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cs.CL2026
SelfJudge: Faster Speculative Decoding via Self-Supervised Judge Verification
Kanghoon Yoon, Minsub Kim, Sungjae Lee +6
Speculative decoding accelerates LLM inference by verifying candidate tokens from a draft model against a larger target model. Recent judge decoding boosts this process by relaxing…
cs.CL2026
Affine-Scaled Attention: Towards Flexible and Stable Transformer Attention
Jeongin Bae, Baeseong Park, Gunho Park +7
Transformer attention is typically implemented using softmax normalization, which enforces attention weights with unit sum normalization. While effective in many settings, this con…
cs.CL2025
Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models
Seungcheol Park, Jeongin Bae, Beomseok Kwon +5
How can we quantize large language models while preserving accuracy? Quantization is essential for deploying large language models (LLMs) efficiently. Binary-coding quantization (B…