Paper Citation Record · LEDGER

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference

As of 17 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2506.22033.

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

pith.paper-citation-record.v1
2506.22033 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:21:08.635007Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

52 of 52 outbound references displayed

verified exact3
verified fuzzy5
unresolved43
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eda8f667-6c97-40e1-8709-c7640524db87 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:12.863562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a7e2ca0d-ed95-45fc-abf6-f24ce6039877 · outbound

This paper cites Llama 2 follow-up: too much RLHF, GPU sizing, technical details.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Llama 2 follow-up: too much RLHF, GPU sizing, technical details

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:21:12.743116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 27287006-71ea-4b4f-aee3-782b6863c827 · outbound

This paper cites AI Inference Market Size, Share and Trends Report.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference AI Inference Market Size, Share and Trends Report

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:21:12.550883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68c9c1f6-c288-418c-85e0-dbd25802cb0b · outbound

This paper cites OpenAI API Documentation.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference OpenAI API Documentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:21:12.301445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 668572f2-9761-4394-81f0-0ed57fa41f2e · outbound

This paper cites ShareGPT Datasets.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference ShareGPT Datasets

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:21:12.099360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8fe31ad3-be65-41c5-9159-e878d7be02f9 · outbound

This paper cites vLLM–Optimization and Tuning.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference vLLM–Optimization and Tuning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:21:11.863187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4deeb3c9-ff8b-430a-8f4c-eb8486bcac22 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:11.726600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 483eb470-30d0-4c87-96da-62ab4b519120 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:11.584750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e3094ddb-046f-4c7f-ad34-77e5c2a2f2e9 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:11.432438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8640ffa2-d7a3-4b79-abce-c8e5e86284ec · outbound

This paper cites Efficient Training of Language Models to Fill in the Middle.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Efficient Training of Language Models to Fill in the Middle

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:15.212688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28b0a20a-608e-4a84-b9cd-64802d1e956d · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:11.349478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4c9d6a34-cb93-46be-b390-3dbaeabb0195 · outbound

This paper cites Hilfer fractional advection-diffusion equations with power-law initial condition; a Numerical study using variational iteration method.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Hilfer fractional advection-diffusion equations with power-law initial condition; a Numerical study using variational iteration method

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:15.500147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 350d479b-3d67-42c8-930c-01e10176205f · outbound

This paper cites Pipeline MoE: A Flexible MoE Implementation with Pipeline Parallelism.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Pipeline MoE: A Flexible MoE Implementation with Pipeline Parallelism

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:21:09.451557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cf1e1b8c-182c-4363-b042-b7af0fc35e48 · outbound

This paper cites The Llama 3 Herd of Models.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference The Llama 3 Herd of Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:15.704474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69d42e74-a598-4bce-8b85-3f8147ce0421 · outbound

This paper cites Hierarchical Neural Story Generation.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Hierarchical Neural Story Generation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:15.795643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d82b7fb0-3dec-4317-b55d-62d7d524cea7 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:11.240085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 67316e09-607d-48a7-82e8-eaf985ffa864 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:15.954063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4f58a12-cd6b-4257-af48-4a0438e3610e · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:11.143841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation afe2f31d-fd0a-4e3f-a1af-958f0bfb29db · outbound

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

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:16.049548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bbfbc50-d118-4b34-af80-607e28c5d775 · outbound

This paper cites gLLM: Global Balanced Pipeline Parallelism System for Distributed LLM Serving with Token Throttling.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference gLLM: Global Balanced Pipeline Parallelism System for Distributed LLM Serving with Token Throttling

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:21:09.287877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 89a8467e-b453-40b8-8e93-3be55432743c · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:16.190154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63992c81-8c65-4d35-a313-9d211d0648ff · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 629b038b-6b07-410a-a29f-4922ae16be94 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d12dede5-368d-42b3-85a1-9949a2573ab1 · outbound

This paper cites Mixtral of Experts.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Mixtral of Experts

Reference 24

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Unavailable: canonical work link unavailable.

Observation 16e3a6c2-f9b7-4c5e-94b9-2c95b6aa4ea8 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d084f37-96ae-4aa0-be5d-434df4b4cf17 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 26

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0c7059ae-fd6d-4c0f-b1ea-c9eb65dbaa9b · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 27

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Observation b96b25f9-5721-49c1-8109-4d4a7e9ff94a · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7bc78cbf-e16f-4e8b-af8b-44bacdcbc419 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:10.784355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5508d0a2-44cb-4a0c-8501-fa58a3e1ab7e · outbound

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

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae5d44d4-a143-4a01-a804-ee47ff718c66 · outbound

This paper cites DeepSeek-V3 Technical Report.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference DeepSeek-V3 Technical Report

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T22:21:07.904773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cefce2a6-b69d-41e6-8783-336b31613bd1 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4310d535-db69-4f10-a7f5-da9604b867fb · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:10.709481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0950a895-2307-4290-a159-804a45563232 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:10.588607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 098aa4c5-edf9-4cd1-8311-560e59a21832 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:10.481868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 23c3e4f1-55b1-48d2-b753-caa8000d3519 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 24a13c47-9d69-4473-9ce4-e6d805307483 · outbound

This paper cites The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink

Reference 37

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This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c531d65f-241c-49a2-b291-30be26f522f0 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 39

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Source-reported events for the cited work

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Observation 1356f8a4-9c85-464a-9ac5-39522fae388a · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

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Source-reported events for the cited work

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Observation 214c4e61-2956-459c-9afe-5f4bb09df192 · outbound

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SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 41

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Observation 5c9a273f-9b2b-41e0-b87c-de85b7be8551 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 42

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d9ca8580-08af-4309-a510-6bc2fdc74e20 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 43

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Source-reported events for the cited work

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Observation 40d011e9-9cfc-47ad-a30a-8069b912bb21 · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 44

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Source-reported events for the cited work

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Observation a0796d54-cf61-41e1-aefe-f2c49c2629a8 · outbound

This paper cites PipeFusion: Patch-level Pipeline Parallelism for Diffusion Transformers Inference.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference PipeFusion: Patch-level Pipeline Parallelism for Diffusion Transformers Inference

Reference 45

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 46

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Source-reported events for the cited work

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Observation 51b7d836-3419-4b09-8350-ea0d214bd869 · outbound

This paper cites SGLang: Efficient Execution of Structured Language Model Programs.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference SGLang: Efficient Execution of Structured Language Model Programs

Reference 47

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 557c3af2-268f-4f09-8fc4-5c2d1f9749ec · outbound

This paper cites an unresolved cited work.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:21:09.605042Z

Source-reported events for the cited work

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Observation 9b514c71-d402-45ab-9f31-d839c8a7030d · outbound

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

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference MegaScale-Infer: Serving Mixture-of-Experts at Scale with Disaggregated Expert Parallelism

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T22:21:08.635007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89d81ba5-9760-4bd5-ab5c-1ec0d6815487 · outbound

This paper cites Importance of Search and Evaluation Strategies in Neural Dialogue Modeling.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference Importance of Search and Evaluation Strategies in Neural Dialogue Modeling

Reference 2018

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Observation d990ec36-4a83-46ce-8f78-4998e8148b68 · outbound

This paper cites The Curious Case of Neural Text Degeneration.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference The Curious Case of Neural Text Degeneration

Reference 2019

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Source-reported events for the cited work

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Observation 49db65b0-7641-43df-b475-86403e866d8c · outbound

This paper cites In Proceedings of the 29th Symposium on Operating Systems Principles.

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference In Proceedings of the 29th Symposium on Operating Systems Principles

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:16.951598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.