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Paper Citation Record · LEDGER

Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2505.02639.

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

pith.paper-citation-record.v1
2505.02639 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:31:06.262617Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:37:56.679709Z

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 7f5e2e33-4678-434c-9c0c-6169146c40a5 · inbound

DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning cites this paper.

DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T19:31:06.262617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:31:06.262617Z digest=sha256:cc7018029a154c03f671f9f56504347b82f5e22f60f6c220771e9027ae198586

Observation 8749df3f-be77-48ee-bae8-dce10ebf232d · inbound

Augmenting Molecular Language Models with Local $n$-gram Memory cites this paper.

Augmenting Molecular Language Models with Local $n$-gram Memory Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:37:56.680996Z

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.

source=arxiv_source observed=2026-06-27T09:57:12.398344Z digest=sha256:325d616ab8a44462175049edabc1a328e0b667be273def75a8e2068921f5d2aa