Pith. sign in

Paper Citation Record · LEDGER

Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2308.10168.

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

pith.paper-citation-record.v1
2308.10168 v2

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 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:01:42.135251Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T01:06:50.438061Z

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 3c8d72ec-19d8-43a9-a350-d4969db2faea · inbound

A Survey of Hallucination in Large Foundation Models cites this paper.

A Survey of Hallucination in Large Foundation Models Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-16T15:21:01.011099Z

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.

source=arxiv_source observed=2026-05-16T15:21:00.778049Z digest=sha256:092dded14e40c1350891b0d2ba01bf6a5643feba8e73ae89c4525fdfa4ca7d22

Observation 6f4afdd9-f1d6-4cc1-b636-5ec756a7330d · inbound

Chain-of-Verification Reduces Hallucination in Large Language Models cites this paper.

Chain-of-Verification Reduces Hallucination in Large Language Models Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

Reference 164

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:06:50.440450Z

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.

source=arxiv_source observed=2026-05-18T01:06:49.811982Z digest=sha256:eba289042f715e01ce65b0de1453dea27492c0f17ba53fba407bdbfc8fd3914a

Observation 83fff118-d83c-4b31-83f0-38021169b79a · inbound

A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models cites this paper.

A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:15:13.348845Z

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.

source=arxiv_source observed=2026-05-15T19:15:12.378496Z digest=sha256:a428b78e7805fb4328abe1dc71ab9c6f6307715a98bc9d1788f2f52298fa6df1

Observation e15a96db-a0dd-47b1-8040-42271509d9c0 · inbound

ExploreGS: Explorable 3D Scene Reconstruction with Virtual Camera Samplings and Diffusion Priors cites this paper.

ExploreGS: Explorable 3D Scene Reconstruction with Virtual Camera Samplings and Diffusion Priors Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T23:01:42.135251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:01:42.135251Z digest=sha256:466c07b7191bc743c5bb0a1cb40b82e755ee7a3a062951472f7064dd9f694e67

Observation 2393c8eb-35e1-41a8-a53d-83d21a05af4d · inbound

Identifying Origins of Place Names via Retrieval Augmented Generation cites this paper.

Identifying Origins of Place Names via Retrieval Augmented Generation Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T13:01:09.048504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:01:09.048504Z digest=sha256:39cd0ade44143141b5f8397020adc541fc047a4ec5d8831e7033830d08419752

Observation aa7816b3-e9ef-409c-b8e4-3ec3f262a682 · inbound

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval cites this paper.

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:51:10.612867Z

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.

source=arxiv_source observed=2026-05-10T05:43:04.813867Z digest=sha256:b1027bbf6b74c8b968e06b2d03ebebd4165c7c1a54838a92d473c05e32c30e5d

Observation 6d5cbfd1-9b5a-47bb-9620-76afa414a411 · inbound

SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model cites this paper.

SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:30:55.912974Z

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.

source=pdf_text observed=2026-05-11T01:19:42.892343Z digest=sha256:bee8b50104125790c4a931529672502cca9514d2a3c13da8ecf7cde26b991e2b