To RAG or Not to RAG? Rethinking Multilingual Spelling Correction at Global Scale

Hybrid Retrieval for Indic Language Question Answering using an Improved RAG Pipeline

Although Large Language Models (LLMs) have progressed significantly, Retrieval-Augmented Generation (RAG) still falls short for under-resourced Indic languages. Existing embedding systems, built primarily for English, face issues with script mismatches and limited word coverage, leading to near-complete retrieval failu...

Rethinking Knowledge Retrieval for Generation: A Survey on RAG Architectures and Applications

Large Language Models (LLMs) have demonstrated remarkable fluency and versatility across natural language tasks but remain fundamentally limited by their static knowledge and susceptibility to hallucinations, especially in domains requiring up to date or attribute grounded information. Retrieval Augmented Generation (R...

Investigating the Role of Reasoning-Language Alignment in Monolingual Retrieval-Augmented Generation

Reasoning traces improve large language models (LLMs), but current models are trained to reason mostly in English. It has been shown that forcing a model to reason in another language degrades accuracy, even when the reasoning language matches the language of the prompt -- but only for a setting where the model reasons...

Cross-Lingual Indirect Prompt Injection Across Retrieval, Reranking, And Generation In Multilingual RAG

The results indicate that multilingual RAG security depends on several linked stages rather than generation alone, and indicates that multilingual RAG security depends on several linked stages rather than generation alone.

Evaluating RAG approaches for Question Answering

RETRIEVAL BEATS FINE-TUNING: ADAPTING A KAZAKH SMALL LANGUAGE MODEL FOR HISTORICAL QUESTION ANSWERING

Large language models (LLMs) have shown a strong ability to solve a wide range of language tasks. However, they became less practical for subject-specific applications, especially when dealing with low-resource languages. This paper shows an example of adaptation of small language models (SLMs) to solve subject-specifi...