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- Zhejiang UniversityCN121 papers
- Alibaba Group (United States)US60 papers
- Tsinghua UniversityCN52 papers
- Peking UniversityCN50 papers
- University of Science and Technology of ChinaCN50 papers
- Nanyang Technological UniversitySG42 papers
- Chinese Academy of SciencesCN37 papers
- Shanghai Jiao Tong UniversityCN34 papers
- University of Chinese Academy of SciencesCN26 papers
- University of Electronic Science and Technology of ChinaCN19 papers
- Fudan UniversityCN18 papers
- Hong Kong University of Science and TechnologyHK17 papers
89 papers · 1 filter
CKV: Compressed and Composable KV Cache Reuse for Efficient LLM Inference
Chuheng Du, Junyi Chen, Hanlin Tang +7
Long-context inference is central to modern large language model (LLM) applications such as retrieval-augmented generation and multi-document reasoning. To mitigate the growing inf…
Eureka: Intelligent Feature Engineering for Enterprise AI Cloud Resource Demand Prediction
Hangxuan Li, Renjun Jia, Xuezhang Wu +3
Effective features are crucial for predictive model performance, but creating them often requires domain expertise, limiting scalability across applications. We define feature engi…
CoDA: A Context-Decoupled Hierarchical Agent with Reinforcement Learning
Xuanzhang Liu, Jianglun Feng, Zhuoran Zhuang +7
Large Language Model (LLM) agents trained with reinforcement learning (RL) show great promise for solving complex, multi-step tasks. However, their performance is often crippled by…
XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL
Yifu Liu, Yin Zhu, Yingqi Gao +8
To leverage the advantages of LLM in addressing challenges in the Text-to-SQL task, we present XiYan-SQL, an innovative framework effectively generating and utilizing multiple SQL…
ESGenius: Benchmarking LLMs on Environmental, Social, and Governance (ESG) and Sustainability Knowledge
Chaoyue He, Xin Zhou, Yi Wu +9
We introduce ESGenius, a comprehensive benchmark for evaluating and enhancing the proficiency of Large Language Models (LLMs) in Environmental, Social, and Governance (ESG) and sus…
AdaMMS: Model Merging for Heterogeneous Multimodal Large Language Models with Unsupervised Coefficient Optimization
Yiyang Du, Xiaochen Wang, Chi Chen +9
Recently, model merging methods have demonstrated powerful strengths in combining abilities on various tasks from multiple Large Language Models (LLMs). While previous model mergin…