11 papers
SERUM: State Extraction and Refinement for User Modeling
Andy J. Phu, James Mooney, Karin de Langis +2
Agentic assistants capable of proactive, personalized interactions require structured models of user intent and workflow. However, building these models from raw, unstructured scre…
Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks
Young-Jun Lee, Seungone Kim, Minki Kang +5
Would experience designing faster GPU kernels also help close in on a long-standing open mathematical conjecture? Large Language Models (LLMs) integrated into evolutionary search h…
Effects of Varying LLM Access on Essay Writing Behavior
Julia Christenson, Karin de Langis, Shirley Anugrah Hayati +1
Investigating the degree to which large language models (LLMs) affect teaching and learning in universities can help identify strategies for integrating LLMs in a way that supports…
Are LLM Agents Behaviorally Coherent? Latent Profiles for Social Simulation
James Mooney, Josef Woldense, Zheng Robert Jia +4
The impressive capabilities of Large Language Models (LLMs) raise the possibility that synthetic agents can serve as substitutes for real participants in human-subject research. To…
Structure Liberates: How Constrained Sensemaking Produces More Novel Research Output
James Mooney, Zae Myung Kim, Young-Jun Lee +1
Scientific discovery is an extended process of ideation--surveying prior work, forming hypotheses, and refining reasoning--yet existing approaches treat this phase as a brief pream…
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs
Soyeong Jeong, Taehee Jung, Sung Ju Hwang +2
Recent Long-Context Language Models (LCLMs) can process hundreds of thousands of tokens in a single prompt, enabling new opportunities for knowledge-intensive multi-hop reasoning b…