5 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 improving the accuracy of data extraction from large text corpora. Current methods, like prompt engineering…
A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization
Maxwell J. Jacobson, Daniel Xie, Jackson Shen +4
Scientific discovery is slowed by fragmented literature that requires excessive human effort to gather, analyze, and understand. AI tools, including autonomous summarization and qu…
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…
CALM: Contextual Analog Logic with Multimodality
Maxwell J. Jacobson, Corey J. Maley, Yexiang Xue
In this work, we introduce Contextual Analog Logic with Multimodality (CALM). CALM unites symbolic reasoning with neural generation, enabling systems to make context-sensitive deci…
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…