Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
BlockPruner: Fine-grained Pruning for Large Language Models
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2406.10594.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:13:29.129132Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T03:19:31.599473Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 1e8944fd-bf88-40f1-be17-769b576e1fe1 · inbound
Reassessing Layer Pruning in LLMs: New Insights and Methods cites this paper.
Reassessing Layer Pruning in LLMs: New Insights and Methods BlockPruner: Fine-grained Pruning for Large Language Models
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:13:29.129132Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83dc59c8-aacf-4857-b220-cf515fee7487 · inbound
FTP: A Fine-grained Token-wise Pruner for Large Language Models via Token Routing cites this paper.
FTP: A Fine-grained Token-wise Pruner for Large Language Models via Token Routing BlockPruner: Fine-grained Pruning for Large Language Models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:57:27.656730Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1f9c56b-72c8-4fb1-8ffe-3db3596a63db · inbound
Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN cites this paper.
Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN BlockPruner: Fine-grained Pruning for Large Language Models
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:53:33.916955Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 555b6359-a12b-4642-b610-44ceac191251 · inbound
MultiPruner: Balanced Structure Removal in Foundation Models cites this paper.
MultiPruner: Balanced Structure Removal in Foundation Models BlockPruner: Fine-grained Pruning for Large Language Models
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T19:36:11.932839Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1da7d73-9e1b-4f14-927c-97920d2617e2 · inbound
RAP: Runtime Adaptive Pruning for LLM Inference cites this paper.
RAP: Runtime Adaptive Pruning for LLM Inference BlockPruner: Fine-grained Pruning for Large Language Models
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T13:21:35.624281Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b491ff1c-699f-4a69-9c7a-544990760c87 · inbound
Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning cites this paper.
Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning BlockPruner: Fine-grained Pruning for Large Language Models
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:54:18.017977Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fef4010-0458-46f8-96b0-18265d020eee · inbound
Beyond Manually Designed Pruning Policies with Second-Level Performance Prediction: A Pruning Framework for LLMs cites this paper.
Beyond Manually Designed Pruning Policies with Second-Level Performance Prediction: A Pruning Framework for LLMs BlockPruner: Fine-grained Pruning for Large Language Models
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:01:16.402118Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f076a612-3a6d-4de1-9f4f-f58f04997241 · inbound
AQUA: Attention via QUery mAgnitudes for Memory and Compute Efficient Inference in LLMs cites this paper.
AQUA: Attention via QUery mAgnitudes for Memory and Compute Efficient Inference in LLMs BlockPruner: Fine-grained Pruning for Large Language Models
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T17:05:55.047920Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 593fc168-27a7-42b8-b745-ccab2b27d16b · inbound
Activation- and Influence-Aware Ranks (AIR): Function-Preserving SVD Compression for LLMs cites this paper.
Activation- and Influence-Aware Ranks (AIR): Function-Preserving SVD Compression for LLMs BlockPruner: Fine-grained Pruning for Large Language Models
Reference 206
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T03:19:31.601301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation eae9f883-b582-45c3-a052-d1e00201dc5e · inbound
Celty: SpMspV GPU Kernel and SIMT Co-Design for Efficient Dual-Sparse LLM Inference cites this paper.
Celty: SpMspV GPU Kernel and SIMT Co-Design for Efficient Dual-Sparse LLM Inference BlockPruner: Fine-grained Pruning for Large Language Models
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T00:09:29.407949Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.