2 citations · 6 across the 16 of their papers we have counts for
7 papers · 1 filter
Reducing Hallucinations in LLM-based Scientific Literature Analysis Using Peer Context Outlier Detection
Daniel Xie, Maxwell J. Jacobson, Adil Wazeer +3
Reducing hallucinations in Large Language Models (LLMs) is essential for accurate data extraction from large text corpora. Current methods, like prompt engineering and chain-of-tho…
A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization
Maxwell J. Jacobson, Daniel Xie, Jackson Shen +6
Scientific discovery is slowed by fragmented literature that requires excessive human effort to gather, analyze, and understand. AI tools, including autonomous summarization and qu…
Vertical Symbolic Regression
Nan Jiang, Md Nasim, Yexiang Xue
Automating scientific discovery has been a grand goal of Artificial Intelligence (AI) and will bring tremendous societal impact. Learning symbolic expressions from experimental dat…
Hypothesis Network Planned Exploration for Rapid Meta-Reinforcement Learning Adaptation
Maxwell Joseph Jacobson, Rohan Menon, John Zeng +1
Meta-Reinforcement Learning (Meta-RL) learns optimal policies across a series of related tasks. A central challenge in Meta-RL is rapidly identifying which previously learned task…
Integrating Symbolic Reasoning into Neural Generative Models for Design Generation
Maxwell Joseph Jacobson, Yexiang Xue
Design generation requires tight integration of neural and symbolic reasoning, as good design must meet explicit user needs and honor implicit rules for aesthetics, utility, and co…
Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration With Provable Guarantees
Jinzhao Li, Nan Jiang, Yexiang Xue
Satisfiability Modulo Counting (SMC) encompasses problems that require both symbolic decision-making and statistical reasoning. Its general formulation captures many real-world pro…