most citedPractical Marketplace Optimization at Uber Using Causally-Informed Machine Learning

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cs.LG20251 cited

DrugImproverGPT: A Large Language Model for Drug Optimization with Fine-Tuning via Structured Policy Optimization

Xuefeng Liu, Songhao Jiang, Siyu Chen +4

Finetuning a Large Language Model (LLM) is crucial for generating results towards specific objectives. This research delves into the realm of drug optimization and introduce a nove…

cs.LG2025

Active Advantage-Aligned Online Reinforcement Learning with Offline Data

Xuefeng Liu, Hung T. C. Le, Siyu Chen +4

Online reinforcement learning (RL) enhances policies through direct interactions with the environment, but faces challenges related to sample efficiency. In contrast, offline RL le…

cs.LG2024

DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration

Sizhe Liu, Yizhou Lu, Siyu Chen +4

Recent progress in Large Language Models (LLMs) has drawn attention to their potential for accelerating drug discovery. However, a central problem remains: translating theoretical…

cs.LG20241 cited

Practical Marketplace Optimization at Uber Using Causally-Informed Machine Learning

Bobby Chen, Siyu Chen, Jason Dowlatabadi +15

Budget allocation of marketplace levers, such as incentives for drivers and promotions for riders, has long been a technical and business challenge at Uber; understanding lever bud…

cs.LG2024

Contractual Reinforcement Learning: Pulling Arms with Invisible Hands

Jibang Wu, Siyu Chen, Mengdi Wang +2

The agency problem emerges in today's large scale machine learning tasks, where the learners are unable to direct content creation or enforce data collection. In this work, we prop…