Paper Citation Record · LEDGER

Data Efficacy for Language Model Training

As of 18 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 1 inbound Pith citation observation for arXiv:2506.21545.

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

pith.paper-citation-record.v1
2506.21545 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:31:40.416807Z

measured 64 of 64 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T04:49:28.598430Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:49:52.413967Z

Reference resolution

63 of 63 outbound references displayed

verified exact2
verified fuzzy32
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3472e36a-d530-47ef-ae56-b2e31262b75a · outbound

This paper cites Training language models to follow instructions with human feedback.

Data Efficacy for Language Model Training Training language models to follow instructions with human feedback

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:19.795365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34907434-1239-45b4-88c2-d0f1c4fee130 · outbound

This paper cites GPT-4 Technical Report.

Data Efficacy for Language Model Training GPT-4 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:34.789743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c20a7caf-e52b-4419-ab88-69ffb3476f62 · outbound

This paper cites The Llama 3 Herd of Models.

Data Efficacy for Language Model Training The Llama 3 Herd of Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:34.895488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 109ce30e-a715-4be8-9bde-903bf3f6e665 · outbound

This paper cites Advances in natural language processing.

Data Efficacy for Language Model Training Advances in natural language processing

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:46.230969Z

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.

Observation 43b7d785-8f9e-4852-8966-d9661c2e5f0c · outbound

This paper cites Exploring Sentiment Analysis Techniques in Natural Language Processing: A Comprehensive Review.

Data Efficacy for Language Model Training Exploring Sentiment Analysis Techniques in Natural Language Processing: A Comprehensive Review

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:31:40.922314Z

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.

Observation 13d9fd78-e418-4d90-ab5a-2a45644dba8a · outbound

This paper cites Natural language reasoning, a survey.ACM Computing Surveys, 56(12):1–39, 2024.

Data Efficacy for Language Model Training Natural language reasoning, a survey.ACM Computing Surveys, 56(12):1–39, 2024

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:35.320880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af796198-10d4-423a-b3d0-5532553f81bc · outbound

This paper cites Ai- based conversational agents: a scoping review from technologies to future directions.

Data Efficacy for Language Model Training Ai- based conversational agents: a scoping review from technologies to future directions

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:46.065682Z

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.

Observation a1927fc7-0ceb-4778-b125-e5bfacb792d9 · outbound

This paper cites A Survey on Data Selection for Language Models.

Data Efficacy for Language Model Training A Survey on Data Selection for Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:35.530387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef3463bf-d78b-476a-ac3e-401d1550cb6f · outbound

This paper cites Data selection for language models via importance resampling.

Data Efficacy for Language Model Training Data selection for language models via importance resampling

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:45.895241Z

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.

Observation e3ec3028-3dba-451f-a437-18ddd3f97bb0 · outbound

This paper cites Data Selection via Optimal Control for Language Models.

Data Efficacy for Language Model Training Data Selection via Optimal Control for Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:35.732689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9afb825a-41b3-4b1a-ab8e-df850b14d8db · outbound

This paper cites Curriculum learning for language modeling.

Data Efficacy for Language Model Training Curriculum learning for language modeling

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:35.794833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5455404c-f873-465e-8537-443144bf71ca · outbound

This paper cites A survey on curriculum learning.IEEE transactions on pattern analysis and machine intelligence, 44(9):4555–4576, 2021.

Data Efficacy for Language Model Training A survey on curriculum learning.IEEE transactions on pattern analysis and machine intelligence, 44(9):4555–4576, 2021

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:35.871785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 181826f8-e99f-458a-b806-4e797e939955 · outbound

This paper cites hello-gpt-4o.

Data Efficacy for Language Model Training hello-gpt-4o

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:45.681972Z

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.

Observation 732c55b2-97bc-4c44-84b0-dcb59c421d78 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Data Efficacy for Language Model Training Gemini: A Family of Highly Capable Multimodal Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:36.095933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfed6da5-5d01-4875-bc9d-f1b78466d95d · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Data Efficacy for Language Model Training Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:36.144310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 688f2516-476c-4595-b6e0-f95ff308ca9e · outbound

This paper cites Long short-term memory.

Data Efficacy for Language Model Training Long short-term memory

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:36.249863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d60b150-431e-4a24-a423-184016f8a3e5 · outbound

This paper cites Scaling Laws for Neural Language Models.

Data Efficacy for Language Model Training Scaling Laws for Neural Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:36.341314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0858127b-aa58-4d30-8628-25ec4970a281 · outbound

This paper cites Scaling laws for data filtering–data curation cannot be compute agnostic.

Data Efficacy for Language Model Training Scaling laws for data filtering–data curation cannot be compute agnostic

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:45.455618Z

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.

Observation 02bebf18-ee54-457b-b079-53b8c8b972d8 · outbound

This paper cites KenLM: Faster and smaller language model queries.

Data Efficacy for Language Model Training KenLM: Faster and smaller language model queries

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:45.203086Z

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.

Observation 8c87e9eb-75b3-4a0a-9f11-8afdcd28682a · outbound

This paper cites Claude 3 haiku: our fastest model yet.

Data Efficacy for Language Model Training Claude 3 haiku: our fastest model yet

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.984977Z

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.

Observation 1252c827-a720-4254-8352-bdd6bde866cf · outbound

This paper cites Paml 4: phylogenetic analysis by maximum likelihood.

Data Efficacy for Language Model Training Paml 4: phylogenetic analysis by maximum likelihood

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.857188Z

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.

Observation edcc5ac3-4dc4-4523-a9fe-b72b283f75ac · outbound

This paper cites Common crawl – building an open web-scale crawl using hadoop, 2010.

Data Efficacy for Language Model Training Common crawl – building an open web-scale crawl using hadoop, 2010

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.730683Z

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.

Observation 2a3c4282-7a05-45db-aa0a-e57051d3bb3b · outbound

This paper cites Project gutenberg, 2004.

Data Efficacy for Language Model Training Project gutenberg, 2004

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.626745Z

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.

Observation 1800c862-3d77-4e66-8e4d-b2ff96e97ab8 · outbound

This paper cites Synthetic data for deep learning , volume 174.

Data Efficacy for Language Model Training Synthetic data for deep learning , volume 174

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.504460Z

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.

Observation e1b7d25e-5cca-4c8c-8ae9-ab772e92dc82 · outbound

This paper cites Virtual sensors: Abstracting data from physical sensors.

Data Efficacy for Language Model Training Virtual sensors: Abstracting data from physical sensors

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.406796Z

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.

Observation ef5ba448-e607-4b88-95f1-db06e6d7af76 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

Data Efficacy for Language Model Training Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:37.178879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53478cd4-9bc4-4938-9b6e-df65e110288a · outbound

This paper cites The refinedweb dataset for falcon llm: Outperforming curated corpora with web data only.

Data Efficacy for Language Model Training The refinedweb dataset for falcon llm: Outperforming curated corpora with web data only

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.320180Z

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.

Observation 61cb4c60-bc85-4f79-8533-cfae6e3eb1ff · outbound

This paper cites Redpajama: an open dataset for training large language models.

Data Efficacy for Language Model Training Redpajama: an open dataset for training large language models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:37.336209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9af43c7-a9b7-451e-b517-6d0514dd2b55 · outbound

This paper cites RedStone: Curating General, Code, Math, and QA Data for Large Language Models.

Data Efficacy for Language Model Training RedStone: Curating General, Code, Math, and QA Data for Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:37.409614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2af7a3f-b91f-433b-9166-60a72cc70ff1 · outbound

This paper cites Mates: Model-aware data selection for efficient pretraining with data influence models.

Data Efficacy for Language Model Training Mates: Model-aware data selection for efficient pretraining with data influence models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.202949Z

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.

Observation e7f4349a-1d10-4a6f-a369-fef8925df5bf · outbound

This paper cites Training-free dataset pruning for instance segmentation.

Data Efficacy for Language Model Training Training-free dataset pruning for instance segmentation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:44.095050Z

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.

Observation 5ad266e4-2031-4862-899b-a22d6be16703 · outbound

This paper cites P-diff+: Improving learning classifier with noisy labels by noisy negative learning loss.

Data Efficacy for Language Model Training P-diff+: Improving learning classifier with noisy labels by noisy negative learning loss

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:43.990600Z

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.

Observation 3fb4ae5a-4f96-48e0-9d3f-a804118be1dd · outbound

This paper cites P-diff: Learning classifier with noisy labels based on probability difference distributions.

Data Efficacy for Language Model Training P-diff: Learning classifier with noisy labels based on probability difference distributions

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:43.881483Z

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.

Observation ea0935cd-49b8-421c-b4b8-883d969337d8 · outbound

This paper cites SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

Data Efficacy for Language Model Training SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:37.703358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e655be23-c353-4bf2-8cc8-0f06301c35cc · outbound

This paper cites D4: Improving llm pretraining via document de-duplication and diversification.

Data Efficacy for Language Model Training D4: Improving llm pretraining via document de-duplication and diversification

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:43.768535Z

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.

Observation 13b16161-46e5-45cc-b23a-cb4b4c4a5f00 · outbound

This paper cites Strategic Data Ordering: Enhancing Large Language Model Performance through Curriculum Learning.

Data Efficacy for Language Model Training Strategic Data Ordering: Enhancing Large Language Model Performance through Curriculum Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:37.853648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b295c33-2616-43ae-a09a-71f2730342b9 · outbound

This paper cites Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learning.

Data Efficacy for Language Model Training Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learning

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:31:40.710309Z

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.

Observation 8c0be7cb-f617-4dd3-8ec5-df298404a13f · outbound

This paper cites DoReMi: Optimizing data mixtures speeds up language model pretraining.

Data Efficacy for Language Model Training DoReMi: Optimizing data mixtures speeds up language model pretraining

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:43.673371Z

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.

Observation 0b2a68e7-4a68-4024-9700-cf5ce660c34e · outbound

This paper cites Lima: Less is more for alignment.

Data Efficacy for Language Model Training Lima: Less is more for alignment

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:43.563723Z

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.

Observation ca58f8fa-b5bd-49ec-963f-0d6d9132a0b2 · outbound

This paper cites Openwebmath: An open dataset of high-quality mathematical web text, 2023.

Data Efficacy for Language Model Training Openwebmath: An open dataset of high-quality mathematical web text, 2023

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:38.370698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3eb84262-2755-4f47-9c16-039dbd257e40 · outbound

This paper cites MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics.

Data Efficacy for Language Model Training MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:38.509344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b18f4e11-793c-4db5-b71e-5e668be63f4a · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

Data Efficacy for Language Model Training StarCoder 2 and The Stack v2: The Next Generation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:38.679922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1c0a048-7337-4760-b423-606723280f2d · outbound

This paper cites Epicoder: Encompassing diversity and complexity in code generation.

Data Efficacy for Language Model Training Epicoder: Encompassing diversity and complexity in code generation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:38.794928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eaf93f6-b84b-47a9-af78-a170358f2de2 · outbound

This paper cites Mistral 7B.

Data Efficacy for Language Model Training Mistral 7B

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:38.889964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5ee4398-ee2c-41cb-a1c9-f5e6ec0c7bf8 · outbound

This paper cites Qwen Technical Report.

Data Efficacy for Language Model Training Qwen Technical Report

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:38.997852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bb581e0-945e-4cf0-bbb4-8478a8f754fd · outbound

This paper cites OLMo: Accelerating the Science of Language Models.

Data Efficacy for Language Model Training OLMo: Accelerating the Science of Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:39.060536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e32dec9-e955-44f6-b0b1-f9a89ceda0eb · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In Proceedings of ACL, 2019.

Data Efficacy for Language Model Training Hellaswag: Can a machine really finish your sentence? In Proceedings of ACL, 2019

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:43.416290Z

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.

Observation d30f3ec4-a3b1-498c-b6e9-edfd1ef90b55 · outbound

This paper cites The winograd schema challenge.

Data Efficacy for Language Model Training The winograd schema challenge

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:43.234992Z

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.

Observation 1f834b77-8d9d-473d-b3fb-7b758a0a26b8 · outbound

This paper cites The lambada dataset: Word prediction requiring a broad discourse context.

Data Efficacy for Language Model Training The lambada dataset: Word prediction requiring a broad discourse context

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:43.085204Z

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.

Observation 6aa43bff-0821-4ecb-9854-5b3586e92bc1 · outbound

This paper cites Can a suit of armor conduct electricity? a new dataset for open book question answering.

Data Efficacy for Language Model Training Can a suit of armor conduct electricity? a new dataset for open book question answering

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:42.927964Z

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.

Observation a029a61f-bf3a-4d63-8253-7a5d63fb8916 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Data Efficacy for Language Model Training Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:39.363914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc872b53-e93a-4a05-a77d-65bd721bfd29 · outbound

This paper cites Piqa: Reasoning about physical common- sense in natural language.

Data Efficacy for Language Model Training Piqa: Reasoning about physical common- sense in natural language

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:42.710576Z

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.

Observation f407e16b-dd00-4152-aab2-32f538352ad5 · outbound

This paper cites Liu, and Matt Gardner.

Data Efficacy for Language Model Training Liu, and Matt Gardner

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:42.527336Z

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.

Observation 451ce2a6-f0a4-45f6-9ee0-4059911f2b09 · outbound

This paper cites BoolQ: Exploring the surprising difficulty of natural yes/no questions.

Data Efficacy for Language Model Training BoolQ: Exploring the surprising difficulty of natural yes/no questions

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:42.323259Z

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.

Observation fa2ec6e9-33ea-4869-8e1b-9ea6d509a64e · outbound

This paper cites an unresolved cited work.

Data Efficacy for Language Model Training Unresolved cited work

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:39.689642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17350254-b8c4-48a4-8322-bfa482950b43 · outbound

This paper cites Mathqa: Towards interpretable math word problem solving with operation-based formalisms, 2019.

Data Efficacy for Language Model Training Mathqa: Towards interpretable math word problem solving with operation-based formalisms, 2019

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T22:31:39.764554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9caa4a74-9795-4b26-ae42-fdb2e2fb3e54 · outbound

This paper cites an unresolved cited work.

Data Efficacy for Language Model Training Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:31:42.162493Z

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Observation ed73ddf4-2c92-400d-a2e8-1fc17282ccd3 · outbound

This paper cites Program Synthesis with Large Language Models.

Data Efficacy for Language Model Training Program Synthesis with Large Language Models

Reference 58

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Observation 752b0d3d-0c92-47dd-aad2-1212e2992466 · outbound

This paper cites Efficient large scale language modeling with mixtures of experts.

Data Efficacy for Language Model Training Efficient large scale language modeling with mixtures of experts

Reference 59

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Observation bd642587-8300-4094-999f-0cd460e8c61d · outbound

This paper cites Decoupled weight decay regularization.

Data Efficacy for Language Model Training Decoupled weight decay regularization

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:41.786740Z

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Observation 2bc119d4-5638-4b74-be28-6607582b63c6 · outbound

This paper cites Comparing the pearson and spearman correla- tion coefficients across distributions and sample sizes: A tutorial using simulations and empirical data.

Data Efficacy for Language Model Training Comparing the pearson and spearman correla- tion coefficients across distributions and sample sizes: A tutorial using simulations and empirical data

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:41.578495Z

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Observation 6d65bff9-d365-460a-af49-54a81ef4cd17 · outbound

This paper cites As described in algorithm 1, we apply a linear transformation to the mean-pooled representations of instances along the sequence length.

Data Efficacy for Language Model Training As described in algorithm 1, we apply a linear transformation to the mean-pooled representations of instances along the sequence length

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:41.369377Z

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This paper cites I am overpowered by the discovery of my own genius for management.

Data Efficacy for Language Model Training I am overpowered by the discovery of my own genius for management

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:31:41.149390Z

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Pith citing papers

Observation e2a8aeb6-0d71-470b-aa72-6e671db70eb7 · inbound

GEOALIGN: Geometric Rollout Curation for Robust LLM Reinforcement Learning cites this paper.

GEOALIGN: Geometric Rollout Curation for Robust LLM Reinforcement Learning Data Efficacy for Language Model Training

Reference 4

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