Paper Citation Record · LEDGER

Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2409.02727.

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

pith.paper-citation-record.v1
2409.02727 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:49:39.770964Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 152684cd-fcfb-4f2d-bc3d-68246039e0c7 · inbound

The SuperActivator Mechanism: Transformers Concentrate Reliable Concept Signals in the Tail cites this paper.

The SuperActivator Mechanism: Transformers Concentrate Reliable Concept Signals in the Tail Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-03T18:33:08.387238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e0582b5-d228-4703-97d3-dc1607de51c5 · inbound

Xray-Visual Models: Scaling Vision models on Industry Scale Data cites this paper.

Xray-Visual Models: Scaling Vision models on Industry Scale Data Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T22:25:59.821475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c436d3e0-fa89-4e4b-8127-2a7dc6fed07b · inbound

Behavior-Aware Item Modeling via Dynamic Procedural Solution Representations for Knowledge Tracing cites this paper.

Behavior-Aware Item Modeling via Dynamic Procedural Solution Representations for Knowledge Tracing Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:55:59.464339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4ffef57a-39c4-491a-8344-0b79e4db3752 · inbound

LLM Safety From Within: Detecting Harmful Content with Internal Representations cites this paper.

LLM Safety From Within: Detecting Harmful Content with Internal Representations Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T12:20:23.048764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 41c2f5d0-3ed8-4675-bd32-9a1d44025fc2 · inbound

Health System Scale Semantic Search Across Unstructured Clinical Notes cites this paper.

Health System Scale Semantic Search Across Unstructured Clinical Notes Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-09T02:34:41.822862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3dd3eb30-5b97-4c1e-a028-dd6587f28134 · inbound

POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles cites this paper.

POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 111

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:45:55.301912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fa9cc33e-5ac7-47f1-b295-eb61c8aad2fc · inbound

Frequency-Domain Latent Attention Gating for Cross-Domain Token Aggregation cites this paper.

Frequency-Domain Latent Attention Gating for Cross-Domain Token Aggregation Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T20:21:13.118575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cdde1150-0e33-4a28-a8b7-68b79f9c2b2b · inbound

Generative Archetype-Grounded Item Representations for Sequential Recommendation cites this paper.

Generative Archetype-Grounded Item Representations for Sequential Recommendation Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-07-03T07:57:45.011698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 941fbb29-3dcb-4c7f-8960-70744e5d670e · inbound

IMFuse: Instance-Aware Multi-Layer Fusion for LLM-Enhanced Sequential Recommendation cites this paper.

IMFuse: Instance-Aware Multi-Layer Fusion for LLM-Enhanced Sequential Recommendation Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-30T14:25:02.689443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7d64360-d9d8-414d-8eea-cc5e231b2f31 · inbound

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes cites this paper.

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T07:49:39.770964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.