Paper Citation Record · LEDGER

PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2404.18424.

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

pith.paper-citation-record.v1
2404.18424 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:18:08.070937Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T08:13:15.085848Z

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 15584337-1810-40e2-90e9-091f2312419c · inbound

2D Matryoshka Training for Information Retrieval cites this paper.

2D Matryoshka Training for Information Retrieval PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T12:18:08.070937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cc4bac8-48d1-45f7-b77d-cc458ff26a92 · inbound

PaSa: An LLM Agent for Comprehensive Academic Paper Search cites this paper.

PaSa: An LLM Agent for Comprehensive Academic Paper Search PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T19:28:32.376149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65419f29-8b3e-4bad-ae54-9ca12074b4fd · inbound

Estimating Commonsense Plausibility through Semantic Shifts cites this paper.

Estimating Commonsense Plausibility through Semantic Shifts PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:42:26.448858Z

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.

Observation f48b94ca-507d-4191-a4ed-859f9afd502c · inbound

A Comparative Study of Specialized LLMs as Dense Retrievers cites this paper.

A Comparative Study of Specialized LLMs as Dense Retrievers PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T20:02:17.579702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90319cfa-ef12-4e51-8dfd-3f65f01500aa · inbound

Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval cites this paper.

Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T13:50:12.927665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d9c8d62-7c6e-4271-81d2-82b9308fe5f4 · inbound

Attention Grounded Enhancement for Visual Document Retrieval cites this paper.

Attention Grounded Enhancement for Visual Document Retrieval PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-17T20:55:15.240115Z

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.

Observation 473b21b9-0573-41d2-85c4-bb8abb8c3811 · inbound

DocRetriever: A Plug-and-Play Framework for Multimodal Document Retrieval with Comprehensive Benchmark cites this paper.

DocRetriever: A Plug-and-Play Framework for Multimodal Document Retrieval with Comprehensive Benchmark PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:13:15.087365Z

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.