10 papers
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…
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,…
End-to-end Contrastive Language-Speech Pretraining Model For Long-form Spoken Question Answering
Jiliang Hu, Zuchao Li, Baoyuan Qi +2
Significant progress has been made in spoken question answering (SQA) in recent years. However, many existing methods, including large audio language models, struggle with processi…
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…
INSEva: A Comprehensive Chinese Benchmark for Large Language Models in Insurance
Shisong Chen, Qian Zhu, Wenyan Yang +15
Insurance, as a critical component of the global financial system, demands high standards of accuracy and reliability in AI applications. While existing benchmarks evaluate AI capa…
SpindleKV: A Novel KV Cache Reduction Method Balancing Both Shallow and Deep Layers
Zicong Tang, Shi Luohe, Zuchao Li +4
Large Language Models (LLMs) have achieved impressive accomplishments in recent years. However, the increasing memory consumption of KV cache has possessed a significant challenge…