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Paper Citation Record · LEDGER

Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.13091.

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

pith.paper-citation-record.v1
2305.13091 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:20:45.280630Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T17:05:50.412658Z

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 bced2d0e-eae9-47cf-b325-2123d8b20419 · inbound

ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate cites this paper.

ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-13T13:03:18.846385Z

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=2026-05-13T13:03:18.765496Z digest=sha256:6bfdcbb9e7e7152866731e584bb13f2bf5245a43d3f28547e56c9767d016bc1d

Observation bc7184f1-6fa9-4d17-bd54-9686c59ee9a2 · inbound

Instruction-Following Evaluation for Large Language Models cites this paper.

Instruction-Following Evaluation for Large Language Models Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-24T05:36:00.902353Z

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=2026-05-24T05:34:04.002648Z digest=sha256:495e846b004ff583b66ed08b33e17dc71af9140582b669e547eb9c4daf133fa1

Observation 1679e012-7deb-4c66-ab35-cb898c272f87 · inbound

TF1-EN-3M: Three Million Synthetic Moral Fables for Training Small, Open Language Models cites this paper.

TF1-EN-3M: Three Million Synthetic Moral Fables for Training Small, Open Language Models Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-22T19:01:57.803476Z

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=2026-05-22T19:01:42.307514Z digest=sha256:7bc8783acbf7018bbcd0be8f922907f55c408fceed1d4e540dd059640d37ebe5

Observation 1b0d29de-a677-4d6c-a8f0-18697422ffe8 · inbound

AutoRAG-LoRA: Hallucination-Triggered Knowledge Retuning via Lightweight Adapters cites this paper.

AutoRAG-LoRA: Hallucination-Triggered Knowledge Retuning via Lightweight Adapters Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T18:20:45.280630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:20:45.280630Z digest=sha256:636dc371283d52f944e2f417f4bce042bcf514d4a330424644874299b6dd2908

Observation 6a196736-59e8-40db-ab5a-408f9f8b9435 · inbound

A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs cites this paper.

A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization

Reference 250

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T17:05:50.414154Z

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=2026-06-29T04:20:31.649036Z digest=sha256:f41a084e5eaae24061ad5b61ba854395db3c8c4c84961d4f6dfb60b788779bf0