Paper Citation Record · LEDGER

G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2405.12915.

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

pith.paper-citation-record.v1
2405.12915 v2

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 2026-08-20T06:33:59.587034+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:12:38.974313Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T20:17:54.588563Z

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 47c97993-45c2-4a4b-b850-d5115425a42f · inbound

Ensembles of Low-Rank Expert Adapters cites this paper.

Ensembles of Low-Rank Expert Adapters G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-09T20:29:52.611083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09014e26-d1ca-431d-9aa2-429fd75c3604 · inbound

RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection cites this paper.

RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T23:12:38.974313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55abdeae-16b6-42b7-8d79-79383b9b873c · inbound

Daunce: Data Attribution through Uncertainty Estimation cites this paper.

Daunce: Data Attribution through Uncertainty Estimation G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:13.778326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05f842ac-fb1c-4dfe-9e27-5c641721c015 · inbound

Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters cites this paper.

Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:34.192096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77eedcc7-db13-43f2-a5fa-be32324e5813 · inbound

Seed LiveInterpret 2.0: End-to-end Simultaneous Speech-to-speech Translation with Your Voice cites this paper.

Seed LiveInterpret 2.0: End-to-end Simultaneous Speech-to-speech Translation with Your Voice G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T14:52:43.055284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b037cf95-413f-4476-b9e1-49f4121dbd6e · inbound

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation cites this paper.

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:23.343005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30d705c9-330d-4a31-b414-bfa5a7204743 · inbound

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms cites this paper.

From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:17:54.676371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.