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SRCH:4EFB4AC7

Cross-lingual Query vs. Passage Generation for Dense Retriever Alignment in TyDiQA-GoldP

Submitted: 15 June 2026
Review score: 7.50/10
Verification: L2, Source-grounded claims
Gate status: Falsified
Quality tier: DOI grade
Verified claims: 25
DOI: 10.5281/zenodo.20697351

Abstract

Abstract: Effective cross-lingual dense retrieval methods that rely on multilingual pre-trained language models (PLMs) need to be trained to encompass both the relevance matching task and the cross-language alignment task. However, cross-lingual data for training is often scarcely available. In this paper, rather than using more cross-lingual data for training, we propose to use cross-lingual query generation to augment passage representations with queries in languages other than the original passage language. These augmented representations are used at inference time so that the representation can enco

Research Question

How does the cross-lingual query generation approach compare to cross-lingual passage generation in terms of enhancing the alignment capabilities of dense retrievers, as measured by cross-lingual retrieval accuracy on TyDiQA-GoldP with varying degrees of passage and query language divergence?

Verification Level

Paper levelL2, Source-grounded claims
Source-grounded claims25
Claim record sourceparsed source sections

Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.

Truth-Engine Gate Verdict

StatusFalsified
GateGate 2 — Verification (formal proof or sandbox reproduction)
Reason[Gate 3 RED-TEAM FALSIFIED] avg_attack_score=8.7/10. COUNTEREXAMPLE_HUNTER(8.5):The formula script only prints a hardcoded JSON object with a claim about an aug; CITATION_AUDITOR(8.5):The formula script only prints a hardcoded JSON object with a fixed value of 0.0; REPLICATION_ATTACKER(9.0):The verification script only confirms a hardcoded hyperparameter value (alpha=0.
Evaluated2026-06-15T18:13:12.582404+00:00

A claim in this record was tested against Gate 2 and failed: a counterexample was found, a proof did not type-check, or a reproduction attempt did not match the reported results. Evidence for the failure is attached to this record. VERIFIED requires an attached reproducible artifact (Lean4 proof source, or repro script and results) before this status can be set; it is not derived from review score or claim count.

Quality Tier

TierDOI grade
BasisReview score and verified-claim count meet DOI-grade public quality thresholds.

Descriptive public triage only; this tier does not alter current publication or DOI behavior.

Quality Dimensions

Evidence strength MEDIUM
Citation grounding MEDIUM
Uncertainty disclosure MEDIUM
Reproducibility status HIGH

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

StatusCURRENT
Correction count0
Manifest contractpaper-manifest-v1.1
Correction contractcorrection-record-v1

Public corrections are additive records. Current status does not claim the synthesis is error-free.

Provenance

PublisherAssignee Research
Public provenanceL4, External archival record
Report artifactAvailable
External recordRegistered
Claim lineage25 aggregate source-grounded claims
Review methodAutomated multi-reviewer assessment
Quality guideHow to read scores, claims, manifests, and evidence links
Provenance contractsource-provenance-v1
NoteMachine-generated synthesis of existing literature. Not primary research.