Paper Citation Record · LEDGER

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures

As of 11 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2607.08511.

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

pith.paper-citation-record.v1
2607.08511 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T06:13:42.239715Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

verified exact7
verified fuzzy6
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e0bc5e2-f620-47c3-b4c9-e0df0e144299 · outbound

This paper cites LEMUR Neural Network Dataset: Towards Seamless AutoML.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures LEMUR Neural Network Dataset: Towards Seamless AutoML

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-10T06:16:51.284448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9222bb8a-e983-41f0-b938-f2163c3c0991 · outbound

This paper cites Resource- efficient iterative LLM-based NAS with feedback memory.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures Resource- efficient iterative LLM-based NAS with feedback memory

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-10T06:16:51.277647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation aa9d8606-5c86-4f2f-afcf-389841dd6bf0 · outbound

This paper cites U., et al.: AI on the Edge: An Automated Pipeline for PyTorch- to-Android Deployment and Benchmarking, Preprints, Nov.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures U., et al.: AI on the Edge: An Automated Pipeline for PyTorch- to-Android Deployment and Benchmarking, Preprints, Nov

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-10T06:16:51.141612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8a3d7a53-1588-4644-8c2b-a63c920dd971 · outbound

This paper cites A Retrieval-Augmented Generation Approach to Extracting Algorithmic Logic from Neural Networks.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures A Retrieval-Augmented Generation Approach to Extracting Algorithmic Logic from Neural Networks

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-10T06:16:51.284693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 258c4376-0a80-4d22-8aed-bf33438ae5c8 · outbound

This paper cites From Memorization to Creativity: LLM as a Designer of Novel Neural Architectures.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures From Memorization to Creativity: LLM as a Designer of Novel Neural Architectures

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-07-10T06:16:51.287237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3c84832c-b6dd-4a39-af23-a144a25c86c8 · outbound

This paper cites an unresolved cited work.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-07-10T06:16:51.584864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0a790245-7afb-417d-80b9-d4bacbd418d3 · outbound

This paper cites NNGPT: Rethinking AutoML with large language models.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures NNGPT: Rethinking AutoML with large language models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T06:16:51.579853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5e1ce5fb-3b76-4520-ba9e-ba8b155b7402 · outbound

This paper cites Learning multiple layers of features from tiny images.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures Learning multiple layers of features from tiny images

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T06:16:51.578645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation acdfdddc-c2a7-4df2-bc7b-a5e2a3a98fb9 · outbound

This paper cites SGDR: Stochastic gradi- ent descent with warm restarts.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures SGDR: Stochastic gradi- ent descent with warm restarts

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T06:16:51.580611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a5741d06-0359-48a9-bcda-314875a0123e · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures PyTorch: An imperative style, high-performance deep learning library

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T06:16:51.577942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ed2080dc-8f6f-4ede-8ca9-bebfbfc667a9 · outbound

This paper cites From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-08-06T02:01:35.592368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9cabe1eb-2f72-485f-b4a3-150280e46d62 · outbound

This paper cites Smith and Nicholay Topin.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures Smith and Nicholay Topin

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T06:16:51.582826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ba5718df-4e4e-41eb-b714-c4846d151317 · outbound

This paper cites LEMUR 2: Unlocking neural net- work diversity for AI.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures LEMUR 2: Unlocking neural net- work diversity for AI

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T06:16:51.586860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fea7a0e3-a07a-4f17-b680-03d51674f089 · outbound

This paper cites Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design.

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-10T06:16:51.287756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

No inbound Pith citation observations are available.