Paper Citation Record · LEDGER

Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2404.07647.

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

pith.paper-citation-record.v1
2404.07647 v1

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 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:33:35.873061Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T02:30:32.237611Z

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 52cbf95b-fe71-4410-93b3-355dcd598466 · inbound

EasyMath: A 0-shot Math Benchmark for SLMs cites this paper.

EasyMath: A 0-shot Math Benchmark for SLMs Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:33:35.873061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2988fb8e-629f-48d4-ace9-b76f3659ff9c · inbound

Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning cites this paper.

Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:20.382188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5827bea8-e2f5-4fc0-ac50-f3017293fa59 · inbound

Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training cites this paper.

Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T11:59:52.185886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 944e1033-3b30-446b-bc66-2e6868d061fa · inbound

When Less is More: The LLM Scaling Paradox in Context Compression cites this paper.

When Less is More: The LLM Scaling Paradox in Context Compression Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-16T02:30:32.241335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.