4 papers
E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning
Zihan Liao, Jun Wang, Hang Yu +3
Processing long contexts is increasingly important for Large Language Models (LLMs) in tasks like multi-turn dialogues, code generation, and document summarization. This paper addr…
Pushing the Limits of Low-Bit Optimizers: A Focus on EMA Dynamics
Cong Xu, Wenbin Liang, Mo Yu +7
The rapid scaling of models has led to prohibitively high training and fine-tuning costs. A major factor accounting for memory consumption is the widespread use of stateful optimiz…
CNNSum: Exploring Long-Context Summarization with Large Language Models in Chinese Novels
Lingxiao Wei, He Yan, Xiangju Lu +3
Large language models (LLMs) have been well-researched in various long-context tasks. However, the scarcity of long-context summarization datasets hinders progress in this area. To…
Coherency Improved Explainable Recommendation via Large Language Model
Shijie Liu, Ruixing Ding, Weihai Lu +4
Explainable recommender systems are designed to elucidate the explanation behind each recommendation, enabling users to comprehend the underlying logic. Previous works perform rati…