Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.18424.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:02:17.579702Z
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 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.