5 citations · 5 across the 4 of their papers we have counts for
4 papers
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…
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…
MASR: Self-Reflective Reasoning through Multimodal Hierarchical Attention Focusing for Agent-based Video Understanding
Shiwen Cao, Zhaoxing Zhang, Junming Jiao +4
Even in the era of rapid advances in large models, video understanding remains a highly challenging task. Compared to texts or images, videos commonly contain more information with…
DR-RAG: Applying Dynamic Document Relevance to Retrieval-Augmented Generation for Question-Answering
Zijian Hei, Weiling Liu, Wenjie Ou +5
Retrieval-Augmented Generation (RAG) has recently demonstrated the performance of Large Language Models (LLMs) in the knowledge-intensive tasks such as Question-Answering (QA). RAG…