3 papers
cs.CL2026
ARKD: Adaptive Reinforcement Learning-Guided Bidirectional KL Divergence Distillation for Text Generation
Zilong Liu, Xuewen Zhang, Jinrui Xing +3
Knowledge distillation (KD) is a key technique for compressing Large Language Models (LLMs), yet methods relying on a single KL objective often fail to balance primary distribution…
cs.IR2026
Rethinking Sales Lead Scoring with LLM-based Hierarchical Preference Ranking
Chenyu Zhang, Yiwen Liu, Yin Sun +4
Sales lead conversion in high-stakes domains (e.g., automotive, real estate) differs fundamentally from e-commerce recommendation due to prolonged decision cycles and multi-stage f…
cs.LG2025
MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models
Yiwen Liu, Chenyu Zhang, Junjie Song +6
As a prominent data modality task, time series forecasting plays a pivotal role in diverse applications. With the remarkable advancements in Large Language Models (LLMs), the adopt…