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cs.CL2026
RACER: Retrieval-Augmented Contextual Rapid Speculative Decoding
Zihong Zhang, Zuchao Li, Lefei Zhang +2
Autoregressive decoding in Large Language Models (LLMs) generates one token per step, causing high inference latency. Speculative decoding (SD) mitigates this through a guess-and-v…
cs.CL2026
SongSage: A Large Musical Language Model with Lyric Generative Pre-training
Jiani Guo, Jiajia Li, Jie Wu +3
Large language models have achieved significant success in various domains, yet their understanding of lyric-centric knowledge has not been fully explored. In this work, we first i…
cs.CL2026
MERMAID: Memory-Enhanced Retrieval and Reasoning with Multi-Agent Iterative Knowledge Grounding for Veracity Assessment
Yupeng Cao, Chengyang He, Yangyang Yu +2
Assessing the veracity of online content has become increasingly critical. Large language models (LLMs) have recently enabled substantial progress in automated veracity assessment,…