Computational & Cross-Linguistic Research

Advancing AI-driven language understanding across linguistic boundaries to build a truly global, interoperable knowledge infrastructure.

Bridging Languages, Scaling Knowledge

Our Computational & Cross-Linguistic Research division develops next-generation NLP architectures, multilingual alignment techniques, and low-resource language modeling frameworks. These tools power Aevum Encyclopedia's ability to ingest, verify, and connect knowledge across 140+ languages.

We focus on overcoming linguistic bias, improving cross-lingual transfer, and creating open benchmarks that measure true semantic equivalence rather than surface-level translation accuracy.

42
Active Research Grants
8.2B
Parameters Trained
140+
Languages Supported
12
Open Datasets Released

Research Pillars

Targeted investigations designed to solve fundamental bottlenecks in multilingual AI and cross-lingual knowledge representation.

🌐

Multilingual NLP Architectures

Designing transformer variants optimized for high-dimensional semantic spaces, enabling zero-shot and few-shot cross-lingual transfer without catastrophic forgetting.

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Cross-Linguistic Knowledge Transfer

Developing contrastive alignment techniques that map concepts across languages with divergent syntax, morphology, and cultural framing.

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Low-Resource Language Modeling

Pioneering data augmentation, phonetic transliteration pipelines, and transfer learning strategies to achieve parity for underrepresented languages.

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Computational Semantics & Ontology

Building dynamic knowledge graphs that evolve with language, integrating lexical semantics, pragmatic context, and encyclopedic metadata.

Research Methodology

A rigorous, reproducible pipeline from hypothesis to open-source deployment.

01

Corpus Mining & Curation

We aggregate, clean, and align parallel and pseudo-parallel corpora from academic, web, and indigenous language archives, ensuring ethical sourcing and representational balance.

02

Contrastive Pre-Training

Models are trained on cross-lingual contrastive objectives, forcing shared latent representations for equivalent concepts while preserving language-specific nuances.

03

Cross-Lingual Evaluation

We benchmark using XNLI, XSTS, and custom Aevum semantic equivalence tasks, measuring precision, recall, and cultural context preservation.

04

Open Release & Integration

All models, datasets, and evaluation scripts are published under permissive licenses and directly integrated into Aevum's knowledge graph pipeline.

Selected Publications & Datasets

CrossLinguaBench: A Unified Framework for Multilingual Semantic Alignment

ACL 2024 • J. Chen, M. Al-Farsi, R. Okoye
Dataset

Zero-Shot Concept Transfer in Morphologically Rich Languages

EMNLP 2023 • S. Nair, L. Vogel, T. Tanaka
Paper

Low-Resource Phonetic Transliteration for Agglutinative Languages

NAACL 2023 • K. Mbaye, E. Sørensen
Paper

OpenPolyGlot-140: The Aevum Multilingual Corpus

arXiv:2402.8819 • Aevum Research Collective
Dataset

Collaborate With Our Team

We actively seek partnerships with universities, linguistic institutes, and open-source developers. Share your expertise or request access to our datasets.