Paper Citation Record · LEDGER

A Survey on Model Compression for Large Language Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 41 inbound Pith citation observations for arXiv:2308.07633.

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

pith.paper-citation-record.v1
2308.07633 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 41 of 41 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:32:56.634579Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T10:27:02.453970Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

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Pith citing papers

Observation d8f3448f-b9e1-4de5-a46c-3d526e8720c1 · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models A Survey on Model Compression for Large Language Models

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:28:39.513658Z

Source-reported events for the cited work

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Observation 8b58d1ef-d214-4a57-a24c-d79e8a360122 · inbound

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models cites this paper.

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models A Survey on Model Compression for Large Language Models

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T13:49:33.798725Z

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Observation 59122b54-0682-4aa6-b875-1e5d83f2fc3d · inbound

A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.

A Survey on the Memory Mechanism of Large Language Model based Agents A Survey on Model Compression for Large Language Models

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T07:21:39.766166Z

Source-reported events for the cited work

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Observation b02219e1-bafa-4922-8f5d-9e28b6c42605 · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models A Survey on Model Compression for Large Language Models

Reference 17

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Observation 31a3178f-e27a-4e1e-a219-9cdbfa558d95 · inbound

Precision or Peril: A PoC of Python Code Quality from Quantized Large Language Models cites this paper.

Precision or Peril: A PoC of Python Code Quality from Quantized Large Language Models A Survey on Model Compression for Large Language Models

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:33:15.813455Z

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Observation b4d59a57-c4c1-485d-9f12-a06f45e2ba99 · inbound

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges cites this paper.

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges A Survey on Model Compression for Large Language Models

Reference 76

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Observation 6866c6f5-87f5-49a8-91e2-eeeb265f4393 · inbound

Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning cites this paper.

Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning A Survey on Model Compression for Large Language Models

Reference 33

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Observation b884096a-6e81-40bd-ac00-1248f41f1541 · inbound

Falcon: Faster and Parallel Inference of Large Language Models through Enhanced Semi-Autoregressive Drafting and Custom-Designed Decoding Tree cites this paper.

Falcon: Faster and Parallel Inference of Large Language Models through Enhanced Semi-Autoregressive Drafting and Custom-Designed Decoding Tree A Survey on Model Compression for Large Language Models

Reference 48

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Observation 1587f2f9-a5d6-4e24-9ea5-e37b9dc581d4 · inbound

Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference cites this paper.

Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference A Survey on Model Compression for Large Language Models

Reference 26

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Observation f8eeb740-8275-4448-9872-aa2df0f1b310 · inbound

Less is More: Towards Green Code Large Language Models via Unified Structural Pruning cites this paper.

Less is More: Towards Green Code Large Language Models via Unified Structural Pruning A Survey on Model Compression for Large Language Models

Reference 80

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Observation 3b6ef9c0-23d0-4660-b75d-acf611118b0c · inbound

A Survey on Large Language Model Acceleration based on KV Cache Management cites this paper.

A Survey on Large Language Model Acceleration based on KV Cache Management A Survey on Model Compression for Large Language Models

Reference 3

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Observation 400b2c5d-d868-458e-a8e8-7ce1d612126f · inbound

Language Models for Code Optimization: Survey, Challenges and Future Directions cites this paper.

Language Models for Code Optimization: Survey, Challenges and Future Directions A Survey on Model Compression for Large Language Models

Reference 164

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Observation df5e3aaf-90c4-4d66-8e13-21477903f164 · inbound

DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models cites this paper.

DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models A Survey on Model Compression for Large Language Models

Reference 23

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Observation b24bd678-0a1e-400c-98e9-474510a532af · inbound

Dissecting Bit-Level Scaling Laws in Quantizing Vision Generative Models cites this paper.

Dissecting Bit-Level Scaling Laws in Quantizing Vision Generative Models A Survey on Model Compression for Large Language Models

Reference 37

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Observation a1440eb5-360b-4b70-a7c7-3cf432871322 · inbound

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach cites this paper.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach A Survey on Model Compression for Large Language Models

Reference 41

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Observation a678d389-27c7-4661-a1d2-98018ce12462 · inbound

Resource-Efficient & Effective Code Summarization cites this paper.

Resource-Efficient & Effective Code Summarization A Survey on Model Compression for Large Language Models

Reference 46

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Observation 780e26fb-6a48-4fd6-ab9a-87f207ed756b · inbound

Refine Knowledge of Large Language Models via Adaptive Contrastive Learning cites this paper.

Refine Knowledge of Large Language Models via Adaptive Contrastive Learning A Survey on Model Compression for Large Language Models

Reference 55

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Observation 5f175c5c-0b68-40bc-82a2-495a124fb0cb · inbound

Resource-Efficient Language Models: Quantization for Fast and Accessible Inference cites this paper.

Resource-Efficient Language Models: Quantization for Fast and Accessible Inference A Survey on Model Compression for Large Language Models

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-15T21:55:07.904113Z

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Observation d2b5f896-08da-44e7-9896-d7520c679690 · inbound

The Hitchhikers Guide to Production-ready Trustworthy Foundation Model powered Software (FMware) cites this paper.

The Hitchhikers Guide to Production-ready Trustworthy Foundation Model powered Software (FMware) A Survey on Model Compression for Large Language Models

Reference 106

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Observation ba3600f1-79c8-4469-9147-29081cf8dac9 · inbound

On the Generalization vs Fidelity Paradox in Knowledge Distillation cites this paper.

On the Generalization vs Fidelity Paradox in Knowledge Distillation A Survey on Model Compression for Large Language Models

Reference 44

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Observation 35d1fb85-9e6b-4e03-bb04-4cf406c1c24d · inbound

NQKV: A KV Cache Quantization Scheme Based on Normal Distribution Characteristics cites this paper.

NQKV: A KV Cache Quantization Scheme Based on Normal Distribution Characteristics A Survey on Model Compression for Large Language Models

Reference 22

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Observation b62bf205-1d45-4324-88d6-cd9ac7e21163 · inbound

DECA: A Near-Core LLM Decompression Accelerator Grounded on a 3D Roofline Model cites this paper.

DECA: A Near-Core LLM Decompression Accelerator Grounded on a 3D Roofline Model A Survey on Model Compression for Large Language Models

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T14:21:59.265594Z

Source-reported events for the cited work

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Observation f897c398-904e-43bf-9df3-7e7471abb794 · inbound

Turning LLM Activations Quantization-Friendly cites this paper.

Turning LLM Activations Quantization-Friendly A Survey on Model Compression for Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T22:32:56.634579Z

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Observation 8b6e608d-ad4e-4c43-b58e-9b8b51284001 · inbound

Pruning General Large Language Models into Customized Expert Models cites this paper.

Pruning General Large Language Models into Customized Expert Models A Survey on Model Compression for Large Language Models

Reference 66

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Unavailable: canonical work link unavailable.

Observation fcbefac7-491d-4fa1-bdf5-25b2764ff8b6 · inbound

DIVE into MoE: Diversity-Enhanced Reconstruction of Large Language Models from Dense into Mixture-of-Experts cites this paper.

DIVE into MoE: Diversity-Enhanced Reconstruction of Large Language Models from Dense into Mixture-of-Experts A Survey on Model Compression for Large Language Models

Reference 57

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Observation 7c0818d5-62e2-48eb-b4dd-f23930c15f86 · inbound

Orchestration for Domain-specific Edge-Cloud Language Models cites this paper.

Orchestration for Domain-specific Edge-Cloud Language Models A Survey on Model Compression for Large Language Models

Reference 52

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Observation 78cde938-e477-4afe-993b-9d13f98a60d5 · inbound

Foundation Models for Clean Energy Forecasting: A Comprehensive Review cites this paper.

Foundation Models for Clean Energy Forecasting: A Comprehensive Review A Survey on Model Compression for Large Language Models

Reference 176

Resolution: unresolved; no resolver link, observed 2026-08-06T11:06:14.262804Z

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Observation 238f9b56-ae31-49ca-8e7c-3ed76c57da8d · inbound

Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos cites this paper.

Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos A Survey on Model Compression for Large Language Models

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-18T23:52:53.084202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7d1220cd-4c89-4ff3-8003-db1ce7f96456 · inbound

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression cites this paper.

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression A Survey on Model Compression for Large Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T12:52:01.733295Z

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Observation fff96ee7-9324-463c-a844-b2e7dfdc9fd9 · inbound

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models cites this paper.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models A Survey on Model Compression for Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.878839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30436d1e-7f56-45b3-8f4b-988c1fb393aa · inbound

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations cites this paper.

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations A Survey on Model Compression for Large Language Models

Reference 71

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T18:50:30.264426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 57ffe698-dbd2-49b9-a9e5-2008e7ac393f · inbound

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations cites this paper.

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations A Survey on Model Compression for Large Language Models

Reference 71

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14994c42-d4de-4a2c-9588-84ebfe2588af · inbound

Fragile Knowledge, Robust Instruction-Following: The Width Pruning Dichotomy in Llama-3.2 cites this paper.

Fragile Knowledge, Robust Instruction-Following: The Width Pruning Dichotomy in Llama-3.2 A Survey on Model Compression for Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-16T18:58:18.985436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 74b55445-88d2-4dbf-a640-99136f0522e9 · inbound

RUQuant: Towards Refining Uniform Quantization for Large Language Models cites this paper.

RUQuant: Towards Refining Uniform Quantization for Large Language Models A Survey on Model Compression for Large Language Models

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T17:38:02.576780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 08831974-50de-4a11-b9ff-6b4180f8386e · inbound

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models cites this paper.

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models A Survey on Model Compression for Large Language Models

Reference 46

Resolution: malformed identifier; arxiv_id, observed 2026-05-11T08:30:58.360484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c5b9396d-2f3b-48de-a3f5-2244ffcfe9bf · inbound

From Text to Voice: A Reproducible and Verifiable Framework for Evaluating Tool Calling LLM Agents cites this paper.

From Text to Voice: A Reproducible and Verifiable Framework for Evaluating Tool Calling LLM Agents A Survey on Model Compression for Large Language Models

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-21T08:49:53.710035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 31c07307-c8ae-4e6b-8859-c33106133de0 · inbound

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks cites this paper.

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks A Survey on Model Compression for Large Language Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:45:48.357172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 364cfd3a-c27d-4f3b-a42b-c0bd24d3cac8 · inbound

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks cites this paper.

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks A Survey on Model Compression for Large Language Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:35:40.072846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fb8fe8b2-24f6-4156-b72f-1ae9f5be74b7 · inbound

Different Teachers, Different Capabilities: Sub-1B On-Device Distillation for Structured Text Enrichment cites this paper.

Different Teachers, Different Capabilities: Sub-1B On-Device Distillation for Structured Text Enrichment A Survey on Model Compression for Large Language Models

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:27:02.455290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fc7b565d-8c03-4e38-a086-8fc79abf8b4b · inbound

Quantize with Confidence? An Empirical Study of Quantization for Code Generation cites this paper.

Quantize with Confidence? An Empirical Study of Quantization for Code Generation A Survey on Model Compression for Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T03:32:51.526085Z

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Observation d7ad915d-16b2-4492-a0cb-307eb22ecf6c · inbound

Unifying Depth and Width Pruning for LLMs via Binary Knapsack Optimization cites this paper.

Unifying Depth and Width Pruning for LLMs via Binary Knapsack Optimization A Survey on Model Compression for Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T19:58:17.591834Z

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Unavailable: canonical work link unavailable.