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Paper Citation Record · LEDGER

SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression

As of 13 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2604.03258.

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

pith.paper-citation-record.v1
2604.03258 v1

Coverage vector

measured 4 of 4 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-15T12:43:57.572912Z

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

4 of 4 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b234c5ff-8a7a-46b3-84b3-70822a73f37d · outbound

This paper cites From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications.

SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-15T12:45:37.370437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-15T12:43:57.572912Z digest=sha256:f99b6b132c6e29d5ccdeba7d15213efb9282f7ff64e29dddf8b6bae99bcb7888

Observation 88a23b88-fecf-46ad-b803-4bc67325a691 · outbound

This paper cites ShortGPT: Layers in Large Language Models are More Redundant Than You Expect.

SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T12:45:37.362705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-15T12:43:57.572912Z digest=sha256:1d418db6df198fa7a7d5ae9cb8002363226359082b70e8246905a34ba3265c76

Observation 05194e89-7f08-4481-b9dc-268727723159 · outbound

This paper cites Pointer Sentinel Mixture Models.

SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression Pointer Sentinel Mixture Models

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-05-15T12:45:37.366144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-15T12:43:57.572912Z digest=sha256:a0990fbb3120afc9fdf42ac07ba0a815908c6ea89e729502f6c13a51d5e0a510

Observation 699cbf75-5f8d-4795-9c79-8dc26dce6c4d · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression OPT: Open Pre-trained Transformer Language Models

Reference 4

Resolution
metadata mismatch
local_arxiv, observed 2026-05-15T12:45:37.374987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-15T12:43:57.572912Z digest=sha256:4b0c0e27f1ae4d983b4a72ae219ea1d9ddc0438e568aab2dcb69cf27535f09c6

Pith citing papers

No inbound Pith citation observations are available.