: Bridging the gap in accelerating general sparse matrix multiplication with tensor cores.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Dtc-spmm: Bridging the gap in accelerating general sparse matrix multiplication with tensor cores

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:22:20.748411Z

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Observation 78b4c38a-26e9-4ccf-9da0-c33aca6dd0b3 · outbound

This paper cites Yan, Haichen Shen, Meghan Cowan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, and Arvind Krishnamurthy.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Yan, Haichen Shen, Meghan Cowan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, and Arvind Krishnamurthy

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.836724Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f5d1cdc7-da21-4abd-8040-cb29f965e972 · outbound

This paper cites GC3: An Optimizing Compiler for GPU Collective Communication.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training GC3: An Optimizing Compiler for GPU Collective Communication

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:06:05.130784Z

Source-reported events for the cited work

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Observation 9910f007-77b5-4f4b-8e46-21b7e701b973 · outbound

This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T16:22:09.323619Z

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Observation 47e2ec53-b33d-4dda-a4ee-7fceb129e196 · outbound

This paper cites Gemini 3 pro: Best for complex tasks and bringing creative concepts to life.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Gemini 3 pro: Best for complex tasks and bringing creative concepts to life

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.778932Z

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Observation 94199d36-dc3e-422c-a228-9b211b633178 · outbound

This paper cites Deepseek deepgemm.https://github.com/deepseek-ai/DeepGEMM.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Deepseek deepgemm.https://github.com/deepseek-ai/DeepGEMM

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.775098Z

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Observation c9c0a81e-f413-4a95-a08f-a5f12a14cd8a · outbound

This paper cites EPLB: Expert parallelism load balancer.https://github.com/deepseek-ai/EPLB.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training EPLB: Expert parallelism load balancer.https://github.com/deepseek-ai/EPLB

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.829774Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 13b002bd-403a-4464-a425-b21586977825 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 13

Resolution: metadata mismatch; local_arxiv, observed 2026-05-10T02:22:20.745599Z

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Observation 628cb1b5-64df-40d5-9e69-67b8842768e2 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T05:36:27.707517Z

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Observation 380db4b4-2128-4070-969b-2915da0c2679 · outbound

This paper cites DeepSeek-V3 Technical Report.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training DeepSeek-V3 Technical Report

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-05-10T02:22:20.777223Z

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Observation 4b2e0c17-39bf-4900-9792-037f915bec17 · outbound

This paper cites Megablocks: Efficient sparse training with mixture-of-experts.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Megablocks: Efficient sparse training with mixture-of-experts

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.801668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 13d1e92c-5aad-42e2-8675-6aaec65d3323 · outbound

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

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Fastermoe: modeling and optimizing training of large-scale dynamic pre-trained models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.816689Z

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Observation 36a3c88b-7e5a-4c57-a0a4-36ffe714ffa5 · outbound

This paper cites ISBN 9781450392051.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training ISBN 9781450392051

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:22:20.772321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c8233072-779d-42b2-90e7-637e2e63a33a · outbound

This paper cites Megascale-moe: Large-scale communication-efficient training of mixture-of-experts models in production.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Megascale-moe: Large-scale communication-efficient training of mixture-of-experts models in production

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:22:20.792865Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cdc58660-fb0f-4d37-8ca1-a3b6209b69d2 · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention , booktitle =.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Efficient Memory Management for Large Language Model Serving with PagedAttention , booktitle =

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:22:20.785190Z

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Observation 1175d644-e51a-49f6-a538-8ff8ed301a29 · outbound

This paper cites TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T13:06:05.145883Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation df5c352b-b3b6-4374-a2d2-eda39f20e0d2 · outbound

This paper cites Netmoe: Accelerating moe training through dynamic sample placement.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Netmoe: Accelerating moe training through dynamic sample placement

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.826544Z

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Observation 468dc8cd-76d3-4096-a1e4-0501c6f32fed · outbound

This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training DeepSeek-VL: Towards Real-World Vision-Language Understanding

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:58:54.896552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8e6b96f6-3b73-4f09-bc9b-d6f8452dec97 · outbound

This paper cites Efficient large-scale language model training on GPU clusters using megatron-lm.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Efficient large-scale language model training on GPU clusters using megatron-lm

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.795542Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c619b48e-c2da-44cb-9325-148fce09a6b2 · outbound

This paper cites Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis , articleno =.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis , articleno =

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:22:20.764122Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ab7678e8-03c7-44cc-a8e9-ec61309cf81b · outbound

This paper cites cuBLAS.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training cuBLAS

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.798348Z

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Observation e148596f-810e-4815-bb3e-248b7bf567b9 · outbound

This paper cites Cutlass.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Cutlass

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.792629Z

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Observation 094117ac-38db-4cea-b24e-266bfe990cbc · outbound

This paper cites Transformer Engine.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Transformer Engine

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.785435Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 46d1206e-8468-49f5-a5ba-ed06f8da8f1a · outbound

This paper cites Nvidia collective communications library.https://developer.nvidia.com/nccl.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Nvidia collective communications library.https://developer.nvidia.com/nccl

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.833907Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e8a0f742-0bce-4c4e-9b8d-1bfbd8a73121 · outbound

This paper cites NVSHMEM.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training NVSHMEM

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.813695Z

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Observation 951a7b2d-116a-4386-9b50-2517f7535b63 · outbound

This paper cites Cudnn.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Cudnn

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.820327Z

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Observation 4658d62d-678c-48d1-8b22-29e16d82ef1f · outbound

This paper cites Cutile.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Cutile

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.810611Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 75f7aef6-ff81-4635-b35a-57928430dca9 · outbound

This paper cites In Proceedings of the 34th ACM SIGPLAN Conference on Programming Language Design and Implementation (Seattle, Washington, USA) (PLDI ’13).

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training In Proceedings of the 34th ACM SIGPLAN Conference on Programming Language Design and Implementation (Seattle, Washington, USA) (PLDI ’13)

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:22:20.769286Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 42fd1dae-0226-49cf-99b3-58636af2d7fb · outbound

This paper cites Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation AI scale.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation AI scale

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.823485Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a89c9baf-3daf-43a5-91ab-27f9b8ac00d8 · outbound

This paper cites TACCL: guiding collective algorithm synthesis using communication sketches.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training TACCL: guiding collective algorithm synthesis using communication sketches

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.782565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ae709182-f79a-4b0d-bd49-57fd5248c1ba · outbound

This paper cites 13 Msccl++: Rethinking gpu communication abstrac- tions for cutting-edge ai applications.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training 13 Msccl++: Rethinking gpu communication abstrac- tions for cutting-edge ai applications

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:06:05.160837Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1fd23176-d698-4b43-b71c-2e2896b225dd · outbound

This paper cites OpenAI GPT-5 System Card.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training OpenAI GPT-5 System Card

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-05-11T13:06:05.091271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 162f04d2-a0cf-4723-a9c3-dfae7f341d36 · outbound

This paper cites Look ma, no bubbles! designing a low-latency megakernel for LLAMA-1B.https://hazyresearch.stanford.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Look ma, no bubbles! designing a low-latency megakernel for LLAMA-1B.https://hazyresearch.stanford

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.840033Z

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Observation 9c6593ea-dde3-49fc-bad7-71e36d02c808 · outbound

This paper cites Tilelang.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Tilelang

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.804445Z

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Observation 4d9a3f9d-d4b2-4089-8bc0-5145c73b963b · outbound

This paper cites T., and Cox, D.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training T., and Cox, D

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:22:20.782611Z

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Observation 70424c11-e580-4bfb-8637-cc2755e560e2 · outbound

This paper cites Deepseek-ocr 2: Visual causal flow.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Deepseek-ocr 2: Visual causal flow

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:06:05.154892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 001275b3-50c1-4502-8acd-9c55eb7af1a1 · outbound

This paper cites Mirage: A multi-level superoptimizer for tensor programs.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Mirage: A multi-level superoptimizer for tensor programs

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.807709Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8d7c778e-2d3e-43e1-a02c-b76f054756b3 · outbound

This paper cites HeterMoE: Efficient Training of Mixture-of-Experts Models on Heterogeneous GPUs.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training HeterMoE: Efficient Training of Mixture-of-Experts Models on Heterogeneous GPUs

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:22:20.798325Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 142864b2-7607-46bb-8820-533d0697d3fb · outbound

This paper cites Qwen3 Technical Report.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Qwen3 Technical Report

Reference 44

Resolution: metadata mismatch; local_arxiv, observed 2026-05-10T02:22:20.787842Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5dbe25a5-b271-4c12-b37a-bcb711a1a898 · outbound

This paper cites Hybridep: Scaling expert parallelism to cross-datacenter scenario via hybrid expert/data transmission.CoRR, abs/2510.19470.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Hybridep: Scaling expert parallelism to cross-datacenter scenario via hybrid expert/data transmission.CoRR, abs/2510.19470

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:22:20.780202Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a56ece74-955e-488a-81e0-21a99ec07a7c · outbound

This paper cites FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-16T13:26:34.840430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 314cc047-63c7-4e6e-98a2-028d0fcc62fd · outbound

This paper cites Moeblaze: Breaking the memory wall for efficient moe training on modern gpus.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Moeblaze: Breaking the memory wall for efficient moe training on modern gpus

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:06:05.100544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a66710f6-37a0-466c-82b1-ea015a73c01f · outbound

This paper cites Comet: Fine-grained Computation-communication Overlapping for Mixture-of-Experts.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Comet: Fine-grained Computation-communication Overlapping for Mixture-of-Experts

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:22:20.774941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 689b5af6-e7a3-48db-8b59-6c774e36567a · outbound

This paper cites Kimi Linear: An Expressive, Efficient Attention Architecture.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Kimi Linear: An Expressive, Efficient Attention Architecture

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:49:11.451207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f33ca7f4-8bc4-40e8-94b9-493731ae88c2 · outbound

This paper cites Deepep: an efficient expert-parallel communication library.https://github.com/deepseek-ai/ DeepEP.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Deepep: an efficient expert-parallel communication library.https://github.com/deepseek-ai/ DeepEP

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:55:12.789393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3ad8e02c-cd63-41e6-a347-8849af033675 · outbound

This paper cites Triton-distributed: Programming Overlapping Kernels on Distributed AI Systems with the Triton Compiler.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training Triton-distributed: Programming Overlapping Kernels on Distributed AI Systems with the Triton Compiler

Reference 51

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T13:06:05.137902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bcbaa556-f5f3-49e8-92a6-29a89e3e840b · outbound

This paper cites TileLink: Generating Efficient Compute-Communication Overlapping Kernels using Tile-Centric Primitives.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training TileLink: Generating Efficient Compute-Communication Overlapping Kernels using Tile-Centric Primitives

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:06:05.170224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5ccfd899-b6aa-43a5-874e-954b84295ffe · outbound

This paper cites MegaScale-Infer: Serving Mixture-of-Experts at Scale with Disaggregated Expert Parallelism.

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training MegaScale-Infer: Serving Mixture-of-Experts at Scale with Disaggregated Expert Parallelism

Reference 53

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T13:06:05.120260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation d48fd47b-27d9-4071-ab35-5fcddb1f043f · inbound

HyperParallel-MoE: Multi-Core Interleaved Scheduling for Fast MoE Training on Ascend NPUs cites this paper.

HyperParallel-MoE: Multi-Core Interleaved Scheduling for Fast MoE Training on Ascend NPUs UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-25T02:55:16.740757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5aa9ec18-b6ca-4b5e-bed4-515bbe1a9efd · inbound

HyperParallel-MoE: Multi-Core Interleaved Scheduling for Fast MoE Training on Ascend NPUs cites this paper.

HyperParallel-MoE: Multi-Core Interleaved Scheduling for Fast MoE Training on Ascend NPUs UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-06-30T15:14:46.920212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f3be937e-2cbe-441f-aba0-308989d8ae18 · inbound

UBEP: Re-architecting Expert Parallelism Communication Library for Production Superpods cites this paper.

UBEP: Re-architecting Expert Parallelism Communication Library for Production Superpods UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-07-08T13:44:54.959728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a95939fd-7d5f-4ca2-a4a0-cfb70e2bfb7e · inbound

UBEP: Re-architecting Expert Parallelism Communication Library for Production Superpods cites this paper.

UBEP: Re-architecting Expert Parallelism Communication Library for Production Superpods UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-07-11T01:07:44.052559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c9d599b9-36c8-4d1f-a50a-b2255d0f2a21 · inbound

Route-Block Membership Selects Packed-AWQ Arithmetic: A Controlled Single-Fixture Mechanism Study cites this paper.

Route-Block Membership Selects Packed-AWQ Arithmetic: A Controlled Single-Fixture Mechanism Study UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T00:15:48.899045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.