Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-09T07:15:50.133587Z
Paper Citation Record · LEDGER
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning
As of 20 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2607.07557.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T01:03:27.178402Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T01:03:31.456510Z
Reference resolution
27 of 27 outbound references displayed
- verified exact1
- verified fuzzy14
- unresolved1
- parse uncertain0
- malformed identifier0
- metadata mismatch11
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 6a74a955-ec21-464d-93ce-7fac425d9fc2 · outbound
This paper cites Advances in neural information processing systems , volume=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Advances in neural information processing systems , volume=
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.228177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f663a40c-335f-4aad-99e2-cafa0af3314b · outbound
This paper cites PaLM: Scaling Language Modeling with Pathways.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning PaLM: Scaling Language Modeling with Pathways
Reference 2
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.174928Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5639d8fa-c0e9-417e-b0c7-dff11af5d970 · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning LLaMA: Open and Efficient Foundation Language Models
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.168693Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f77dd2a4-2fbd-46de-9b41-64d1d8d85395 · outbound
This paper cites Journal of Machine Learning Research , volume=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Journal of Machine Learning Research , volume=
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.221170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e7343406-b679-4d17-848a-7342a0b86274 · outbound
This paper cites Advances in neural information processing systems , pages=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Advances in neural information processing systems , pages=
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.244867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 3b1b7d12-6888-4f46-bf94-56996568d230 · outbound
This paper cites Advances in neural information processing systems , pages=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Advances in neural information processing systems , pages=
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.239075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5a20f46f-a478-46c6-955c-15fcb14da5df · outbound
This paper cites SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot
Reference 7
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.163023Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2bc277b6-8600-4d6e-bae7-6fc5a07dd8e5 · outbound
This paper cites A Simple and Effective Pruning Approach for Large Language Models.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning A Simple and Effective Pruning Approach for Large Language Models
Reference 8
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.196767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 562d79ca-6318-4440-a7dc-1d6f3fc6e665 · outbound
This paper cites Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
Reference 9
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.180815Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cbd78e39-63fe-45e7-a617-f222a1e79e22 · outbound
This paper cites Advances in neural information processing systems , volume=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Advances in neural information processing systems , volume=
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.247693Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4f7c88c5-2b81-4888-938e-97472b07bd0b · outbound
This paper cites Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.253566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2f300183-cc21-4f51-ab88-c901bfe3e3b2 · outbound
This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.232030Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation af32c5ea-1cbd-4f8c-b6e6-6e5b6b2f4eeb · outbound
This paper cites International Conference on Learning Representations , year=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning International Conference on Learning Representations , year=
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.241795Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1118065d-29a9-4e80-b2dd-3256e62b90ca · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Advances in Neural Information Processing Systems , volume=
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.256819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2629a558-3966-41c0-95f2-2db890f38932 · outbound
This paper cites Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T07:16:04.147759Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 66a076d9-44b3-4178-8ce2-6b33414b96fe · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Advances in Neural Information Processing Systems , volume=
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.224568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 18df66cb-6e13-410c-9756-ba4d85f5fa9a · outbound
This paper cites SliceGPT: Compress Large Language Models by Deleting Rows and Columns.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Reference 17
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.206433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 54cfb100-cc16-4e96-9fd5-5d63a240f6c9 · outbound
This paper cites International Conference on Learning Representations , year=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning International Conference on Learning Representations , year=
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.262265Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cade172c-629a-4fd1-9d5e-28713ce8f0ed · outbound
This paper cites Faster gaze prediction with dense networks and Fisher pruning.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Faster gaze prediction with dense networks and Fisher pruning
Reference 19
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.153672Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 400c6307-dab2-4c98-9956-0c8bfff0d564 · outbound
This paper cites LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning
Reference 20
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.191634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 569525ea-2a68-4734-ac65-a2a754f7df68 · outbound
This paper cites Pointer Sentinel Mixture Models.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Pointer Sentinel Mixture Models
Reference 21
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.201755Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c30846b4-42a4-4ab3-bf45-41f8ea60f783 · outbound
This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Proceedings of the AAAI Conference on Artificial Intelligence , volume=
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.235867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 29ba3800-ea07-4dcc-9318-ab0fe9f173c2 · outbound
This paper cites Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics , pages=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics , pages=
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.259697Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8144a2aa-1545-4f47-baf0-2b533f87bb9f · outbound
This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions
Reference 24
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.158216Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ec3affd4-8c04-4339-817f-03d9e47d7c3c · outbound
This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 25
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T07:16:04.186198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d2930964-d68d-4b1f-b848-6e33656bbb45 · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Advances in Neural Information Processing Systems , volume=
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T07:16:04.250260Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cdf9f81e-66af-482f-9f30-b39e38a1a082 · outbound
This paper cites an unresolved cited work.
PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning Unresolved cited work
Reference 27
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T07:16:04.217693Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
Observation 1a880480-ac7b-4bbe-be50-505c8a2d4e2a · inbound
When Compression Scores Cannot Decide: Information Boundaries for Group-Robust LLM Pruning cites this paper.
When Compression Scores Cannot Decide: Information Boundaries for Group-Robust LLM Pruning PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning
Reference 21
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T01:03:31.548017Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.