Grouped Value Attention
An attention variant that caches grouped values and reconstructs content keys on demand via a learned linear map absorbed into the query, cutting persistent KV cache by ~45-47% versus GQA with near-GQA accuracy
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An attention variant that caches grouped values and reconstructs content keys on demand via a learned linear map absorbed into the query, cutting persistent KV cache by ~45-47% versus GQA with near-GQA accuracy
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A mixture-of-experts layer on grouped-query attention that routes each token to a subset of query-head experts while keeping KV heads dense, matching GQA accuracy with half the query heads active and 1.7-1.8x faster long-context prefill
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A novel multimodal document chunking approach that leverages LMMs to process PDF documents in batches while maintaining semantic coherence and structural integrity
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Large Language Models designed to address this gap by seamlessly operating across Indonesian, English, and 11 regional languages in Indonesia
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This research introduces an innovative approach to enhance the accuracy of complex table queries in RAG-based systems
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This research introduces a comprehensive Bahasa text-to-speech (TTS) dataset and a novel TTS model, EnGen-TTS, designed to enhance the quality and versatility of synthetic speech in the Bahasa language
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