1 citations · 1 across the 8 of their papers we have counts for
4 papers · 1 filter
Motif-Mamba: network motif improved mamba for long-range sequence modeling
Chonghe Hao, Yue Sun, Jian Zhang +4
Efficient long-sequence modeling remains a central challenge for large language models, as self-attention scales quadratically with sequence length. Mamba offers a linear-time alte…
PivotRL: High Accuracy Agentic Post-Training at Low Compute Cost
Junkeun Yi, Damon Mosk-Aoyama, Baihe Huang +9
Post-training for long-horizon agentic tasks has a tension between compute efficiency and generalization. While supervised fine-tuning (SFT) is compute efficient, it often suffers…
LLMdoctor: Token-Level Flow-Guided Preference Optimization for Efficient Test-Time Alignment of Large Language Models
Tiesunlong Shen, Rui Mao, Jin Wang +4
Aligning Large Language Models (LLMs) with human preferences is critical, yet traditional fine-tuning methods are computationally expensive and inflexible. While test-time alignmen…
WeMusic-Agent: Efficient Conversational Music Recommendation via Knowledge Internalization and Agentic Boundary Learning
Wendong Bi, Yirong Mao, Xianglong Liu +4
Personalized music recommendation in conversational scenarios usually requires a deep understanding of user preferences and nuanced musical context, yet existing methods often stru…