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Paper Citation Record · LEDGER

OmniPred: Language Models as Universal Regressors

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.14547.

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

pith.paper-citation-record.v1
2402.14547 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:05:04.185225Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T00:52:55.841243Z

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 5150d67e-f306-44d3-9835-f355b6abc003 · inbound

Understanding LLM Embeddings for Regression cites this paper.

Understanding LLM Embeddings for Regression OmniPred: Language Models as Universal Regressors

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-12T15:05:04.185225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T15:05:04.185225Z digest=sha256:b60a2aec8bef286e46ea85932361a7ca2c2a2b5018480e3a0a8812b0f9cac5e8

Observation 03c28c55-d67e-4301-a7de-b6f16fe9c9d5 · inbound

Decoding-based Regression cites this paper.

Decoding-based Regression OmniPred: Language Models as Universal Regressors

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-09T20:34:01.617785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:34:01.617785Z digest=sha256:dc5daeb72d417e848b7c77e79c8bbab028a753fc6ef188866d09c691a161efc7

Observation 4c092f70-5544-4a5d-8b58-2a7377cac9ba · inbound

Quantile Regression with Large Language Models for Price Prediction cites this paper.

Quantile Regression with Large Language Models for Price Prediction OmniPred: Language Models as Universal Regressors

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T05:58:20.365065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:58:20.365065Z digest=sha256:4be1cfae770178ed8c2f133b7d7671e77de5f228eff3ed16c354267012eb59d2

Observation 0a611526-1f0c-4c9c-a342-f71d0620c924 · inbound

Performance Prediction for Large Systems via Text-to-Text Regression cites this paper.

Performance Prediction for Large Systems via Text-to-Text Regression OmniPred: Language Models as Universal Regressors

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T22:29:59.037171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:29:59.037171Z digest=sha256:9a1dfedd1d0d4fec4fa11f437943aba054b362a3abf2caddeacc951d0b4746a7

Observation c30ed659-8376-4c9e-91fe-d72d5c4821e0 · inbound

Distribution-Aware Reward: Reinforcement Learning over Predictive Distributions for LLM Regression cites this paper.

Distribution-Aware Reward: Reinforcement Learning over Predictive Distributions for LLM Regression OmniPred: Language Models as Universal Regressors

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:04:01.616111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-21T07:01:15.729873Z digest=sha256:0b41be6936c426de6df6eb1826a5eb742a5cd89ce5734312e153c70ea6ff11be

Observation 3c210396-6cc0-43e0-a4de-d77991d7f2f0 · inbound

Large language model for unified and accurate description of multidimensional nuclear properties cites this paper.

Large language model for unified and accurate description of multidimensional nuclear properties OmniPred: Language Models as Universal Regressors

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-06-29T00:52:55.842931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-29T00:44:36.381382Z digest=sha256:7ee3c10cf653b1eb103e3bb02158cb462f9f093625649a27ef85ab673d6c19b2