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Paper Citation Record · LEDGER

C-ICL: Contrastive In-context Learning for Information Extraction

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.11254.

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

pith.paper-citation-record.v1
2402.11254 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 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:12:35.728961Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T07:34:21.323323Z

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 bca7aa42-f059-47d8-b0c3-7294a4b38c9d · inbound

SkillVerse : Assessing and Enhancing LLMs with Tree Evaluation cites this paper.

SkillVerse : Assessing and Enhancing LLMs with Tree Evaluation C-ICL: Contrastive In-context Learning for Information Extraction

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:35.728961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:12:35.728961Z digest=sha256:2798528a6a8c3fcea9373a7adc188e7e0cc74d426980ace8c371d242559abd57

Observation 170493a7-615f-41d0-a268-77b8e4f05b7d · inbound

Demystifying Feature Requests: Leveraging LLMs to Refine Feature Requests in Open-Source Software cites this paper.

Demystifying Feature Requests: Leveraging LLMs to Refine Feature Requests in Open-Source Software C-ICL: Contrastive In-context Learning for Information Extraction

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T16:26:35.066390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:26:35.066390Z digest=sha256:519ffadb619fa8c15d3dbd46134e733933674db9de0a6becbfcfb667633b4065

Observation fe0170d6-e758-482d-a8c8-b48fd24af426 · inbound

LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction cites this paper.

LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction C-ICL: Contrastive In-context Learning for Information Extraction

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:34:21.324917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T07:33:12.712241Z digest=sha256:a27df1637a7737a4f13531afc97bcb8f4f7eecb3e6cb22fe769aacd7c424d75b

Observation 1dd5cb85-30a2-492f-a1cf-dd5c649f36ab · inbound

LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction cites this paper.

LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction C-ICL: Contrastive In-context Learning for Information Extraction

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-30T22:49:42.939870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T22:49:42.939870Z digest=sha256:05cf61cd9a305f28022db789270594521e2403e5050db085bb8a8e5f7a08dbf6

Observation 352f91bb-1f0a-494e-bc32-7e23c11dded1 · inbound

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models cites this paper.

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models C-ICL: Contrastive In-context Learning for Information Extraction

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-30T17:59:31.466358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T17:59:31.466358Z digest=sha256:0ee9ea378046cf73b9a7e865cc1b030c31d18e1dcbbaf0f6929382bd2b763bff