6 citations · 16 across the 8 of their papers we have counts for
8 papers
Facets, Taxonomies, and Syntheses: Navigating Structured Representations in LLM-Assisted Literature Review
Raymond Fok, Joseph Chee Chang, Marissa Radensky +4
Comprehensive literature review requires synthesizing vast amounts of research -- a labor intensive and cognitively demanding process. Most prior work focuses either on helping res…
CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation
Peter Jansen, Oyvind Tafjord, Marissa Radensky +6
Despite the surge of interest in autonomous scientific discovery (ASD) of software artifacts (e.g., improved ML algorithms), current ASD systems face two key limitations: (1) they…
Human-LLM Compound System for Scientific Ideation through Facet Recombination and Novelty Evaluation
Marissa Radensky, Simra Shahid, Raymond Fok +3
The scientific ideation process often involves blending facets of existing papers to create new ideas. We contribute Scideator, the first human-LLM system for facet-based scientifi…
Papers-to-Posts: Supporting Detailed Long-Document Summarization with an Interactive LLM-Powered Source Outline
Marissa Radensky, Daniel S. Weld, Joseph Chee Chang +2
Compressing long and technical documents (e.g., >10 pages) into shorter-form articles (e.g., <2 pages) is critical for communicating information to different audiences, for example…
Exploring How Anomalous Model Input and Output Alerts Affect Decision-Making in Healthcare
Marissa Radensky, Dustin Burson, Rajya Bhaiya +1
An important goal in the field of human-AI interaction is to help users more appropriately trust AI systems' decisions. A situation in which the user may particularly benefit from…
Exploring The Role of Local and Global Explanations in Recommender Systems
Marissa Radensky, Doug Downey, Kyle Lo +2
Explanations are well-known to improve recommender systems' transparency. These explanations may be local, explaining an individual recommendation, or global, explaining the recomm…
Bursting Scientific Filter Bubbles: Boosting Innovation via Novel Author Discovery
Jason Portenoy, Marissa Radensky, Jevin West +3
Isolated silos of scientific research and the growing challenge of information overload limit awareness across the literature and hinder innovation. Algorithmic curation and recomm…
Interactive Task and Concept Learning from Natural Language Instructions and GUI Demonstrations
Toby Jia-Jun Li, Marissa Radensky, Justin Jia +3
Natural language programming is a promising approach to enable end users to instruct new tasks for intelligent agents. However, our formative study found that end users would often…