Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2405.08707.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:59:52.240108Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T15:59:56.405469Z
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 d4744f33-043d-4ad0-b297-e92d696d6a8e · inbound
Simplifying CLIP: Unleashing the Power of Large-Scale Models on Consumer-level Computers cites this paper.
Simplifying CLIP: Unleashing the Power of Large-Scale Models on Consumer-level Computers Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:59:52.240108Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a44a1e5-8713-4a25-9544-de4538893053 · inbound
Optimizing Sequential Recommendation Models with Scaling Laws and Approximate Entropy cites this paper.
Optimizing Sequential Recommendation Models with Scaling Laws and Approximate Entropy Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:29:21.888575Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56fbc392-ca6f-4a85-b541-5fa00209cb83 · inbound
Efficient Prompt Compression with Evaluator Heads for Long-Context Transformer Inference cites this paper.
Efficient Prompt Compression with Evaluator Heads for Long-Context Transformer Inference Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:40:36.729578Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 15874c08-c7c6-4825-8fa7-1b05e307d5b1 · inbound
Enhancing Speech Instruction Understanding and Disambiguation in Robotics via Speech Prosody cites this paper.
Enhancing Speech Instruction Understanding and Disambiguation in Robotics via Speech Prosody Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:56:43.117825Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e2b7cb81-fb9d-453a-8e0a-1649555cd395 · inbound
NeuralDB: Scaling Knowledge Editing in LLMs to 100,000 Facts with Neural KV Database cites this paper.
NeuralDB: Scaling Knowledge Editing in LLMs to 100,000 Facts with Neural KV Database Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:44:15.890696Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e6db65c-722e-431c-98c8-3f492389c988 · inbound
Forget BIT, It is All about TOKEN: Towards Semantic Information Theory for LLMs cites this paper.
Forget BIT, It is All about TOKEN: Towards Semantic Information Theory for LLMs Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 99
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T01:55:38.186637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 20b4cccf-58c8-429b-9253-739817431750 · inbound
Unifying Learning Dynamics and Generalization in Transformers Scaling Law cites this paper.
Unifying Learning Dynamics and Generalization in Transformers Scaling Law Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T14:02:56.712450Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4549467c-1423-45a3-9fc4-889807fe7418 · inbound
On the Non-decoupling of Supervised Fine-tuning and Reinforcement Learning in Post-training cites this paper.
On the Non-decoupling of Supervised Fine-tuning and Reinforcement Learning in Post-training Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T14:48:00.519812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e467aabd-c50a-4ab0-bcd1-6546f1112ff0 · inbound
Active Adversarial Perturbation-driven Associative Memory Retrieval for RGB-Event Visual Object Tracking cites this paper.
Active Adversarial Perturbation-driven Associative Memory Retrieval for RGB-Event Visual Object Tracking Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T15:59:56.410113Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.