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Paper Citation Record · LEDGER

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration

As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2505.14085.

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

pith.paper-citation-record.v1
2505.14085 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:42:23.582268Z

measured 36 of 36 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

36 of 36 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c86273b6-479b-4f88-b177-5d17cecd19d0 · outbound

This paper cites 6g wireless communication systems: Applications, requirements, technolo- gies, challenges, and research directions,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration 6g wireless communication systems: Applications, requirements, technolo- gies, challenges, and research directions,

Reference 1

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Observation 3a715e3e-690f-4f32-997b-9cf3b6109eb0 · outbound

This paper cites White Paper on Broadband Connectivity in 6G.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration White Paper on Broadband Connectivity in 6G

Reference 2

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Observation 11bedb4e-9721-4d3d-ab78-bd7c0e58505f · outbound

This paper cites Ai-native network slicing for 6g networks,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Ai-native network slicing for 6g networks,

Reference 3

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Observation 8ae12871-c2b9-44fc-a741-3ef16b254497 · outbound

This paper cites Towards 6g wireless communication networks: Vision, enabling technologies, and new paradigm shifts,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Towards 6g wireless communication networks: Vision, enabling technologies, and new paradigm shifts,

Reference 4

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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 3aaa0cb3-ba2d-4600-bde1-edcc9012da77 · outbound

This paper cites Optimizing llm inference clusters for enhanced performance and energy efficiency,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Optimizing llm inference clusters for enhanced performance and energy efficiency,

Reference 5

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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 baca5998-54b7-4d72-ad0a-dd51c56179a4 · outbound

This paper cites Performance modeling and workload analysis of dis- tributed large language model training and inference,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Performance modeling and workload analysis of dis- tributed large language model training and inference,

Reference 6

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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 171f39d0-57f8-4d81-b5ed-c4e50d2e374b · outbound

This paper cites Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters,

Reference 7

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

source=pdf_text observed=2026-08-07T15:42:20.736238Z digest=sha256:aa89e36469c7100d21e5ad20c0125eef1d93b36b0c6b1618bc7253fcf727db4d

Observation 3cffd5d7-2ef3-4502-84bf-5bfca4a043d6 · outbound

This paper cites Reducing activation recomputation in large transformer models,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Reducing activation recomputation in large transformer models,

Reference 8

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source=pdf_text observed=2026-08-07T15:42:20.837495Z digest=sha256:bd16986e306519b090b45bc634ece4192f8e4b479745322e48d31c62c0282568

Observation f5aed8f0-a8e7-435c-8072-a37046d6fe4c · outbound

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

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Efficient large-scale language model training on gpu clusters using megatron-lm,

Reference 9

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source=pdf_text observed=2026-08-07T15:42:20.925708Z digest=sha256:7f88428f204b4b4b7a4ea0ab47f2df77b7ec3611828c2741a9f90e6c19be3597

Observation 2252d4ab-9b9f-4f5d-ab01-f409ad64ac1e · outbound

This paper cites Efficient memory management for large language model serving with pagedattention,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Efficient memory management for large language model serving with pagedattention,

Reference 10

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source=pdf_text observed=2026-08-07T15:42:21.025575Z digest=sha256:c80b6935c78bfb9d2721b3fa937ca1613baf2933780a9d4ab54115f5b55318df

Observation 83d66fd5-4371-4bd0-b743-0b6af6ac3726 · outbound

This paper cites RelayAttention for Efficient Large Language Model Serving with Long System Prompts.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration RelayAttention for Efficient Large Language Model Serving with Long System Prompts

Reference 11

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source=pdf_text observed=2026-08-07T15:42:21.128740Z digest=sha256:531a59d317749abbd01d3d4ddc384f957595d18356f788dd27b18fddd46d8bd3

Observation 4db954af-3db0-403d-8890-0f273a857ee4 · outbound

This paper cites Prompt cache: Modular attention reuse for low-latency inference,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Prompt cache: Modular attention reuse for low-latency inference,

Reference 12

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

source=pdf_text observed=2026-08-07T15:42:21.231655Z digest=sha256:093c9c3bae3007b25b724aa309ded5888f9049c89a6fb8f3e46f8ad305413b15

Observation ece9a834-b1c9-4f7d-a5cb-c5cd559267ec · outbound

This paper cites Model pruning enables efficient federated learning on edge devices,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Model pruning enables efficient federated learning on edge devices,

Reference 13

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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.

source=pdf_text observed=2026-08-07T15:42:21.339035Z digest=sha256:129934a9fc5665d13d8f7026ea6fcb4d038de53041e2f926783b1d5dc9014e33

Observation 94330cc7-8d05-49a8-8d41-dbe980d5b3e6 · outbound

This paper cites EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting

Reference 14

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Observation 5614e127-983e-4639-b28f-1dc4facfd617 · outbound

This paper cites Optimizing mobile-edge ai-generated everything (aigx) services by prompt engineering: Fundamental, framework, and case study,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Optimizing mobile-edge ai-generated everything (aigx) services by prompt engineering: Fundamental, framework, and case study,

Reference 15

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

source=pdf_text observed=2026-08-07T15:42:21.553679Z digest=sha256:1fa77de6ef6071979014c3bd5da77e664b78be76f05968c513db2c289ff4ad6e

Observation 9d0856ff-9b02-4b2d-80a0-05f524d75af0 · outbound

This paper cites CE-CoLLM: Efficient and Adaptive Large Language Models Through Cloud-Edge Collaboration.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration CE-CoLLM: Efficient and Adaptive Large Language Models Through Cloud-Edge Collaboration

Reference 16

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Observation c6e991f7-3307-4c1a-9155-e0b38881e6c1 · outbound

This paper cites Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache

Reference 17

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Observation e009fbe8-b573-4466-92ef-600fb12c5026 · outbound

This paper cites Zero: Memory optimizations toward training trillion parameter models,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Zero: Memory optimizations toward training trillion parameter models,

Reference 18

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Observation 6b6e9b1d-0818-485e-b782-db74ee69e692 · outbound

This paper cites LLM-Pruner: On the Structural Pruning of Large Language Models.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 19

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source=pdf_text observed=2026-08-07T15:42:21.943627Z digest=sha256:b646534ea45d49ca512b726ce8041b5a0e3f69d1b7d7c0b7d8e7f3910ccfccba

Observation c59d05b9-46f2-4c8f-9be7-de32966817b3 · outbound

This paper cites SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot

Reference 20

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source=pdf_text observed=2026-08-07T15:42:22.002271Z digest=sha256:4fc245e5a3ef3e319bb09f70ca7251ed349018740c12558fe614c9eb34bc38c8

Observation a5d6b63f-1400-4643-a2f9-df03bc2f9948 · outbound

This paper cites Cachegen: Kv cache compression and streaming for fast large language model serving,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Cachegen: Kv cache compression and streaming for fast large language model serving,

Reference 21

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source=pdf_text observed=2026-08-07T15:42:22.098511Z digest=sha256:8b175e901223b3fd432d39ce02f205924b22f771e74b8a88d58d5ecafdd2084a

Observation cb0bdeff-ff8b-439d-9382-c80aa88a7e44 · outbound

This paper cites KVSharer: Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration KVSharer: Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing

Reference 22

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source=pdf_text observed=2026-08-07T15:42:22.203859Z digest=sha256:af04e6c7dec3ca187e57a3de1c935791fa29ce7f0e9e565365f4453ff5b712e2

Observation 9f5775f5-be36-4c5c-9531-eba11776302d · outbound

This paper cites Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference

Reference 23

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Observation cfcd4484-3cb2-4f0a-8378-cbbd363a2109 · outbound

This paper cites Model tells you what to discard: Adaptive kv cache compression for llms,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Model tells you what to discard: Adaptive kv cache compression for llms,

Reference 24

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source=pdf_text observed=2026-08-07T15:42:22.355802Z digest=sha256:756d09d73694cf72fcab9f1cf77fc546e1a9d82b8ecbce4cd8b0ec6017e71824

Observation 6d872b2c-9fbb-48cc-aec1-fa9723b252f4 · outbound

This paper cites Netgpt: An ai-native network architecture for provisioning beyond personalized generative services,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Netgpt: An ai-native network architecture for provisioning beyond personalized generative services,

Reference 25

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

source=pdf_text observed=2026-08-07T15:42:22.452645Z digest=sha256:cd9c8cdf4f7d39c60ac11839666d516b66a0ed78a441dd4c1997aba7f7e5ad25

Observation a974abcd-187d-46b9-9315-854d348d651f · outbound

This paper cites Compute Or Load KV Cache? Why Not Both?.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Compute Or Load KV Cache? Why Not Both?

Reference 26

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source=pdf_text observed=2026-08-07T15:42:22.542928Z digest=sha256:3a6bc054fb720cacc7a8e8663b8ba770631e0dde414d8add5f968a3c445c36db

Observation d64e7a03-6e3a-4b0d-90ca-73cfd009e03b · outbound

This paper cites {OSCA}: An{Online-Model}based cache allocation scheme in cloud block storage systems,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration {OSCA}: An{Online-Model}based cache allocation scheme in cloud block storage systems,

Reference 27

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

source=pdf_text observed=2026-08-07T15:42:22.623389Z digest=sha256:f4c90e8f4d115f62064826042192ff067b53fbd1e29cf833b3468b880d592cce

Observation 9278466e-630c-4ef2-beb6-d14d133d7670 · outbound

This paper cites Similarity of neural network models: A survey of functional and representational measures,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Similarity of neural network models: A survey of functional and representational measures,

Reference 28

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source=pdf_text observed=2026-08-07T15:42:22.690741Z digest=sha256:70accc280c0f2d996c43ad31fd573925585ce390048739cc89d6dd9ed2de2ec7

Observation 2972a50a-33da-4f1c-a58f-be2f92ce2e4c · outbound

This paper cites ThinK: Thinner Key Cache by Query-Driven Pruning.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration ThinK: Thinner Key Cache by Query-Driven Pruning

Reference 30

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Observation 9f91f44f-fe55-4ee4-8225-5ed1061ea45e · outbound

This paper cites A Survey of Large Language Models.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration A Survey of Large Language Models

Reference 31

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source=pdf_text observed=2026-08-07T15:42:23.082239Z digest=sha256:a1154f1f027e9a9cf616ec57d2c20ff1983648f1d5bf6bce05b7e7357558e2f1

Observation f2d31dae-3178-4f20-bd3b-9b124471e737 · outbound

This paper cites Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

Reference 32

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source=pdf_text observed=2026-08-07T15:42:23.171221Z digest=sha256:852e8440b4b8040ee5056c6952366c307112ecb101f5b55e060fd1d897b0ce81

Observation e72d29dd-9468-4454-bdb9-2060b6317fcc · outbound

This paper cites Aligning ai with shared human values,.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Aligning ai with shared human values,

Reference 33

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

source=pdf_text observed=2026-08-07T15:42:23.272726Z digest=sha256:1722430f260404b9aa170c57128190d96fcc8feb96f02dc06e1640a97cb1bab6

Observation e423a7f1-e62a-48d2-961a-bf5cf2914e95 · outbound

This paper cites an unresolved cited work.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Unresolved cited work

Reference 35

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source=pdf_text observed=2026-08-07T15:42:23.380463Z digest=sha256:e4105935b2f0eaa102612d4fecf6a2ec010c634b6f219dac315b6100df4c40bc

Observation 3c155ec4-fc16-4007-a30a-75c7b896324c · outbound

This paper cites After applying an orthogonal trans- formation, it becomes: Oc =O eQ(26) whereQ T Q=I.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration After applying an orthogonal trans- formation, it becomes: Oc =O eQ(26) whereQ T Q=I

Reference 36

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raw_fallback, observed 2026-08-07T15:42:24.153525Z

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=2026-08-07T15:42:23.478704Z digest=sha256:93c6be90a3a3a42f8d17b8be8fdcba1841614e654cf91faf5d63e01faa97b775

Observation 6d10a037-0e94-40d0-9f0b-61708886f2f2 · outbound

This paper cites an unresolved cited work.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:42:23.976496Z

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=2026-08-07T15:42:23.582268Z digest=sha256:b9cee8e35ebb4c47c9b3d90c6be16fffe041e4ffc823e9724dfeeb85e1584cee

Observation 496173f2-1f8a-4559-8dc3-3e891f1321ef · outbound

This paper cites Similarity of Neural Network Representations Revisited.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration Similarity of Neural Network Representations Revisited

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:22.865614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:22.865614Z digest=sha256:c2934dea30f44cc431d680317c1f1ce432376e75186b4b5447c1227e86112c0a

Pith citing papers

No inbound Pith citation observations are available.