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Paper Citation Record · LEDGER

Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2403.20306.

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

pith.paper-citation-record.v1
2403.20306 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 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 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:17:13.163081Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

14
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e3d92b6a-829f-4c09-bf1f-1f409d75f19f · inbound

Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference cites this paper.

Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-23T00:07:17.277444Z

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=2026-05-23T00:05:26.205947Z digest=sha256:03d6a45de40589c0c1c398efb153de6c377aeeb12ea32103aa9cad6ff649d8b4

Observation 22d5c83e-5765-4de7-84be-7ec87f3ab893 · inbound

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation cites this paper.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.163081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.163081Z digest=sha256:3e599eb29026c67098e5ed1f6d452db47534c1dc38d4343114b78b4aaf056dd6

Observation 185606c2-2e66-478f-9002-527e1ca63e75 · inbound

GPTFootprint: Increasing Consumer Awareness of the Environmental Impacts of LLMs cites this paper.

GPTFootprint: Increasing Consumer Awareness of the Environmental Impacts of LLMs Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T12:38:22.120089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:38:22.120089Z digest=sha256:1755ab6b2a5f5d066f8166673a994db8f1a9c9cb0df53a35e0febec4a33e129b

Observation 0c823151-99af-4d27-9d87-0b6c60cb9593 · inbound

Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques cites this paper.

Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T05:56:56.758394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:56:56.758394Z digest=sha256:42721ca81ffea1605d06ebebad8c8b96a28f8a6c30e9f2ab795f335ce4d0428b

Observation 0e2288a8-c6bb-474d-80dc-8905e470c649 · inbound

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? cites this paper.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T23:19:15.550305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:15.550305Z digest=sha256:542dc6b945b69377bc2e5f3288af339b9f3d1b72112d1460ae87da2c8a7c162b

Observation f4c4b411-9f86-454a-9e7b-f6d4351ab1d0 · inbound

ELASTIC: Event-Tracking Data Synchronization in Soccer Without Annotated Event Locations cites this paper.

ELASTIC: Event-Tracking Data Synchronization in Soccer Without Annotated Event Locations Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 124

Resolution
unresolved
no resolver link, observed 2026-08-05T21:22:48.601696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:22:48.601696Z digest=sha256:afcd2ab8637aa1abba293b7a6cf4e804f22bca154b4bbf2121ba2fad8c13f845

Observation 39468f77-3527-424c-abac-d29ed106152d · inbound

SweetSpot: An Analytical Model for Predicting Energy Efficiency of LLM Inference cites this paper.

SweetSpot: An Analytical Model for Predicting Energy Efficiency of LLM Inference Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T07:07:29.554851Z

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=2026-05-16T07:05:56.380048Z digest=sha256:405432fe88a9f14a50b3954b91f89389c570d1aa6f33113aec01fa213373bf6b

Observation 2b461277-0916-4e8e-b42a-6fe31eb07a90 · inbound

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

Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-16T06:47:28.113992Z

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=2026-05-16T06:44:47.160905Z digest=sha256:f465333ac5df5a219b9b70e73ca486cb261bd5782ae4680335f3e7daf695cb35

Observation b1e059e6-0869-487d-a889-22762a4eabd1 · inbound

DualScale: Energy-Efficient Disaggregated LLM Serving via Phase-Aware Placement and DVFS cites this paper.

DualScale: Energy-Efficient Disaggregated LLM Serving via Phase-Aware Placement and DVFS Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:56:37.089687Z

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=2026-05-15T20:54:30.486885Z digest=sha256:26ffc276a5fc41a632b0d6cecd3bba517e6076823fb9b5248e3c763e2ead0869

Observation 5db92d6b-9ae0-4b2b-a943-2257b5063436 · inbound

Workload composition smooths aggregate power demand while sustaining short-horizon ramps in AI data centers cites this paper.

Workload composition smooths aggregate power demand while sustaining short-horizon ramps in AI data centers Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T15:45:34.267198Z

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=2026-05-10T15:41:17.648005Z digest=sha256:6e899a6249e7d52467d3b1037c4d4fcb8f83a989b84aba82c32d562d8b7aa392

Observation 62f8d904-7050-4dd1-a6ec-aec954595f44 · inbound

KAIROS: Stateful, Context-Aware Power-Efficient Agentic Inference Serving cites this paper.

KAIROS: Stateful, Context-Aware Power-Efficient Agentic Inference Serving Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-10T07:01:48.809796Z

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=2026-05-10T06:58:36.525442Z digest=sha256:061bcdb5c9fb5da5360b1c49cd2f4dc7cca30695dc10c02c18e498aeed135880

Observation e9d41b09-26f6-443f-a48d-3e041b7319a7 · inbound

Experimentation for Different Scheduling Policies on Queues: Mixed Differences-in-Q Estimators Based on Little's Law cites this paper.

Experimentation for Different Scheduling Policies on Queues: Mixed Differences-in-Q Estimators Based on Little's Law Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T15:03:32.051612Z

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=2026-06-29T05:54:24.873991Z digest=sha256:f44f575569300bd85f0f50a90ca7f02cfb112859bd074bf835801aa76e1458e1

Observation 28ef1078-4945-4c64-8e32-9b64477edae1 · inbound

EnerInfer: Energy-Aware On-Device LLM Inference cites this paper.

EnerInfer: Energy-Aware On-Device LLM Inference Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-07-04T11:29:50.718879Z

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=2026-06-26T07:58:29.150228Z digest=sha256:a1260cc7cea99014192dda19990d139513fdeb8a7bb3180383961fc983c95b5d

Observation 21c727fc-12ef-4cbf-9deb-10df179c927e · 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 Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-13T04:56:20.002453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T04:56:20.002453Z digest=sha256:4e749481ad754c05ae3e87b1e5206147bf307644a58740d28e3be73093175fcf

Observation e84fa8ce-3691-4ea7-a872-37035d935269 · 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 Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-02T07:43:17.516763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:43:17.516763Z digest=sha256:160e212270bf2009430d14fda800bdb3a1f64e9d576dae8be965b1dcae6997e8

Observation 7c39d644-88c3-475f-8410-d9ef367d75cc · inbound

Energy-Efficient LLM Serving via Disaggregated Attention--FFN and Flexible Frequency Scaling cites this paper.

Energy-Efficient LLM Serving via Disaggregated Attention--FFN and Flexible Frequency Scaling Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-04T18:49:25.678359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:49:25.678359Z digest=sha256:2a6675257039b135fe490995b3d1e178e7a6f15408c3b961703646a311e3dd73