Paper Citation Record · LEDGER

SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2408.15545.

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

pith.paper-citation-record.v1
2408.15545 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:53:48.805092Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:32:32.897241Z

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 20623bd4-0580-4d1a-934f-5d7a4bc645b0 · inbound

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

Large language models for automated scholarly paper review: A survey SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T19:16:12.807292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9de263b1-2e74-46f2-9b23-f5dce2ebfe53 · inbound

LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient cites this paper.

LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T18:09:01.642749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 729eb361-cb9f-49de-bae8-d3c692acdf64 · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

Reference 100

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:32:32.900477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 79858c9c-0bee-4edc-9b70-367fcef93ae7 · inbound

AdaParse: An Adaptive Parallel PDF Parsing and Resource Scaling Engine cites this paper.

AdaParse: An Adaptive Parallel PDF Parsing and Resource Scaling Engine SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T10:53:48.805092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.