Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-22T15:48:05.377409Z
Paper Citation Record · LEDGER
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge
As of 10 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2505.09246.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T08:36:00.377754Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
21 of 21 outbound references displayed
- verified exact7
- verified fuzzy8
- unresolved4
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation acef55c3-37b4-47d0-8d79-82163b37e395 · outbound
This paper cites Can knowledge graphs reduce hallucinations in llms?: A survey.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Can knowledge graphs reduce hallucinations in llms?: A survey
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T15:51:46.733516Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4180fa76-1f59-40b3-b9fa-dcac4d3ed115 · outbound
This paper cites an unresolved cited work.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-05-22T15:51:46.720965Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f61f7408-c08b-4cfe-acbf-e039f32e32d1 · outbound
This paper cites 8 Xuemei Dong, Chao Zhang, Yuhang Ge, Yuren Mao, Yunjun Gao, Jinshu Lin, Dongfang Lou, et al.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge 8 Xuemei Dong, Chao Zhang, Yuhang Ge, Yuren Mao, Yunjun Gao, Jinshu Lin, Dongfang Lou, et al
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-22T15:51:45.821957Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d60062a8-052e-4fcf-b444-43be81bb5c98 · outbound
This paper cites Trapping LLM Hallucinations Using Tagged Context Prompts.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Trapping LLM Hallucinations Using Tagged Context Prompts
Reference 4
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-22T15:51:45.816078Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4cc35515-df5b-4542-8e4c-19d5ce4ef68a · outbound
This paper cites Knowledge Solver: Teaching LLMs to Search for Domain Knowledge from Knowledge Graphs.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Knowledge Solver: Teaching LLMs to Search for Domain Knowledge from Knowledge Graphs
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T15:51:45.827565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d2fad9fc-1a22-4173-8361-a209b2272451 · outbound
This paper cites Cypher: An evolving query language for property graphs.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Cypher: An evolving query language for property graphs
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T15:51:46.716995Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 89728378-73ec-4cd7-a65b-587bf630b3f5 · outbound
This paper cites an unresolved cited work.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-05-22T15:51:46.737198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation cde2dc6f-be71-422e-b358-1875c6600f2a · outbound
This paper cites Kundu and U.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Kundu and U
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T15:51:46.710202Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 17033909-3251-45fa-8d36-2388d2fcb32b · outbound
This paper cites Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Bases.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Bases
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T15:51:45.805560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 240db2c7-bd31-4c8d-a559-921119912eeb · outbound
This paper cites Multi-Field Adaptive Retrieval.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Multi-Field Adaptive Retrieval
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T15:51:45.811148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation cd2a0b60-60f2-404b-a422-6ed72da950eb · outbound
This paper cites Using multiple RDF knowledge graphs for enriching Chat- GPT responses.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Using multiple RDF knowledge graphs for enriching Chat- GPT responses
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T15:51:46.713285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation db18b05b-52c9-4a96-8eeb-7b40430112cf · outbound
This paper cites Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu
Reference 12
- Resolution
- verified exact
- doi, observed 2026-05-22T15:51:45.573744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 684dfcad-5b0c-439d-8303-cc8204a10628 · outbound
This paper cites Stephen E Robertson, Steve Walker, Susan Jones, Micheline M Hancock-Beaulieu, Mike Gatford, et al.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Stephen E Robertson, Steve Walker, Susan Jones, Micheline M Hancock-Beaulieu, Mike Gatford, et al
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T15:51:45.569760Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 8266e000-7a58-4899-a489-c1d20dd44d9b · outbound
This paper cites DanishShakeelandNitinJain.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge DanishShakeelandNitinJain
Reference 14
- Resolution
- verified exact
- doi, observed 2026-05-22T15:51:45.577454Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4318a434-361f-457e-b3ba-7c1e6b97e25e · outbound
This paper cites FACE-KEG: fact checking explained using knowledge graphs.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge FACE-KEG: fact checking explained using knowledge graphs
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T15:51:46.727536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2bfa3522-b44f-4934-b53c-686b3b1ca09d · outbound
This paper cites an unresolved cited work.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-05-22T15:51:46.744001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 648f9373-e157-4b8b-932c-f2e3f1fb4cf8 · outbound
This paper cites Avatar: Optimizing llm agents for tool usage via contrastive reasoning.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Avatar: Optimizing llm agents for tool usage via contrastive reasoning
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T15:51:46.740768Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 98d18c95-7f53-4ed2-90e6-dcb270d1d019 · outbound
This paper cites Hansi Yang, Qi Zhang, Wei Jiang, and Jianguo Li.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Hansi Yang, Qi Zhang, Wei Jiang, and Jianguo Li
Reference 18
- Resolution
- verified exact
- doi, observed 2026-05-22T15:51:45.581353Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e014f243-5851-4a7d-8f00-816c046ae9f4 · outbound
This paper cites Yasunaga, H.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Yasunaga, H
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T15:51:46.747272Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 489ca556-abf7-4574-bc29-e1a32155947f · outbound
This paper cites Zhuang, Z.
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T15:51:46.750591Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 022fb384-2e75-4526-ad25-a6687e216859 · outbound
This paper cites an unresolved cited work.
Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-05-22T15:51:46.724366Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Pith citing papers
Observation 3a863143-1c41-4cc1-92eb-c8a1ad837389 · inbound
When Thinking Before Retrieval Hurts: TraceBound Diagnostics for Adaptive Knowledge-Graph Retrieval cites this paper.
When Thinking Before Retrieval Hurts: TraceBound Diagnostics for Adaptive Knowledge-Graph Retrieval Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T08:36:00.377754Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.