Paper Citation Record · LEDGER

LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2309.14393.

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

pith.paper-citation-record.v1
2309.14393 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:44:35.312020Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:05:46.397672Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a15d8e24-8217-467a-a609-7ddcea6ce950 · inbound

A Survey on Inference Optimization Techniques for Mixture of Experts Models cites this paper.

A Survey on Inference Optimization Techniques for Mixture of Experts Models LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T12:44:35.312020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9125468c-e7c1-4885-9058-4f5117d0375f · inbound

Reconsidering SMT Over NMT for Closely Related Languages: A Case Study of Persian-Hindi Pair cites this paper.

Reconsidering SMT Over NMT for Closely Related Languages: A Case Study of Persian-Hindi Pair LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T06:05:22.484005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4609b7f-ef20-40a8-b744-6d955531a3d6 · inbound

Kryptonite-N: Machine Learning Strikes Back cites this paper.

Kryptonite-N: Machine Learning Strikes Back LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:58.455697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a1a8008-7d32-4133-b4a0-8f1b1a9da2c1 · inbound

CarbonChat: Large Language Model-Based Corporate Carbon Emission Analysis and Climate Knowledge Q&A System cites this paper.

CarbonChat: Large Language Model-Based Corporate Carbon Emission Analysis and Climate Knowledge Q&A System LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T22:26:09.670814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6552209-cf6c-4d1f-b669-10733f97f800 · inbound

Addressing the sustainable AI trilemma: a case study on LLM agents and RAG cites this paper.

Addressing the sustainable AI trilemma: a case study on LLM agents and RAG LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:34.649220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25ecc27b-c722-40d3-9bf6-17e83cfff42d · inbound

Exploring the sustainable scaling of AI dilemma: A projective study of corporations' AI environmental impacts cites this paper.

Exploring the sustainable scaling of AI dilemma: A projective study of corporations' AI environmental impacts LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T15:20:32.458780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2242299-863c-4b8f-b325-9094d10aaffa · inbound

EcoServe: Designing Carbon-Aware AI Inference Systems cites this paper.

EcoServe: Designing Carbon-Aware AI Inference Systems LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T20:31:35.646240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3648170-c39c-42d9-83d0-d7e1bd67d9d6 · inbound

Beyond Vision: How Large Language Models Interpret Facial Expressions from Valence-Arousal Values cites this paper.

Beyond Vision: How Large Language Models Interpret Facial Expressions from Valence-Arousal Values LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T19:06:48.569516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56481f6f-420f-4eaf-92e6-e5b9f9095cea · inbound

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

Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-23T00:07:17.290521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 54d9b4db-9fb7-4734-9ae9-fff583816ab7 · inbound

Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time cites this paper.

Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T12:44:19.930035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfaf3d68-9e6d-41b0-9a53-a672eee2a5ab · inbound

Scaling Fine-Grained MoE Beyond 50B Parameters: Empirical Evaluation and Practical Insights cites this paper.

Scaling Fine-Grained MoE Beyond 50B Parameters: Empirical Evaluation and Practical Insights LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:18:58.457714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10e97ba5-576b-4db9-a67b-8cf8d15ea5e3 · inbound

Calculating Software's Energy Use and Carbon Emissions: A Survey of the State of Art, Challenges, and the Way Ahead cites this paper.

Calculating Software's Energy Use and Carbon Emissions: A Survey of the State of Art, Challenges, and the Way Ahead LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T04:47:06.691656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac81000c-57ba-4351-80f4-f706671c9d8e · inbound

Analysis of Propaganda in Tweets From Politically Biased Sources cites this paper.

Analysis of Propaganda in Tweets From Politically Biased Sources LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 5646

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:56.991783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dc804c7-5911-4df3-b883-304ed3fc2922 · inbound

CEO-DC: Driving Decarbonization in HPC Data Centers with Actionable Insights cites this paper.

CEO-DC: Driving Decarbonization in HPC Data Centers with Actionable Insights LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T18:18:48.139078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1ca63f3-9cf2-48ad-9a5f-db29b2da5bc2 · inbound

Performance is not All You Need: Sustainability Considerations for Algorithms cites this paper.

Performance is not All You Need: Sustainability Considerations for Algorithms LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T17:03:25.827775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6820ef8-acea-4a44-a257-838dfffb1b0a · inbound

Throttling Web Agents Using Reasoning Gates cites this paper.

Throttling Web Agents Using Reasoning Gates LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T12:28:03.894314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73339394-2495-4107-8c13-703eba13a886 · inbound

EnergyLens: Predictive Energy-Aware Exploration for Multi-GPU LLM Inference Optimization cites this paper.

EnergyLens: Predictive Energy-Aware Exploration for Multi-GPU LLM Inference Optimization LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:48:33.269930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 16c3cf6f-1063-43c1-9ef1-420e9bcfee41 · inbound

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations cites this paper.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:09:07.316240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 068ef811-52b6-40fc-b4a9-fa0082f8014f · inbound

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations cites this paper.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.399550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.