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cs.LG2026
Training Data Selection with Gradient Orthogonality for Efficient Domain Adaptation
Xiyang Zhang, Yuanhe Tian, Hongzhi Wang +1
Fine-tuning large language models (LLMs) for specialized domains often necessitates a trade-off between acquiring domain expertise and retaining general reasoning capabilities, a p…
cs.LG2025
MoE Pathfinder: Trajectory-driven Expert Pruning
Xican Yang, Yuanhe Tian, Yan Song
Mixture-of-experts (MoE) architectures used in large language models (LLMs) achieve state-of-the-art performance across diverse tasks yet face practical challenges such as deployme…
cs.LG2025
DNAZEN: Enhanced Gene Sequence Representations via Mixed Granularities of Coding Units
Lei Mao, Yuanhe Tian, Yan Song
Genome modeling conventionally treats gene sequence as a language, reflecting its structured motifs and long-range dependencies analogous to linguistic units and organization princ…