Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-30T08:59:51.104895Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2606.28847.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-30T08:59:51.104895Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
15 of 15 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation a9be8160-7b2b-4ed2-9046-26d4fa8380a8 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model A vision of 6G wireless systems: Applications, trends, technologies, and open research problems
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e5174c46-496a-4d32-ba90-eb01d4bc14dd · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model AI-based time-, frequency-, and space-domain channel extrapolation for 6G: Opportuni- ties and challenges,
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6c1f767d-3022-4662-99ec-233eea6cee4e · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Scaling Laws for Neural Language Models
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a2903d7c-b9ca-4012-b6a7-128915453a61 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model WiFo: Wireless foundation model for channel prediction
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a8670099-f4ba-4b85-9415-e891e72760c0 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model HeterCSI: Channel-adaptive heterogeneous CSI pretraining framework for gener- alized wireless foundation models
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1980e851-c913-45c7-bb91-d3b2301008e7 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Unresolved cited work
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f258cd7d-51af-446b-9f35-80f9b3792ee1 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Large language models for wireless communications: From adaptation to autonomy,
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7b41af75-1805-41f7-82ed-73dc5b0d1d74 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Study on channel model for frequencies from 0.5 to 100 GHz,
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ca682991-cb6c-44db-9a88-91fa0b9dc43d · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Qwen3 Technical Report
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d9673f25-e4b0-4fdd-8dc7-4c8382fce072 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Attention is all you need
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f7a5be85-e674-457b-ad5b-c5604b323f04 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Deep learning for fading channel prediction,
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b834eb01-35da-45a2-968b-91d82c2185b7 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Informer: Beyond efficient transformer for long sequence time-series forecasting,
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f10d2590-d7e4-4675-8e24-7de569537e8e · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model WAIR-D: Wireless AI Research Dataset
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b739ffa8-129d-408c-9eb2-2b37626c942d · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b0da655f-82b8-450d-89b0-15f68d0da200 · outbound
Physics Equivariance for Robust Generalization in Wireless Foundation Model Massive MIMO channels with inter-user angle correlation: Open-access dataset, analysis and measurement-based validation,
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
No inbound Pith citation observations are available.