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Paper Citation Record · LEDGER

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering

As of 20 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2507.14179.

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

pith.paper-citation-record.v1
2507.14179 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:17:30.860934Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

20 of 20 outbound references displayed

  • verified exact2
  • verified fuzzy2
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9a0ee90d-608d-47a1-b740-0b61dc07d87a · outbound

This paper cites Dhar et al.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Dhar et al

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:17:32.242680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T18:17:29.623478Z digest=sha256:f7751805c36dafdf18125583f1c6745141075c28a21f9ec57133f17e58ef6a7b

Observation 19d5247a-9832-4f42-a0a9-5126e80c0b8b · outbound

This paper cites an unresolved cited work.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:17:32.101683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T18:17:29.693031Z digest=sha256:9edd09934c538c544bb3d9330cd8164a889d2bb0b5d9a05ed33d550f2206d6e4

Observation 7bd7deaa-4d3f-47ce-a67e-d162e50135b3 · outbound

This paper cites LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:29.759912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:29.759912Z digest=sha256:6baf3ec5c0c8a08c6c43302d67bf5c2bbfd99e807c87048e3851b151e103e800

Observation 72f34db2-1421-4361-84fa-68f5f0e40b43 · outbound

This paper cites an unresolved cited work.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Unresolved cited work

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:29.821817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:29.821817Z digest=sha256:03cf34d4c6509e722cb50eb540e44d85f99bf441c100d51194b91578874738a3

Observation 9b133cfa-df0e-4ec1-ba82-26bf5538d5ac · outbound

This paper cites Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:29.862879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:29.862879Z digest=sha256:5d310e0af29dbb453090dfee1d59b4196bfe0c2ae8faff408505f906f85e3110

Observation b20005dd-db28-4ede-a5cd-a5695b3b0063 · outbound

This paper cites SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:29.918290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:29.918290Z digest=sha256:b9a315c60fd4d09158fdacd34eec050373d9c4df8d3a96ef0dcd0eb077a38bf7

Observation 475efcc9-9968-4896-be7f-f9b96b9c5ab0 · outbound

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

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:29.973274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:29.973274Z digest=sha256:5470bff2de1c19eaec89a3d0c43d8ab618b612297950381d3c98231c0fe74abd

Observation 6ee79471-7856-406b-869e-86add7e524e6 · outbound

This paper cites Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.028045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.028045Z digest=sha256:8b7c4d745dd9c2807f10b552ecb2c1fae5aa39255ba4560f436c858a021eda4c

Observation 50334ada-932d-4cbe-952a-57680ad08cab · outbound

This paper cites an unresolved cited work.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Unresolved cited work

Reference 9

Resolution
verified exact
doi, observed 2026-08-06T18:17:31.025486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T18:17:30.074271Z digest=sha256:017ce93ecd8e5fe450e7ee15eb7a61316d21739cab257aa73556ee6456d5bea4

Observation adcc2da6-36b9-48bc-ad55-27bcf2ebb472 · outbound

This paper cites CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.144622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.144622Z digest=sha256:d4d2dcbdb8015ac92470bcfe61b4291eb7c63432929e8724c753117f06b88ebd

Observation 91f9e931-b89c-4c62-a95c-59cd3fda9aa1 · outbound

This paper cites an unresolved cited work.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Unresolved cited work

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.220937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.220937Z digest=sha256:3899886a30cac9b83d7bb389655208978b265f4258940e95a604fd75010af2ac

Observation b01386a4-9e7b-49df-8454-d2390b9ef45b · outbound

This paper cites Proceedings of Machine Learning Research, vol.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Proceedings of Machine Learning Research, vol

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:17:31.933531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T18:17:30.287864Z digest=sha256:f7844af4b65497c2463694acfa443bbbec4715f74cd62ddf4c547e6ade75908e

Observation 316e5680-4332-4071-952e-c9fd654e1171 · outbound

This paper cites LLM-Pruner: On the Structural Pruning of Large Language Models.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.339991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.339991Z digest=sha256:ea33035eeba28896bc24c3dc6e2e1648aa1cfa8e979f50337e4dbba36169c247

Observation f0168627-8c53-408f-9776-629340b8ae8b · outbound

This paper cites an unresolved cited work.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:17:31.784969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T18:17:30.411116Z digest=sha256:de06e7d208ca35db587a84d51839318240ebeefd114a69afb019c2db37fefb3f

Observation a230b66e-ef87-44cb-99d4-09d63303f1c3 · outbound

This paper cites Pruning Convolutional Neural Networks for Resource Efficient Inference.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Pruning Convolutional Neural Networks for Resource Efficient Inference

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.500225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.500225Z digest=sha256:8975d4df955518aafd2905c8fe399362905b7e35ca74e253b90092d13b5daf5b

Observation 9f7bc0c5-bdc2-4da4-9206-6ea4aa18ce2e · outbound

This paper cites Generalized Slow Roll for Tensors.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Generalized Slow Roll for Tensors

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.586662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.586662Z digest=sha256:06c73b87daea38135b54ecbfe78b6fee6c6411d7112b6f0a926e6f756354d437

Observation 74785084-eeb8-4990-9c57-c8677a207fdf · outbound

This paper cites SparseInfer: Training-free Prediction of Activation Sparsity for Fast LLM Inference.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering SparseInfer: Training-free Prediction of Activation Sparsity for Fast LLM Inference

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:17:31.288946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T18:17:30.649767Z digest=sha256:b7b223bb745d253ea0f2d61ea9163380017e10f94df54e5f6b0943d00044f377

Observation 2950b28d-ac6b-4d06-9bbf-fcdf52566cca · outbound

This paper cites PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.724777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.724777Z digest=sha256:30efc625e472ac37c695d3d592bac40419b4c443e9bb1ea9c7e2ce73a514572c

Observation 65b6dae8-23c0-494b-ab5e-cd01df9a1525 · outbound

This paper cites Distilling Task-Specific Knowledge from BERT into Simple Neural Networks.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Distilling Task-Specific Knowledge from BERT into Simple Neural Networks

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.790700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.790700Z digest=sha256:3b29fcc9ad7a3a082987c7fdbfec8814380253b29b3e974fa9968cc726b9c2ee

Observation 5cdc3ae1-7fa3-4d76-9e04-9725b67bb886 · outbound

This paper cites an unresolved cited work.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering Unresolved cited work

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.860934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.860934Z digest=sha256:c97fd3cbcfa8c270c2829bd97bb6dfad9468e7996df9fad3332f9c154118fbb6

Pith citing papers

No inbound Pith citation observations are available.