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Paper Citation Record · LEDGER

Regress, Don't Guess -- A Regression-like Loss on Number Tokens for Language Models

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.02083.

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

pith.paper-citation-record.v1
2411.02083 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:25:16.718816Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:32:10.082928Z

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 ee388ee7-08d7-4cf7-bbc2-fa0678e607e6 · inbound

multivariateGPT: a decoder-only transformer for multivariate categorical and numeric data cites this paper.

multivariateGPT: a decoder-only transformer for multivariate categorical and numeric data Regress, Don't Guess -- A Regression-like Loss on Number Tokens for Language Models

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:32:10.166975Z

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.

source=pdf_text observed=2026-08-07T13:32:09.507776Z digest=sha256:9d1cb56df613e1d7cb87034df4d2465dd8264aefe73d27bbd3e91e74bd8e7064

Observation 2b4744cc-8ca7-41c5-895d-16b0941fb551 · inbound

Every Token Counts: Exact Likert-Scale Distributions for Measuring LLM Attitudes and Biases cites this paper.

Every Token Counts: Exact Likert-Scale Distributions for Measuring LLM Attitudes and Biases Regress, Don't Guess -- A Regression-like Loss on Number Tokens for Language Models

Reference 104

Resolution
unresolved
no resolver link, observed 2026-08-15T14:25:16.718816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:25:16.718816Z digest=sha256:339ee70a5ce409ed1bd05b73c517ee2b88dd73f8c34f93bc2c35a3f1e4a2c937