Paper Citation Record · LEDGER

Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.02616.

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

pith.paper-citation-record.v1
2406.02616 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T19:21:36.380653Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:49:44.099745Z

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 6410cd9d-fef6-41ee-8347-2c38598d79ec · inbound

Joint Partitioning and Placement of Foundation Models for Real-Time Edge AI cites this paper.

Joint Partitioning and Placement of Foundation Models for Real-Time Edge AI Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T19:21:36.380653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9edf613d-80bf-4e22-b66e-51a1ab613673 · inbound

WISP: Waste- and Interference-Suppressed Distributed Speculative LLM Serving at the Edge via Dynamic Drafting and SLO-Aware Batching cites this paper.

WISP: Waste- and Interference-Suppressed Distributed Speculative LLM Serving at the Edge via Dynamic Drafting and SLO-Aware Batching Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-16T14:12:58.630175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 84b7439d-9584-41fa-a3f6-8dca8f42c4fa · inbound

What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference cites this paper.

What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:45:20.560535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d0f918b8-7816-4716-9d2f-6dc5cac19928 · inbound

Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing cites this paper.

Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:49:44.101262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.