64 citations · 79 across the 10 of their papers we have counts for
6 papers · 1 filter
Large Discovery Models: Empirically-grounded Model-Based Open-Ended Search
Zhongwei Yu, Yan Song, Xue Yan +9
Scientific discovery often involves optimising expensive-to-evaluate objectives over vast, structured, and open-ended hypothesis spaces, such as molecules, protein sequences, and c…
Decision Flow Policy Optimization
Jifeng Hu, Sili Huang, Siyuan Guo +6
In recent years, generative models have shown remarkable capabilities across diverse fields, including images, videos, language, and decision-making. By applying powerful generativ…
DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
Siyuan Guo, Cheng Deng, Ying Wen +3
In this work, we investigate the potential of large language models (LLMs) based agents to automate data science tasks, with the goal of comprehending task requirements, then build…
Instructed Diffuser with Temporal Condition Guidance for Offline Reinforcement Learning
Jifeng Hu, Yanchao Sun, Sili Huang +6
Recent works have shown the potential of diffusion models in computer vision and natural language processing. Apart from the classical supervised learning fields, diffusion models…
A Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning
Siyuan Guo, Yanchao Sun, Jifeng Hu +5
Offline reinforcement learning (RL) provides a promising solution to learning an agent fully relying on a data-driven paradigm. However, constrained by the limited quality of the o…
Enhanced Doubly Robust Learning for Debiasing Post-click Conversion Rate Estimation
Siyuan Guo, Lixin Zou, Yiding Liu +6
Post-click conversion, as a strong signal indicating the user preference, is salutary for building recommender systems. However, accurately estimating the post-click conversion rat…