Paper Citation Record · LEDGER

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models

As of 10 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2510.19698.

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

pith.paper-citation-record.v1
2510.19698 v3

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:39:46.035913Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy0
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6480431e-de19-44ff-8861-94dfc96d6ce5 · outbound

This paper cites Agentichypothesis: A survey on hypothesis generation using llm systems.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Agentichypothesis: A survey on hypothesis generation using llm systems

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:42.658929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9882d552-1731-4d4f-bc22-289a4a67b666 · outbound

This paper cites Generalisation through negation and predicate invention.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Generalisation through negation and predicate invention

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:42.767958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd7d4a8b-4699-454a-aa57-2569ded429b1 · outbound

This paper cites Fast effective rule induction.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Fast effective rule induction

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:42.857517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7039c65f-6076-4c23-8a09-944baea6f04c · outbound

This paper cites Learning programs by learning from failures.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Learning programs by learning from failures

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:42.974358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0aba7b1-8402-4c14-b827-c7b927989874 · outbound

This paper cites Inductive logic programming at 30.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Inductive logic programming at 30

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:43.126951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acebc130-2544-4462-b76d-37c8cb4da446 · outbound

This paper cites Human-like few-shot learning via bayesian reasoning over natural language.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Human-like few-shot learning via bayesian reasoning over natural language

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:43.232605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bca2c172-4e0e-4895-a0f1-aa4a0abf05ca · outbound

This paper cites Friedman and Bogdan E.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Friedman and Bogdan E

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:43.365170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0c016e1-536f-4d33-bb85-ebd76de8494b · outbound

This paper cites A brief overview of rule learning.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models A brief overview of rule learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:43.508194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9716625-c2dc-443c-8130-57ca9664aabd · outbound

This paper cites Neuro-symbolic hierarchical rule induction.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Neuro-symbolic hierarchical rule induction

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:43.563423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffe35188-0f53-4635-a649-eef3174e7c36 · outbound

This paper cites Learning mdl logic programs from noisy data.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Learning mdl logic programs from noisy data

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:43.727595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbdf287c-4e2a-4adb-9567-8700e3e7a5a6 · outbound

This paper cites Hypobench: Towards systematic and principled benchmarking for hypothesis generation.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Hypobench: Towards systematic and principled benchmarking for hypothesis generation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:43.835856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc496bf8-c2b7-4642-94fc-dc5703309466 · outbound

This paper cites Explainable artificial intelligence: a comprehensive review.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Explainable artificial intelligence: a comprehensive review

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:43.951416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 447eedbb-bdd0-433a-be9b-c02375d03594 · outbound

This paper cites Learning accurate and interpretable decision rule sets from neural networks.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Learning accurate and interpretable decision rule sets from neural networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.069077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4429a2a-c564-4fdf-816d-30dd9c2256d0 · outbound

This paper cites Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.197829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ae2db2a-142b-41a9-b622-f6c5365458d7 · outbound

This paper cites Logic regression.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Logic regression

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.344620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b196ac9-f4b1-4d9b-b2f7-ef830f225e00 · outbound

This paper cites Explaining Patterns in Data with Language Models via Interpretable Autoprompting.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Explaining Patterns in Data with Language Models via Interpretable Autoprompting

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.466508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29171324-d0be-4b8f-a363-cbafb849f18f · outbound

This paper cites Neuro-Symbolic Rule Lists.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Neuro-Symbolic Rule Lists

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.635741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa2bd175-6f53-47f8-9d37-ab82a170b044 · outbound

This paper cites Scalable bayesian rule lists.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Scalable bayesian rule lists

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.748202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cebef19-ba7b-47e1-ae9d-bf626de54d91 · outbound

This paper cites Truly unordered probabilistic rule sets for multi-class classification.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Truly unordered probabilistic rule sets for multi-class classification

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.822454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0999d25-aa66-4a2b-b7e6-ac87b8ad9a87 · outbound

This paper cites Hyperlogic: Enhancing diversity and accuracy in rule learning with hypernets.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Hyperlogic: Enhancing diversity and accuracy in rule learning with hypernets

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.877303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89c97a68-bf83-41f0-9085-01e7a0065c2f · outbound

This paper cites Large Language Models for Automated Open-domain Scientific Hypotheses Discovery.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:44.933593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06a8cedc-95fe-45ee-82c1-b6841ff42d81 · outbound

This paper cites Moose-chem: Large language models for rediscovering unseen chemistry scientific hypotheses.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Moose-chem: Large language models for rediscovering unseen chemistry scientific hypotheses

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:45.077154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4f0bd83-23cc-4c41-9b6c-1fb421301482 · outbound

This paper cites RuAG: Learned-rule-augmented Generation for Large Language Models.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models RuAG: Learned-rule-augmented Generation for Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:45.202113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b530077d-2837-4026-910f-10659ba57d40 · outbound

This paper cites Hypothesis Generation with Large Language Models.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Hypothesis Generation with Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:45.342261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76f46210-45f5-4218-bfaa-7f18f6d19050 · outbound

This paper cites Regularization and Variable Selection via the Elastic Net.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Regularization and Variable Selection via the Elastic Net

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:45.524067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72852579-40dd-42aa-a67c-add05ece206b · outbound

This paper cites write newline.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models write newline

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:45.649081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 410ae112-a7ac-4b5c-9fd6-de190997b35e · outbound

This paper cites @esa (Ref.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models @esa (Ref

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:45.814043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f0bca04-f901-4aab-b46d-73a9a9883c89 · outbound

This paper cites an unresolved cited work.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:45.921260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da4d0788-00a7-430f-a992-6b744cc7b850 · outbound

This paper cites first" vs.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models first" vs

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T08:39:46.035913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.