Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:31:40.416807Z
Paper Citation Record · LEDGER
Data Efficacy for Language Model Training
As of 7 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-26T04:49:28.598430Z
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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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.
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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:31:39.955344Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:31:41.973753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dc04d5f7-4d10-422b-bf68-e651558f3866 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T13:49:52.415420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.