Paper Citation Record · LEDGER

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

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 47 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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Pith citing papers

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Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension Ability cites this paper.

Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension Ability Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 47

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Theoretical limitations of multi-layer Transformer cites this paper.

Theoretical limitations of multi-layer Transformer Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 5

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Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation cites this paper.

Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2

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Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs cites this paper.

Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 1

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LIFT: Improving Long Context Understanding Through Long Input Fine-Tuning cites this paper.

LIFT: Improving Long Context Understanding Through Long Input Fine-Tuning Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2023

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ICLR: In-Context Learning of Representations cites this paper.

ICLR: In-Context Learning of Representations Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 4

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Analyzing Memorization in Large Language Models through the Lens of Model Attribution cites this paper.

Analyzing Memorization in Large Language Models through the Lens of Model Attribution Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 3

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Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home cites this paper.

Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 3

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Spurious Forgetting in Continual Learning of Language Models cites this paper.

Spurious Forgetting in Continual Learning of Language Models Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 3

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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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From Promising Capability to Pervasive Bias: Assessing Large Language Models for Emergency Department Triage cites this paper.

From Promising Capability to Pervasive Bias: Assessing Large Language Models for Emergency Department Triage Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 57

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Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search cites this paper.

Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 10

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Evaluating Explanations: An Explanatory Virtues Framework for Mechanistic Interpretability -- The Strange Science Part I.ii cites this paper.

Evaluating Explanations: An Explanatory Virtues Framework for Mechanistic Interpretability -- The Strange Science Part I.ii Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2

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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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Capacity Matters: a Proof-of-Concept for Transformer Memorization on Real-World Data cites this paper.

Capacity Matters: a Proof-of-Concept for Transformer Memorization on Real-World Data Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 2

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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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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

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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

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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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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

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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

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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

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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

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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

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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

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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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The Announcement Carries the Cue: Markup, Boundaries, and the Notation of Pre-Training Corpora cites this paper.

The Announcement Carries the Cue: Markup, Boundaries, and the Notation of Pre-Training Corpora Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

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