Paper Citation Record · LEDGER

Learning Facts at Scale with Active Reading

As of 21 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 3 inbound Pith citation observations for arXiv:2508.09494.

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

pith.paper-citation-record.v1
2508.09494 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:05:45.252753Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:43:07.506475Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T10:45:42.826299Z

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy4
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8f609d92-7573-4329-85a5-7cd4517ef3a1 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Learning Facts at Scale with Active Reading Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.181964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12e98aea-f85e-49c3-8d3b-948ec0f483a3 · outbound

This paper cites Learning to Ask: Neural Question Generation for Reading Comprehension.

Learning Facts at Scale with Active Reading Learning to Ask: Neural Question Generation for Reading Comprehension

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.197094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec96c355-dd7b-4620-804a-31a247acf53c · outbound

This paper cites Understanding Finetuning for Factual Knowledge Extraction.

Learning Facts at Scale with Active Reading Understanding Finetuning for Factual Knowledge Extraction

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.205525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 063cf6d4-af7f-49ec-9ad4-7839538bfae2 · outbound

This paper cites FinanceBench: A New Benchmark for Financial Question Answering.

Learning Facts at Scale with Active Reading FinanceBench: A New Benchmark for Financial Question Answering

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.211008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85fbef7c-f222-49e0-bc85-fb83c265ee90 · outbound

This paper cites doi: 10.18653/v1/P17-1147.

Learning Facts at Scale with Active Reading doi: 10.18653/v1/P17-1147

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.214048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d15bf24f-e233-40de-ae03-f749b7432737 · outbound

This paper cites Unfamiliar Finetuning Examples Control How Language Models Hallucinate.

Learning Facts at Scale with Active Reading Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.219566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88882ea9-09af-4b26-ac12-0481483d251a · outbound

This paper cites Textbooks Are All You Need II: phi-1.5 technical report.

Learning Facts at Scale with Active Reading Textbooks Are All You Need II: phi-1.5 technical report

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.221888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fab2e529-8271-4bb6-a0c2-cd32c520b693 · outbound

This paper cites Scaling Laws for Fact Memorization of Large Language Models.

Learning Facts at Scale with Active Reading Scaling Laws for Fact Memorization of Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.224515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1a3b514-908e-41b2-bf0d-6014ddfc61f0 · outbound

This paper cites How much do language models memorize?.

Learning Facts at Scale with Active Reading How much do language models memorize?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.227099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a403f49a-9b0f-4978-bb53-d8a239f7d57e · outbound

This paper cites Transfer learning in biomedical natural language processing: An evaluation of bert and elmo on ten benchmarking datasets.BioNLP 2019, page 58,.

Learning Facts at Scale with Active Reading Transfer learning in biomedical natural language processing: An evaluation of bert and elmo on ten benchmarking datasets.BioNLP 2019, page 58,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:05:45.421804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c53a816-0e25-4b9e-a815-8295b0d6db31 · outbound

This paper cites The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus.

Learning Facts at Scale with Active Reading The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.234867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84407bae-5299-4641-afc2-84184bf6f362 · outbound

This paper cites How new data permeates LLM knowledge and how to dilute it.

Learning Facts at Scale with Active Reading How new data permeates LLM knowledge and how to dilute it

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.240391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20334309-0999-4ca0-b5f4-bfca4de70b75 · outbound

This paper cites Synthetic continued pretraining.

Learning Facts at Scale with Active Reading Synthetic continued pretraining

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.245212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dcc3f8c-7f3e-47c9-b762-910a6871fae3 · outbound

This paper cites From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning.

Learning Facts at Scale with Active Reading From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.250462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b12f30b-9014-437a-a952-196d579dbd1b · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,.

Learning Facts at Scale with Active Reading Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.191545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c49f388-f4a5-4b09-88d0-ec1d2df9ff6b · outbound

This paper cites an unresolved cited work.

Learning Facts at Scale with Active Reading Unresolved cited work

Reference 2017

Resolution: unresolved; raw_fallback, observed 2026-08-05T21:05:45.438914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0e856678-5cc3-4674-92c1-0586552b2389 · outbound

This paper cites Here ’ s t h e p a r a g r a p h.

Learning Facts at Scale with Active Reading Here ’ s t h e p a r a g r a p h

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:05:45.412137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4b3655e1-a9bd-4695-b72f-48ff463a6ddf · outbound

This paper cites Memory Layers at Scale.

Learning Facts at Scale with Active Reading Memory Layers at Scale

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.188392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d31fa017-f06c-4b72-937f-bf5855fc4693 · outbound

This paper cites Legal-bert: The muppets straight out of law school.

Learning Facts at Scale with Active Reading Legal-bert: The muppets straight out of law school

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:05:45.447498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7fbcc309-8d5e-43df-b604-0813db2ba0a9 · outbound

This paper cites Will we run out of data? Limits of LLM scaling based on human-generated data.

Learning Facts at Scale with Active Reading Will we run out of data? Limits of LLM scaling based on human-generated data

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.242496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aef74e22-1d56-459b-8b5e-7e5779a29714 · outbound

This paper cites Textbooks Are All You Need.

Learning Facts at Scale with Active Reading Textbooks Are All You Need

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.207996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20361a5b-48e5-4052-b8b8-d99679b980a4 · outbound

This paper cites FinBERT: Financial Sentiment Analysis with Pre-trained Language Models.

Learning Facts at Scale with Active Reading FinBERT: Financial Sentiment Analysis with Pre-trained Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T21:05:45.185403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45f8727d-a35f-4c40-a319-2a471a41046f · outbound

This paper cites Fine-tuning or retrieval? comparing knowledge injection in llms.

Learning Facts at Scale with Active Reading Fine-tuning or retrieval? comparing knowledge injection in llms

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:05:45.430571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation f2f332c9-99d3-46d3-8b91-ee358a3a9b2c · inbound

EVE: A Domain-Specific LLM Framework for Earth Intelligence cites this paper.

EVE: A Domain-Specific LLM Framework for Earth Intelligence Learning Facts at Scale with Active Reading

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:35:18.264975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 386956e9-1d59-4574-95cd-222a3c1b42c8 · inbound

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA cites this paper.

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA Learning Facts at Scale with Active Reading

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:45:42.827705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3caafa8e-5deb-44a8-9844-35cb32e326d8 · inbound

K-EXAONE 2.0 Technical Report cites this paper.

K-EXAONE 2.0 Technical Report Learning Facts at Scale with Active Reading

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T14:43:07.506475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.