2 citations · 4 across the 19 of their papers we have counts for
4 papers · 1 filter
Less is MoE: Trimming Experts in Domain-Specialist Language Models
Haoze He, Xinkai Zou, Xuan Jiang +4
Mixture-of-Experts (MoE) models achieve strong performance through conditional computation, but their large parameter footprint poses deployment challenges. Prior MoE compression a…
The Last Human-Written Paper: Agent-Native Research Artifacts
Jiachen Liu, Jiaxin Pei, Jintao Huang +34
Scientific publication compresses a branching, iterative research process into a linear narrative, discarding the majority of what was discovered along the way. This compilation im…
From Street Views to Urban Science: Discovering Road Safety Factors with Multimodal Large Language Models
Yihong Tang, Ao Qu, Xujing Yu +4
Urban and transportation research has long sought to uncover statistically meaningful relationships between key variables and societal outcomes such as road safety, to generate act…
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Vindula Jayawardana, Baptiste Freydt, Ao Qu +3
Despite the popularity of multi-agent reinforcement learning (RL) in simulated and two-player applications, its success in messy real-world applications has been limited. A key cha…