Paper Citation Record · LEDGER

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection

As of 8 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2509.06524.

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

pith.paper-citation-record.v1
2509.06524 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:33:43.787531Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

51 of 51 outbound references displayed

verified exact2
verified fuzzy24
unresolved24
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 36611695-46bc-4fbd-84b8-32bb852895e0 · outbound

This paper cites write newline.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection write newline

Reference 1

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Observation b8a1c987-f9d3-4830-97bd-5cac28f49bee · outbound

This paper cites Program Synthesis with Large Language Models.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Program Synthesis with Large Language Models

Reference 2

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Observation 1f02c21e-0bd0-43f5-8ed4-61aa24933c99 · outbound

This paper cites Color-filter: Conditional loss reduction filtering for targeted language model pre-training.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Color-filter: Conditional loss reduction filtering for targeted language model pre-training

Reference 3

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Observation 7f3a2181-16a7-4984-a9b9-c71cb163f229 · outbound

This paper cites Statistical inference.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Statistical inference

Reference 4

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This paper cites Maybe Only 0.5% Data is Needed: A Preliminary Exploration of Low Training Data Instruction Tuning.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Maybe Only 0.5% Data is Needed: A Preliminary Exploration of Low Training Data Instruction Tuning

Reference 5

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Unresolved cited work

Reference 6

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Observation 704d50ee-96cd-4719-aea2-56c47465eb94 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Training Verifiers to Solve Math Word Problems

Reference 7

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Observation 287cdd5e-d610-4783-8cf1-ef9e6da14912 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

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Observation 2ce12f0a-0236-4e3e-919b-87c55dcfe2ae · outbound

This paper cites Sketchy moment matching: Toward fast and provable data selection for finetuning.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Sketchy moment matching: Toward fast and provable data selection for finetuning

Reference 9

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Observation 14b74413-3450-492a-a832-84dcac04a4c6 · outbound

This paper cites Dsdm: Model-aware dataset selection with datamodels.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Dsdm: Model-aware dataset selection with datamodels

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:47.679914Z

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Observation b41baaee-b249-45ce-80bb-435e46fd4c17 · outbound

This paper cites Dsdm: Model-aware dataset selection with datamodels.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Dsdm: Model-aware dataset selection with datamodels

Reference 11

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Observation 9e408eab-4345-4f8c-ba54-82c54f1b0b66 · outbound

This paper cites Evans, Gordon B.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Evans, Gordon B

Reference 12

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Observation 7768ed40-0b9f-49ac-a8a0-5c6e23406c02 · outbound

This paper cites GIO : Gradient information optimization for training dataset selection.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection GIO : Gradient information optimization for training dataset selection

Reference 13

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Observation 76aea87e-84af-4f9d-90f8-6dbdca0f4488 · outbound

This paper cites CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution

Reference 14

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Observation cafc6fa2-8a3c-48f4-a098-066c6a9741c4 · outbound

This paper cites Data selection via optimal control for language models.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Data selection via optimal control for language models

Reference 15

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Observation 46d76be7-5a67-48c0-98a5-fc5bab34c857 · outbound

This paper cites SHED : Shapley-based automated dataset refinement for instruction fine-tuning.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection SHED : Shapley-based automated dataset refinement for instruction fine-tuning

Reference 16

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Observation f797b552-f111-48b8-87c1-5ee5e7140c79 · outbound

This paper cites Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights

Reference 17

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Observation f75f2856-375b-4f60-9c50-be598e2a3354 · outbound

This paper cites Livecodebench: Holistic and contamination free evaluation of large language models for code.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Livecodebench: Holistic and contamination free evaluation of large language models for code

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:46.868735Z

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Observation b51f0d1c-0cd2-4268-b5a4-3e4c2f94796f · outbound

This paper cites Scaling Laws for Neural Language Models.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Scaling Laws for Neural Language Models

Reference 19

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Rule-based data selection for large language models

Reference 20

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This paper cites One shot learning as instruction data prospector for large language models.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection One shot learning as instruction data prospector for large language models

Reference 21

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Observation c561e07e-59f4-4c65-a8cd-535feab56a53 · outbound

This paper cites D 2 LLM : Decomposed and distilled large language models for semantic search.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection D 2 LLM : Decomposed and distilled large language models for semantic search

Reference 22

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Observation bbd39cec-346f-458f-8e51-2b755225f82e · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Let's Verify Step by Step

Reference 23

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This paper cites What makes good data for alignment? a comprehensive study of automatic data selection in instruction tuning.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection What makes good data for alignment? a comprehensive study of automatic data selection in instruction tuning

Reference 24

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Observation 033ccbfb-96c2-4282-93a0-05f3e839a323 · outbound

This paper cites Take the essence and discard the dross: A Rethinking on Data Selection for Fine-Tuning Large Language Models.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Take the essence and discard the dross: A Rethinking on Data Selection for Fine-Tuning Large Language Models

Reference 25

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Observation 0fab0a4b-2e75-415d-83e8-751c43aebed6 · outbound

This paper cites TSDS : Data selection for task-specific model finetuning.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection TSDS : Data selection for task-specific model finetuning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:46.481496Z

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Observation 5af94284-6847-4d3b-a7ab-6e956edfb3e9 · outbound

This paper cites When less is more: Investigating data pruning for pretraining llms at scale.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection When less is more: Investigating data pruning for pretraining llms at scale

Reference 27

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Observation 5e28398d-e475-4374-a303-2403924068b6 · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection SGPT: GPT Sentence Embeddings for Semantic Search

Reference 28

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Scaling data-constrained language models

Reference 29

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Observation 9631d39c-eeeb-4309-90f6-e80fb02a35b2 · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Trak: Attributing model behavior at scale

Reference 30

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection O1 Replication Journey: A Strategic Progress Report -- Part 1

Reference 31

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Learning to retrieve prompts for in-context learning

Reference 32

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection How to Train Data-Efficient LLMs

Reference 33

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Improving dense retrieval models with llm augmented data for dataset search

Reference 34

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Observation 46a246d7-5e3a-422f-9a78-9df8a2838166 · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Improving pretraining data using perplexity correlations

Reference 35

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection LLaMA: Open and Efficient Foundation Language Models

Reference 36

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This paper cites How do your code LLM s perform? empowering code instruction tuning with really good data.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection How do your code LLM s perform? empowering code instruction tuning with really good data

Reference 37

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Observation 4c1b800b-8ca5-4467-8ea0-988b5cf2a74d · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection QuRating : Selecting high-quality data for training language models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:45.605862Z

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Observation cb22c5e6-6e93-49f8-998b-a50e84f659d8 · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection LESS : Selecting influential data for targeted instruction tuning

Reference 39

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Observation d58a49f6-035b-4227-b3bd-5532c68c0beb · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Data selection for language models via importance resampling

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:45.284526Z

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Observation f481929d-97f7-4e8b-9e38-5883038d6f20 · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Wizard LM : Empowering large pre-trained language models to follow complex instructions

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:45.103528Z

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Observation 46a96f41-d786-4306-8a1b-96158de5e3c9 · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Diffusion models: A comprehensive survey of methods and applications

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:44.964591Z

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Observation 2a0ed0ab-e21f-40d8-a1c9-3fc0cb07deef · outbound

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection LIMO: Less is More for Reasoning

Reference 43

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Mates: Model-aware data selection for efficient pretraining with data influence models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:44.836188Z

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Observation c9202663-b1d7-44aa-a5fc-987e70b7257a · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 45

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Observation c5e85840-c6e5-4cad-959e-3d8b7ab4e27a · outbound

This paper cites Beyond similarity: A gradient-based graph method for instruction tuning data selection.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection Beyond similarity: A gradient-based graph method for instruction tuning data selection

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:44.679324Z

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Observation d5965d9f-92de-4616-bf9d-b506567a1a1e · outbound

This paper cites OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement

Reference 47

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LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection LIMA : Less is more for alignment

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:33:44.510160Z

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Observation aa2630f7-9d58-403b-a007-d0b16e3eb506 · outbound

This paper cites @esa (Ref.

LAMDAS: LLM as an Implicit Classifier for Domain-specific Data Selection @esa (Ref

Reference 49

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Reference 50

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Reference 51

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Pith citing papers

No inbound Pith citation observations are available.