1 citations · 1 across the 9 of their papers we have counts for
9 papers
Mapping the Emerging Social Science of Large Language Models
Yi Yang, Xiao Jia, Zeyun Dong +2
Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these developments remains fragmented…
Measuring Iterative Temporal Reasoning with Time Puzzles
Zhengxiang Wang, Zeyu Dong
Tool use, such as web search, has become a standard capability even in freely available large language models (LLMs). However, existing benchmarks evaluate temporal reasoning mainl…
Renaissance of Literate Programming in the Era of LLMs: Enhancing LLM-Based Code Generation in Large-Scale Projects
Wuyang Zhang, Yansong Li, Zeyu Dong +6
Large Language Models (LLMs) have helped programmers increase efficiency through code generation, comprehension, and repair. However, their application to large-scale projects rema…
Learning to Help in Multi-Class Settings
Yu Wu, Yansong Li, Zeyu Dong +2
Deploying complex machine learning models on resource-constrained devices is challenging due to limited computational power, memory, and model retrainability. To address these limi…
Generalizing End-To-End Autonomous Driving In Real-World Environments Using Zero-Shot LLMs
Zeyu Dong, Yimin Zhu, Yansong Li +2
Traditional autonomous driving methods adopt a modular design, decomposing tasks into sub-tasks. In contrast, end-to-end autonomous driving directly outputs actions from raw sensor…
EAPCR: A Universal Feature Extractor for Scientific Data without Explicit Feature Relation Patterns
Zhuohang Yu, Ling An, Yansong Li +6
Conventional methods, including Decision Tree (DT)-based methods, have been effective in scientific tasks, such as non-image medical diagnostics, system anomaly detection, and inor…
When to Trust Your Data: Enhancing Dyna-Style Model-Based Reinforcement Learning With Data Filter
Yansong Li, Zeyu Dong, Ertai Luo +3
Reinforcement learning (RL) algorithms can be divided into two classes: model-free algorithms, which are sample-inefficient, and model-based algorithms, which suffer from model bia…
KnobTree: Intelligent Database Parameter Configuration via Explainable Reinforcement Learning
Jiahan Chen, Shuhan Qi, Yifan Li +4
Databases are fundamental to contemporary information systems, yet traditional rule-based configuration methods struggle to manage the complexity of real-world applications with hu…
Technical Report of 2023 ABO Fine-grained Semantic Segmentation Competition
Zeyu Dong
In this report, we describe the technical details of our submission to the 2023 ABO Fine-grained Semantic Segmentation Competition, by Team "Zeyu\_Dong" (username:ZeyuDong). The ta…