3 papers
cs.CL2026
Cloud and On-Premises Deployment of Uzbek Legal RAG via Targeted Retriever Fine-Tuning
Tatul Danielyan, Mariam Avetisyan, Hrant Davtyan
Deploying large language models for legal question answering raises challenges that general-purpose leaderboards do not capture, particularly for low-resource languages and under h…
cs.RO2026
A Statistical Audit of Physical AI Benchmark Redundancy
Zaruhi Navasardyan, Hrant Davtyan
Physical AI models are evaluated on suites of benchmarks that differ across model reports, leaving the model-by-benchmark matrix sparse and the relationship between benchmarks unme…
cs.CL2026
Less is More: Adapting Text Embeddings for Low-Resource Languages with Small Scale Noisy Synthetic Data
Zaruhi Navasardyan, Spartak Bughdaryan, Bagrat Minasyan +1
Low-resource languages (LRLs) often lack high-quality, large-scale datasets for training effective text embedding models, hindering their application in tasks like retrieval-augmen…