Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
EcoServe: Designing Carbon-Aware AI Inference Systems
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2502.05043.
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 2026-08-07T13:00:31.049555Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T02:29:23.910827Z
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 a221b0bb-7cbd-4dd3-a0c6-6230172bd29c · inbound
Cache Your Prompt When It's Green: Carbon-Aware Caching for Large Language Model Serving cites this paper.
Cache Your Prompt When It's Green: Carbon-Aware Caching for Large Language Model Serving EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T13:17:18.481714Z
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.
Observation b30c03c7-b037-462b-9eb6-cf84d54574c4 · inbound
A Vertical Approach to Designing and Managing Sustainable Heterogeneous Edge Data Centers cites this paper.
A Vertical Approach to Designing and Managing Sustainable Heterogeneous Edge Data Centers EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:39:51.789183Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 82f19ffe-d45d-4e31-85bd-68f6e37ec33f · inbound
Quantifying the Energy Consumption and Carbon Emissions of LLM Inference via Simulations cites this paper.
Quantifying the Energy Consumption and Carbon Emissions of LLM Inference via Simulations EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:14:19.340515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d059cc4-2e94-4531-99cd-cdd635e7bd5a · inbound
Energy-Aware Routing to Large Reasoning Models cites this paper.
Energy-Aware Routing to Large Reasoning Models EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T20:33:24.067155Z
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.
Observation 17772232-0efe-498c-bbca-73b5f9903dc5 · inbound
Determinism-Preserving GPU Spatial Sharing with Vitamin-E cites this paper.
Determinism-Preserving GPU Spatial Sharing with Vitamin-E EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T10:35:27.451461Z
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.
Observation 4b3fa359-f733-408f-a592-3a99a681350a · inbound
KAIROS: Stateful, Context-Aware Power-Efficient Agentic Inference Serving cites this paper.
KAIROS: Stateful, Context-Aware Power-Efficient Agentic Inference Serving EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 35
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T07:01:49.268219Z
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.
Observation 56a3eec0-b810-486d-a4d0-121555eb1b26 · inbound
AI Inference as Relocatable Electricity Demand: A Latency-Constrained Energy-Geography Framework cites this paper.
AI Inference as Relocatable Electricity Demand: A Latency-Constrained Energy-Geography Framework EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:16:27.539416Z
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.
Observation 3a610215-e230-4df3-94fb-89a2abfccace · inbound
GAR: Carbon-Aware Routing for LLM Inference via Constrained Optimization cites this paper.
GAR: Carbon-Aware Routing for LLM Inference via Constrained Optimization EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T01:42:03.824803Z
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.
Observation 7add184a-0b97-44e2-a689-9a212e1b5ab1 · inbound
Greening AI Inference with Accuracy and Latency-aware User Incentives cites this paper.
Greening AI Inference with Accuracy and Latency-aware User Incentives EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T19:03:51.120052Z
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.
Observation 0e97ce1d-504d-45a5-a563-baa7ac002d77 · inbound
Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment cites this paper.
Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 67
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-01T21:06:14.616536Z
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.
Observation 1e29a8b2-ef1e-477e-bdff-e3c98be45dd3 · inbound
From Tokens to Energy Flexibility: Quantization-Enabled Demand Response for Data Centers with LLM Inference Workloads cites this paper.
From Tokens to Energy Flexibility: Quantization-Enabled Demand Response for Data Centers with LLM Inference Workloads EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T02:29:23.912557Z
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.
Observation 3df9d850-6d9c-429a-bdf5-608747014a6b · inbound
Enabling Spatially Fine-Grained DVFS in Neural Processing Units for Energy-Efficient LLM Serving cites this paper.
Enabling Spatially Fine-Grained DVFS in Neural Processing Units for Energy-Efficient LLM Serving EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T20:57:21.540286Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c58e9d3b-f534-4daf-afa9-1372a189abb5 · inbound
Routing LLM Inference to the Cleanest Grid in Real Time cites this paper.
Routing LLM Inference to the Cleanest Grid in Real Time EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:00:30.958563Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb7ba158-1ba9-450c-8a7b-44929659aa1d · inbound
Routing LLM Inference to the Cleanest Grid in Real Time cites this paper.
Routing LLM Inference to the Cleanest Grid in Real Time EcoServe: Designing Carbon-Aware AI Inference Systems
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:00:31.049555Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.