Paper Citation Record · LEDGER

Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2409.16605.

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

pith.paper-citation-record.v1
2409.16605 v1

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 2026-08-12T06:34:41.77262+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:16:12.818208Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T05:17:06.000428Z

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 04ba87ab-b3ad-4a55-a493-c845eb5b6c67 · inbound

Large language models for automated scholarly paper review: A survey cites this paper.

Large language models for automated scholarly paper review: A survey Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T19:16:12.818208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 223fbc23-14ca-4f85-ad09-6e498dc8c568 · inbound

How do Humans and Language Models Reason About Creativity? A Comparative Analysis cites this paper.

How do Humans and Language Models Reason About Creativity? A Comparative Analysis Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T05:23:59.941059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b573e2a7-450b-42fd-81be-d656ad67aeb2 · inbound

The Budget AI Researcher and the Power of RAG Chains cites this paper.

The Budget AI Researcher and the Power of RAG Chains Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T00:56:55.135563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ee96a8b-9c3f-4221-9e3b-7aa8858549dc · inbound

Mapping the Evolution of Research Contributions using KnoVo cites this paper.

Mapping the Evolution of Research Contributions using KnoVo Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T23:35:03.278625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3c58c4b-2d9e-450a-a7e5-50802b20076c · inbound

Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator cites this paper.

Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

Reference 93

Resolution: verified exact; arxiv_id, observed 2026-05-19T05:17:06.003946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7af2482d-3635-4a60-adfd-dc226230a87b · inbound

IDRBench: Understanding the Capability of Large Language Models on Interdisciplinary Research cites this paper.

IDRBench: Understanding the Capability of Large Language Models on Interdisciplinary Research Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:52:01.593275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f871bde8-5a13-4193-bd1e-afe97cd24df0 · inbound

Towards a Large Physics Benchmark cites this paper.

Towards a Large Physics Benchmark Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T12:34:57.610021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.