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Paper Citation Record · LEDGER

TrimMoE A communication aware and adaptive depth framework for distributed edge inference

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2608.00573.

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

pith.paper-citation-record.v1
2608.00573 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T00:38:34.613440Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

37 of 37 outbound references displayed

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  • unresolved7
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8d7ae9ad-b54b-4efa-9281-98f38b6faa86 · outbound

This paper cites A survey of large language models,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference A survey of large language models,

Reference 1

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Observation 2d4840ae-6aef-4374-a407-b987a9ca8b16 · outbound

This paper cites A Survey on Efficient Inference for Large Language Models.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference A Survey on Efficient Inference for Large Language Models

Reference 2

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Observation 2d9aa3ed-80f5-4761-b047-9d0c8d24a460 · outbound

This paper cites A r e v i e w o n edge large language models: Design, execution, and applications,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference A r e v i e w o n edge large language models: Design, execution, and applications,

Reference 3

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Observation e2192732-d85c-4113-ace8-6b0cbb766eee · outbound

This paper cites Mixtral of Experts.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Mixtral of Experts

Reference 4

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Observation 53e939e6-2b49-4836-9e82-23e60544b5b7 · outbound

This paper cites A survey on mixture of experts in large language models,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference A survey on mixture of experts in large language models,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 459e3e6c-78bf-4299-8094-a87c65d19232 · outbound

This paper cites GPTQ: Accurate post-training quantization for generative pre-trained transformers,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference GPTQ: Accurate post-training quantization for generative pre-trained transformers,

Reference 6

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Source-reported events for the cited work

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Observation 54d2ccd7-bba8-4829-bb87-0f400defa195 · outbound

This paper cites LLM-Pruner: On the structural pruning of large language models,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference LLM-Pruner: On the structural pruning of large language models,

Reference 7

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Source-reported events for the cited work

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Observation dd546f79-522e-4c4f-957d-85572b4e236a · outbound

This paper cites Survey on knowledge distillation for large language models: Methods, Evaluation, and Application,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Survey on knowledge distillation for large language models: Methods, Evaluation, and Application,

Reference 8

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Source-reported events for the cited work

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Observation ef5bf46e-91f5-4947-8eab-669f6f87a7b1 · outbound

This paper cites SVD-LLM: Truncation-aware singular value decomposition for large language model compression,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference SVD-LLM: Truncation-aware singular value decomposition for large language model compression,

Reference 9

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Source-reported events for the cited work

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Observation 521d492e-3e88-484e-99af-c524f140c884 · outbound

This paper cites LoRA: Low-rank adaptation of large language models,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference LoRA: Low-rank adaptation of large language models,

Reference 10

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Source-reported events for the cited work

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Observation 87543faf-941a-48f2-b23b-e9e960d070ac · outbound

This paper cites LLM in a flash: Efficient large language model inference with limited memory,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference LLM in a flash: Efficient large language model inference with limited memory,

Reference 11

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Source-reported events for the cited work

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Observation 9c2bd2a0-375d-4e93-af10-e72fc1b81545 · outbound

This paper cites EdgeShard: Efficient large language model inference via collaborative edge computing,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference EdgeShard: Efficient large language model inference via collaborative edge computing,

Reference 12

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4fa64280-f3dc-4b34-8e3b-9a07fa0523de · outbound

This paper cites AlpaServe: Statistical multiplexing with model parallelism for deep learning serving,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference AlpaServe: Statistical multiplexing with model parallelism for deep learning serving,

Reference 13

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f50a6135-ca1d-4e6d-9f19-401c862ee956 · outbound

This paper cites Orca: A distributed serving system for transformer-based generative models,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Orca: A distributed serving system for transformer-based generative models,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0f7a89d8-d880-470f-97a2-fcc20d3834de · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 15

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Observation 46348b97-727c-4a79-9967-4b6f7e0bb972 · outbound

This paper cites RDMA over commodity Ethernet at scale,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference RDMA over commodity Ethernet at scale,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 44ef7923-2372-496c-82d6-91a60c3b09bc · outbound

This paper cites An introduction to the InfiniBand architecture,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference An introduction to the InfiniBand architecture,

Reference 17

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Observation 84e203cd-d350-4de0-b404-fd74ccc9c014 · outbound

This paper cites A s u r v e y o n mobile edge computing: The communication perspective,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference A s u r v e y o n mobile edge computing: The communication perspective,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 36ea87fd-59ad-49ea-9070-0a610e369e95 · outbound

This paper cites Resource management in mobile edge computing: A comprehensive survey,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Resource management in mobile edge computing: A comprehensive survey,

Reference 19

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b9515deb-db61-482b-b323-01c16bae3396 · outbound

This paper cites ShortGPT: Layers in large language models are more redundant than you expect,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference ShortGPT: Layers in large language models are more redundant than you expect,

Reference 20

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raw_fallback, observed 2026-08-05T00:38:38.874283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 753b345f-f689-4ed1-ad0f-69a2f409a63a · outbound

This paper cites Mixture-of-Depths: Dynamically allocating compute in transformer-based language models.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Reference 21

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Observation 8a0b6591-ef63-419c-ad9b-aed443d82483 · outbound

This paper cites Confident adaptive language modeling,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Confident adaptive language modeling,

Reference 22

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 805ae9a7-f875-40f0-82b1-cb1d88333de3 · outbound

This paper cites Distributed inference acceleration with adaptive DNN partitioning and offloading,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Distributed inference acceleration with adaptive DNN partitioning and offloading,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7233bfc1-61f9-4736-a0d2-cbde283a5ca4 · outbound

This paper cites PArtNNer: Platform-agnostic adaptive edge-cloud DNN partitioning for minimizing end-to-end latency,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference PArtNNer: Platform-agnostic adaptive edge-cloud DNN partitioning for minimizing end-to-end latency,

Reference 24

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9b080fcb-dda9-4997-8648-588be100f938 · outbound

This paper cites S p l i t c o m p u t i n g a n d e a r l y exiting for deep learning applications: Survey and research challenges,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference S p l i t c o m p u t i n g a n d e a r l y exiting for deep learning applications: Survey and research challenges,

Reference 25

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9e01e4d3-3393-4941-904b-8b230c30bb92 · outbound

This paper cites Edge-LLM: A collaborative framework for large language model serving in edge computing,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Edge-LLM: A collaborative framework for large language model serving in edge computing,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ad7fe097-11bc-4738-a79e-ffbe609a5bf3 · outbound

This paper cites Communication-efficient distributed on-device LLM inference over wireless networks,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Communication-efficient distributed on-device LLM inference over wireless networks,

Reference 27

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ced3409a-c84b-40fc-933c-5fc316b991b8 · outbound

This paper cites Jupiter: Fast and resource-efficient collaborative inference of generative LLMs on edge devices,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Jupiter: Fast and resource-efficient collaborative inference of generative LLMs on edge devices,

Reference 28

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raw_fallback, observed 2026-08-05T00:38:37.104600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation aa09ac28-2974-40a1-982a-8aa8076ab7e0 · outbound

This paper cites AdapMoE: Adaptive sensitivity-based expert gating and management for efficient MoE inference,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference AdapMoE: Adaptive sensitivity-based expert gating and management for efficient MoE inference,

Reference 29

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raw_fallback, observed 2026-08-05T00:38:36.733654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 83cd0344-0fb0-49a7-add1-1537717d61ce · outbound

This paper cites SlimCaching: Edge caching of mixture-of-experts for distributed inference,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference SlimCaching: Edge caching of mixture-of-experts for distributed inference,

Reference 30

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raw_fallback, observed 2026-08-05T00:38:36.435395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 79f1687b-6155-4708-ac53-32a88bc8e88f · outbound

This paper cites Diff-MoE: Efficient batched MoE inference with priority-driven differential expert caching,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference Diff-MoE: Efficient batched MoE inference with priority-driven differential expert caching,

Reference 31

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raw_fallback, observed 2026-08-05T00:38:36.205313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T00:38:34.066116Z digest=sha256:49459a38449d3bef9ba26f31e48fac8380bf486fff2c6ed7d9d49b9dc02dd9f6

Observation 3f76cdf2-7178-4ab3-b2a1-df8c59585127 · outbound

This paper cites PROBE: Co-balancing computation and communication in MoE inference via real-time predictive prefetching,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference PROBE: Co-balancing computation and communication in MoE inference via real-time predictive prefetching,

Reference 32

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no resolver link, observed 2026-08-05T00:38:34.139685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T00:38:34.139685Z digest=sha256:e2702b0fd72cd3422b3e961fc6b640c87be4d3d0bfffe6d550eead1df88c8b2a

Observation 4b6c08dc-e58d-4ab0-801c-51ebfa7784e9 · outbound

This paper cites MegaScale-Infer: Efficient mixture-of-experts model serving with disaggregated expert parallelism,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference MegaScale-Infer: Efficient mixture-of-experts model serving with disaggregated expert parallelism,

Reference 33

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raw_fallback, observed 2026-08-05T00:38:35.968662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 42ffc3c9-37fe-4b96-966e-51f854f9c016 · outbound

This paper cites WDMoE: Wireless distributed mixture of experts for large language models,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference WDMoE: Wireless distributed mixture of experts for large language models,

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-05T00:38:35.609792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ec2343cc-536f-40ac-a424-5c8d8622fec8 · outbound

This paper cites MoE2: Optimizing collaborative inference for edge large language models,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference MoE2: Optimizing collaborative inference for edge large language models,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T00:38:35.349564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T00:38:34.399556Z digest=sha256:05c387a9bcece7d2ad12ce5a14ccc21867afe3259326f3380b725e1fa2cb1e70

Observation 58bab9cb-5ae7-4b69-a1e6-c66281a1cc64 · outbound

This paper cites LayerSkip: Enabling early exit inference and self-speculative decoding,.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference LayerSkip: Enabling early exit inference and self-speculative decoding,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T00:38:35.118909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 91d0d88d-1bfb-44de-b5cd-6a351b33cabf · outbound

This paper cites OrderMoE: An expert similarity driven distributed edge MoE inference.

TrimMoE A communication aware and adaptive depth framework for distributed edge inference OrderMoE: An expert similarity driven distributed edge MoE inference

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T00:38:34.613440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.