Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.18676.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:58:42.740792Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T07:22:09.157747Z
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 c1e765ee-72ec-4efa-85fa-3c70dc181fac · inbound
Search-o1: Agentic Search-Enhanced Large Reasoning Models cites this paper.
Search-o1: Agentic Search-Enhanced Large Reasoning Models Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T17:36:27.688708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation af31926c-5416-4ee3-befe-76e55560be83 · inbound
Optimizing Web-Based AI Query Retrieval with GPT Integration in LangChain A CoT-Enhanced Prompt Engineering Approach cites this paper.
Optimizing Web-Based AI Query Retrieval with GPT Integration in LangChain A CoT-Enhanced Prompt Engineering Approach Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:58:42.740792Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62bc9beb-a0b3-48e9-ab2c-5080788b74d6 · inbound
MultiFinRAG: An Optimized Multimodal Retrieval-Augmented Generation (RAG) Framework for Financial Question Answering cites this paper.
MultiFinRAG: An Optimized Multimodal Retrieval-Augmented Generation (RAG) Framework for Financial Question Answering Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T07:22:09.160559Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1e8fcf3f-c4e8-4be5-a6eb-d2e81c0a4a28 · inbound
Leveraging LLM-Assisted Query Understanding for Live Retrieval-Augmented Generation cites this paper.
Leveraging LLM-Assisted Query Understanding for Live Retrieval-Augmented Generation Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:31:36.736621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.