Paper Citation Record · LEDGER

Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2309.14316.

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

pith.paper-citation-record.v1
2309.14316 v3

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measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:25:25.280155Z

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Outbound references

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Pith citing papers

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Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks cites this paper.

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2

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Paying Attention to Facts: Quantifying the Knowledge Capacity of Attention Layers cites this paper.

Paying Attention to Facts: Quantifying the Knowledge Capacity of Attention Layers Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers cites this paper.

Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 65

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Who Reasons in the Large Language Models? cites this paper.

Who Reasons in the Large Language Models? Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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From Parameters to Prompts: Understanding and Mitigating the Factuality Gap between Fine-Tuned LLMs cites this paper.

From Parameters to Prompts: Understanding and Mitigating the Factuality Gap between Fine-Tuned LLMs Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2

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Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race cites this paper.

Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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Evaluating the Unseen Capabilities: How Many Theorems Do LLMs Know? cites this paper.

Evaluating the Unseen Capabilities: How Many Theorems Do LLMs Know? Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2

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On Generalization across Measurement Systems: LLMs Entail More Test-Time Compute for Underrepresented Cultures cites this paper.

On Generalization across Measurement Systems: LLMs Entail More Test-Time Compute for Underrepresented Cultures Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2024

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NeurIPS 2025 E2LM Competition : Early Training Evaluation of Language Models cites this paper.

NeurIPS 2025 E2LM Competition : Early Training Evaluation of Language Models Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 35

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BlueGlass: A Framework for Composite AI Safety cites this paper.

BlueGlass: A Framework for Composite AI Safety Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 4

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Provable Knowledge Acquisition and Extraction in One-Layer Transformers cites this paper.

Provable Knowledge Acquisition and Extraction in One-Layer Transformers Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 3

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Observation 2ac4b2c5-ff58-4036-9bf2-9abc5299b688 · inbound

Do Activation Verbalization Methods Convey Privileged Information? cites this paper.

Do Activation Verbalization Methods Convey Privileged Information? Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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How Training Data Shapes the Use of Parametric and In-Context Knowledge in Language Models cites this paper.

How Training Data Shapes the Use of Parametric and In-Context Knowledge in Language Models Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models cites this paper.

GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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TRINITY: An Evolved LLM Coordinator cites this paper.

TRINITY: An Evolved LLM Coordinator Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers cites this paper.

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2024

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Unifying Learning Dynamics and Generalization in Transformers Scaling Law cites this paper.

Unifying Learning Dynamics and Generalization in Transformers Scaling Law Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 7

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Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts cites this paper.

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data cites this paper.

Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 51

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Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction cites this paper.

Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities? cites this paper.

ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities? Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 48

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Observation 0086058b-d21d-472a-ad3d-e604b4311b0c · inbound

Boosting Self-Consistency with Ranking cites this paper.

Boosting Self-Consistency with Ranking Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 127

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A Systematic Study of Behavioral Cloning for Scientific Data Annotation cites this paper.

A Systematic Study of Behavioral Cloning for Scientific Data Annotation Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 69

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Analyzing the Correlation Between Hallucinations and Knowledge Conflicts in Large Language Models cites this paper.

Analyzing the Correlation Between Hallucinations and Knowledge Conflicts in Large Language Models Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 18

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Vibe Calibration: Autonomous Bring-up of a 112-Qubit Superconducting Quantum Processor by a Skill-Orchestrating Language Agent cites this paper.

Vibe Calibration: Autonomous Bring-up of a 112-Qubit Superconducting Quantum Processor by a Skill-Orchestrating Language Agent Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 72

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DataComp-VLM: Improved Open Datasets for Vision-Language Models cites this paper.

DataComp-VLM: Improved Open Datasets for Vision-Language Models Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 10

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DataComp-VLM: Improved Open Datasets for Vision-Language Models cites this paper.

DataComp-VLM: Improved Open Datasets for Vision-Language Models Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 10

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PASTA: A Paraphrasing And Self-Training Approach for Knowledge Updating in LLMs cites this paper.

PASTA: A Paraphrasing And Self-Training Approach for Knowledge Updating in LLMs Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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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 Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2

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Pretraining Curricula Enable Selective Fine-tuning cites this paper.

Pretraining Curricula Enable Selective Fine-tuning Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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Can a Language Model Learn Facts Continually in Its Weights? cites this paper.

Can a Language Model Learn Facts Continually in Its Weights? Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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Data Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA cites this paper.

Data Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs cites this paper.

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 18

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