Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2502.05610.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:09:10.858236Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T17:57:20.957533Z
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 88e9f866-b5f3-476b-b572-4990d596d58b · inbound
Brevity is the soul of sustainability: Characterizing LLM response lengths cites this paper.
Brevity is the soul of sustainability: Characterizing LLM response lengths Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:09:10.858236Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8cad7eeb-5ca4-4480-80b8-11fe11d6f9f9 · inbound
A Multi-Pass Large Language Model Framework for Precise and Efficient Radiology Report Error Detection cites this paper.
A Multi-Pass Large Language Model Framework for Precise and Efficient Radiology Report Error Detection Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:00:15.171494Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16d56041-8beb-4955-ba7d-6a3b0c889926 · inbound
SLM-Bench: A Comprehensive Benchmark of Small Language Models on Environmental Impacts--Extended Version cites this paper.
SLM-Bench: A Comprehensive Benchmark of Small Language Models on Environmental Impacts--Extended Version Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T17:57:21.013217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.