Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Approximating Human-Like Few-shot Learning with GPT-based Compression
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2308.06942.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T18:10:38.469335Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T21:07:24.266151Z
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 2622712f-2b98-4fdc-86e8-dd23b0caa542 · inbound
Assessing GPT Model Uncertainty in Mathematical OCR Tasks via Entropy Analysis cites this paper.
Assessing GPT Model Uncertainty in Mathematical OCR Tasks via Entropy Analysis Approximating Human-Like Few-shot Learning with GPT-based Compression
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T04:42:00.316430Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12f35475-5220-4b10-80d6-3b8a818eec82 · inbound
An Enhanced Text Compression Approach Using Transformer-based Language Models cites this paper.
An Enhanced Text Compression Approach Using Transformer-based Language Models Approximating Human-Like Few-shot Learning with GPT-based Compression
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:25:04.611313Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd6de8bf-36c4-4663-8fe8-5735151ce747 · inbound
Separate Source Channel Coding Is Still What You Need: An LLM-based Rethinking cites this paper.
Separate Source Channel Coding Is Still What You Need: An LLM-based Rethinking Approximating Human-Like Few-shot Learning with GPT-based Compression
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:43:04.462387Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16b0d7c0-e76d-49a5-ba42-de2be13d177a · inbound
EDPC: Accelerating Lossless Compression via Lightweight Probability Models and Decoupled Parallel Dataflow cites this paper.
EDPC: Accelerating Lossless Compression via Lightweight Probability Models and Decoupled Parallel Dataflow Approximating Human-Like Few-shot Learning with GPT-based Compression
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T18:10:38.469335Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8c34b9f-975f-4bb5-ba7d-ae7e697511f7 · inbound
TextEconomizer: Enhancing Lossy Text Compression with Denoising Transformers and Entropy Coding cites this paper.
TextEconomizer: Enhancing Lossy Text Compression with Denoising Transformers and Entropy Coding Approximating Human-Like Few-shot Learning with GPT-based Compression
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T21:07:24.267708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.