4 papers
LibraSpec: Dynamic Diffusion-Based Speculative Decoding via Marginal-Gain-Driven Optimization
Zexun Lin, Yuan Feng, Junlin Lv +2
Speculative decoding accelerates large language model inference by drafting multiple tokens for parallel verification, with efficiency critically determined by the speculative leng…
Repetition Mismatch: Why Data Mixture Experiments Don't Scale and How to Fix Them
Kevin Zhou, Lisa Alazraki, Kris Cao +1
Pre-training data mixtures are commonly tuned by running small-scale experiments and extrapolating to the target training budget. When high-quality data is scarce and must be repea…
SkewRoute: Training-Free LLM Routing for Knowledge Graph Retrieval-Augmented Generation via Score Skewness of Retrieved Context
Hairu Wang, Yuan Feng, Yukun Cao +2
Large language models excel at many tasks but often incur high inference costs during deployment. To mitigate hallucination, many systems use a knowledge graph to enhance retrieval…
Path Pooling: Training-Free Structure Enhancement for Efficient Knowledge Graph Retrieval-Augmented Generation
Hairu Wang, Yuan Feng, Xike Xie +1
Although Large Language Models achieve strong success in many tasks, they still suffer from hallucinations and knowledge deficiencies in real-world applications. Many knowledge gra…