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Paper Citation Record · LEDGER

Energy Considerations of Large Language Model Inference and Efficiency Optimizations

As of 18 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 11 inbound Pith citation observations for arXiv:2504.17674.

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

pith.paper-citation-record.v1
2504.17674 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:37:51.568170Z

measured 76 of 76 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:57:00.675817Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T06:37:43.416980Z

Reference resolution

65 of 65 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved65
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b11a766-9a60-4f23-82a4-606bc0c5d8fc · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 1

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4e77e48c-9aee-46b1-bb8f-ccb511ac0416 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 2

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raw_fallback, observed 2026-08-16T10:37:52.931492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8e2838c2-bfbd-463a-8d55-e2a1a3813ba6 · outbound

This paper cites Qwen Technical Report.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Qwen Technical Report

Reference 3

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no resolver link, observed 2026-08-16T10:37:51.204327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.204327Z digest=sha256:0b1feb6801bf84762ca7691e555d376fbacc9c711a3362287f511b5446b00b4f

Observation 1223899b-5265-461f-8b25-3d2f63852213 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c51d8b24-9e74-4e4b-9533-e2cbd2b80174 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.214747Z digest=sha256:49ea0a620d06a434b15c65f15221db9dfdf3220747af724112e8ec28be441974

Observation d38d5350-6230-4471-a3c6-6fa50212eaed · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e256b8ca-44dc-40ec-9205-cc596e94def9 · outbound

This paper cites Accelerating Large Language Model Decoding with Speculative Sampling.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Accelerating Large Language Model Decoding with Speculative Sampling

Reference 7

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no resolver link, observed 2026-08-16T10:37:51.225134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.225134Z digest=sha256:bbbd2670700f22cd54b2a108bebac5d82f68b3b815055d3345479af7fc1bf0d8

Observation 54b405b9-9b62-4924-b4a7-9cb91b7cbec4 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 32c5c017-c5ac-4951-a5db-43c3de08bf60 · outbound

This paper cites de Araújo, JPW, and MinervaBooks.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations de Araújo, JPW, and MinervaBooks

Reference 9

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Observation 04130b19-0455-497d-a052-6792aa5599c4 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d116a99c-2cac-4b5a-b87f-9487b73d77cb · outbound

This paper cites The Llama 3 Herd of Models.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations The Llama 3 Herd of Models

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.245402Z digest=sha256:4e69a0e4fec45bc4b27519b110fea525bb409f3aa74f8b9380d773e56af32304

Observation 5d24d21b-8fac-411a-963c-74feaf08ad24 · outbound

This paper cites LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 12

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no resolver link, observed 2026-08-16T10:37:51.250427Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.250427Z digest=sha256:2694067c6d2ff0d52da57953efcec42f1ac050348a732a7e5bae04f5257a2b63

Observation ad032c4a-b4d4-4840-86d8-aec98535863d · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e3cc45a6-8a55-4618-8980-88d1b4550ddd · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 81cbc995-a199-4494-bbb0-f5133274e015 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f9abf2f3-037b-463c-b004-a8cbb61f4ea1 · outbound

This paper cites OLMo: Accelerating the Science of Language Models.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations OLMo: Accelerating the Science of Language Models

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.270039Z digest=sha256:901c46657cb940fb1ea1526d97e1dd90939a0fd71e50e61d6d5b292250c02adb

Observation c2c58e61-2e03-4a1b-a95d-5a4881451ca6 · outbound

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

Energy Considerations of Large Language Model Inference and Efficiency Optimizations DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.275014Z digest=sha256:05a153e8523371a6699897bc755bb4521c36e072ea529e573c5014f2a96182be

Observation 2992b518-f960-43c1-a34e-2916eac44544 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.279879Z digest=sha256:344bb504ae861ef371d2ed6a36b732ee1950c789c41983ef49444af6f84d33c8

Observation 954b0c55-78ac-4f15-b647-fc216ed783ee · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation bf6c3642-0186-4435-b55d-722f9b250a04 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation be9f0888-bd88-48e1-882d-5a2fb99002da · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Gonzalez, Hao Zhang, and Ion Stoica

Reference 21

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Observation 8675a9e0-df57-4648-99a1-73f40bc6d91f · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 22

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Unavailable: canonical work link unavailable.

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Observation 6973f555-fae5-4e10-be64-9477aef18535 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 23

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Unavailable: canonical work link unavailable.

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Observation 99382f6a-8077-4799-a04b-da5d4699418b · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d0ed7826-31d2-4fc5-9247-34b2ce360feb · outbound

This paper cites Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Models.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Models

Reference 25

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Unavailable: canonical work link unavailable.

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Observation 26cfb5fa-9094-4717-bf78-5938c65aca00 · outbound

This paper cites PyTorch Distributed: Experiences on Accelerating Data Parallel Training.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations PyTorch Distributed: Experiences on Accelerating Data Parallel Training

Reference 26

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Unavailable: canonical work link unavailable.

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Observation 9255cc71-70f5-4e28-ba1a-dc23c44dc0fa · outbound

This paper cites TurboSpec: Closed-loop Speculation Control System for Optimizing LLM Serving Goodput.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations TurboSpec: Closed-loop Speculation Control System for Optimizing LLM Serving Goodput

Reference 27

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no resolver link, observed 2026-08-16T10:37:51.323537Z

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Observation ff4c1276-3192-4dc6-bed2-b1e2c651afc0 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 28

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Unavailable: canonical work link unavailable.

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Observation b7f9f066-e762-421e-b017-dc783e5f70ce · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 044a4ebf-a0da-493a-9e5f-f3e66f45bc5e · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 30

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Unavailable: canonical work link unavailable.

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Observation cc9d7cf3-6dfc-43b7-9b2d-ad6a2c160db1 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.343909Z digest=sha256:5e022905e20a5676b4072efd7fa38aae8163638077836a3452f92369c7e1f859

Observation 8534a4c9-05b5-4373-8991-fa82c8880b8a · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 805a7873-0a36-4623-b98f-5202c7ba45e8 · outbound

This paper cites Pointer Sentinel Mixture Models.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Pointer Sentinel Mixture Models

Reference 33

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Observation 871b2b91-a251-43e6-a385-4685271997d0 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 17b8f8b0-8f19-4a3c-800e-b74552d87189 · outbound

This paper cites OLMoE: Open Mixture-of-Experts Language Models.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations OLMoE: Open Mixture-of-Experts Language Models

Reference 35

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Unavailable: canonical work link unavailable.

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Observation 45537fe5-2a19-4d01-83c1-e6743bb66560 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b28f9e3e-f5a7-4600-acae-c7c7518cdcaf · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:37:51.389183Z digest=sha256:4846b1a7e88c73c3001b45188b781cfd8b80bd8930a834a87295b2c0a99d9bae

Observation 52df6c16-fa65-4139-9d7d-7aa8bb4e8697 · outbound

This paper cites 2 OLMo 2 Furious.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations 2 OLMo 2 Furious

Reference 38

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Observation f76f9c8f-30c7-450a-b9a2-558e28cb79e7 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 39

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Observation 626f5afc-64cd-4d79-a383-4e6d9e50f576 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

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Observation 82d36212-7962-42f0-9ce7-5f1282cffbb4 · outbound

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

Energy Considerations of Large Language Model Inference and Efficiency Optimizations The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink

Reference 41

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Observation 8454e343-6748-4112-a869-be5b1beb2d8c · outbound

This paper cites Compressive Transformers for Long-Range Sequence Modelling.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Compressive Transformers for Long-Range Sequence Modelling

Reference 42

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Observation 19917793-a09e-4723-b2ca-4723ccb70d21 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 43

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

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Observation f3d010bb-ef7e-4cae-b33e-fadb1e525c06 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

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Observation 25e329f0-a30c-48b0-b978-3237bf50ac20 · outbound

This paper cites GreenLLM: Disaggregating Large Language Model Serving on Heterogeneous GPUs for Lower Carbon Emissions.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations GreenLLM: Disaggregating Large Language Model Serving on Heterogeneous GPUs for Lower Carbon Emissions

Reference 47

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Observation 34e1c5ae-9331-4a50-9291-96627a2b609b · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

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Observation 3ea540ae-db10-4a80-8b41-8bd7fbc78524 · outbound

This paper cites Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 49

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Observation 67e80f83-072d-4833-9ffc-22c05fa14d94 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

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Observation f9c141b9-e954-4c3a-8a74-1424f87f5c56 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

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Observation 1fececbd-cb76-49d0-9ded-93eb797639a9 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 52

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Observation 8ed1a345-b4ac-400f-bee9-f55e2e36dfd2 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations BurstGPT: A Real-world Workload Dataset to Optimize LLM Serving Systems

Reference 53

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Observation 6dc148d3-998d-4169-a3f7-22da7866c5e9 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 54

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Observation 48909894-0c2d-46a2-81d8-38c43579e8c1 · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 55

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Observation db9ba1f9-900a-4fbf-822e-772281dbc6ec · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 56

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Observation 3e5cb374-7a99-4411-9060-57e72f82072f · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unveiling Environmental Impacts of Large Language Model Serving: A Functional Unit View

Reference 57

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Observation d10d8f38-1c8e-4409-9fa1-b4e449552740 · outbound

This paper cites Qwen2.5 Technical Report.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Qwen2.5 Technical Report

Reference 58

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Observation bc4598db-2318-4da4-a862-bc41728c8bc3 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 59

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Observation df32f1a1-d235-4b96-8056-cb5af480227f · outbound

This paper cites an unresolved cited work.

Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 60

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Observation 41d99840-83e0-4835-b054-6c7b739d9f11 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations online" 'onlinestring :=

Reference 61

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Observation 354ccb25-6688-44b3-9f4d-dadfecf9cba4 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations write newline

Reference 62

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Observation 64e5d590-4dd2-48a5-9880-b9e1e2f4cd67 · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations @esa (Ref

Reference 63

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Observation e0958990-9d1a-43c7-88fd-aea00a0151ed · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Unresolved cited work

Reference 64

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Observation 23b25463-0995-4586-88d5-e9e69d0c94ac · outbound

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Energy Considerations of Large Language Model Inference and Efficiency Optimizations Prior benchmarking efforts have primarily focused on latency reduction in idealized settings, often overlooking the diverse real-world inference workloads that shape energy use

Reference 65

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Pith citing papers

Observation f6ef9b75-2a1c-41b8-abfb-c2d8948ced19 · inbound

Efficient Reasoning Through Suppression of Self-Affirmation Reflections in Large Reasoning Models cites this paper.

Efficient Reasoning Through Suppression of Self-Affirmation Reflections in Large Reasoning Models Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 9

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Observation 2659cf1c-2787-4e2f-b3c1-45c1bc773db3 · inbound

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SweetSpot: An Analytical Model for Predicting Energy Efficiency of LLM Inference Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 8

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Observation 1585c774-c5da-4d80-9733-b2db6a8435b2 · inbound

Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters cites this paper.

Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 23

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From Cradle to Cloud: A Life Cycle Review of AI's Environmental Footprint cites this paper.

From Cradle to Cloud: A Life Cycle Review of AI's Environmental Footprint Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 35

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Identifying unique developers in OSS projects: A family of models cites this paper.

Identifying unique developers in OSS projects: A family of models Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 125

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Observation fa3fb8af-56a6-4efd-961a-ea73c076ad4e · inbound

From Perception to Action: Can UI Interventions Foster Sustainable LLM Chatbot cites this paper.

From Perception to Action: Can UI Interventions Foster Sustainable LLM Chatbot Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 67

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SEFORA: Student Essays with Feedback Corpus and LLM Feedback Evaluation Framework Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 2

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arxiv_id, observed 2026-07-02T18:57:16.343774Z

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Observation 00b67796-1d1f-49f9-abfb-65b9b1e2ab04 · inbound

Lights, Camera, Carbon: Architectural Scaling Laws for Video Generation Energy Consumption cites this paper.

Lights, Camera, Carbon: Architectural Scaling Laws for Video Generation Energy Consumption Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 7

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Observation c2a4c417-3b9e-4945-a8d9-79410dab9447 · inbound

Attention to Detail: Evaluating Energy, Performance, and Accuracy Trade-offs Across vLLM Configurations cites this paper.

Attention to Detail: Evaluating Energy, Performance, and Accuracy Trade-offs Across vLLM Configurations Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 36

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Observation 0d5f2d1e-6e17-471a-a9aa-c581c8b6c019 · inbound

Attention to Detail: Evaluating Energy, Performance, and Accuracy Trade-offs Across vLLM Configurations cites this paper.

Attention to Detail: Evaluating Energy, Performance, and Accuracy Trade-offs Across vLLM Configurations Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 36

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Observation 864d0f73-d741-404a-a78c-ab3b0ebe7e00 · inbound

Unified Static-Dynamic Pruning for Efficient LLM Inference cites this paper.

Unified Static-Dynamic Pruning for Efficient LLM Inference Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Reference 17

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