Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.10626.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-31T23:18:49.325332Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T03:06:30.499219Z
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 47bd90fa-a559-446c-9539-656f87f5a6cb · inbound
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs cites this paper.
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T12:36:50.124659Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 779fcbd6-30cd-4ec2-ba59-0b6801e7814f · inbound
CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning cites this paper.
CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Reference 56
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T13:20:57.509818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation f49a1b2c-d8df-4e71-961b-d48f88d1effd · inbound
Teaching LLMs Brazilian Healthcare: Injecting Knowledge from Official Clinical Guidelines cites this paper.
Teaching LLMs Brazilian Healthcare: Injecting Knowledge from Official Clinical Guidelines Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:06:06.969540Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 43ead258-7ddd-45b1-a555-c125380770d0 · inbound
ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models cites this paper.
ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Reference 27
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T03:06:30.500938Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 21f0b02f-db2e-4283-be82-cb267a806840 · inbound
MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition cites this paper.
MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:18:49.325332Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.