25 citations · 58 across the 9 of their papers we have counts for
10 papers
SFBench: The SciFy Scientific Feasibility Benchmark
Cash Costello, James Mayfield, Elsbeth Turcan +7
We present SFBench, a benchmark dataset for evaluating systems that assess the feasibility of scientific claims. SFBench includes 197 claims in materials science, each annotated wi…
Closing Gaps in Emissions Monitoring with Climate TRACE
Brittany V. Lancellotti, Jordan M. Malof, Aaron Davitt +32
Global greenhouse gas emissions estimates are essential for monitoring and mitigation planning. Existing emissions datasets provide critical foundations for understanding emissions…
Evaluating the diversity and utility of materials proposed by generative models
Alexander New, Michael Pekala, Elizabeth A. Pogue +4
Generative machine learning models can use data generated by scientific modeling to create large quantities of novel material structures. Here, we assess how one state-of-the-art g…
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Megan M. Baker, Alexander New, Mario Aguilar-Simon +44
Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks enc…
Closed-loop machine learning for discovery of novel superconductors
Elizabeth A. Pogue, Alexander New, Kyle McElroy +15
The discovery of novel materials drives industrial innovation, although the pace of discovery tends to be slow due to the infrequency of "Eureka!" moments. These moments are typica…
Curvature-informed multi-task learning for graph networks
Alexander New, Michael J. Pekala, Nam Q. Le +3
Properties of interest for crystals and molecules, such as band gap, elasticity, and solubility, are generally related to each other: they are governed by the same underlying laws…
Statistical modality tagging from rule-based annotations and crowdsourcing
Vinodkumar Prabhakaran, Michael Bloodgood, Mona Diab +5
We explore training an automatic modality tagger. Modality is the attitude that a speaker might have toward an event or state. One of the main hurdles for training a linguistic tag…
Use of Modality and Negation in Semantically-Informed Syntactic MT
Kathryn Baker, Michael Bloodgood, Bonnie J. Dorr +5
This paper describes the resource- and system-building efforts of an eight-week Johns Hopkins University Human Language Technology Center of Excellence Summer Camp for Applied Lang…
A Modality Lexicon and its use in Automatic Tagging
Kathryn Baker, Michael Bloodgood, Bonnie J. Dorr +3
This paper describes our resource-building results for an eight-week JHU Human Language Technology Center of Excellence Summer Camp for Applied Language Exploration (SCALE-2009) on…
Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach
Kathryn Baker, Michael Bloodgood, Chris Callison-Burch +5
We describe a unified and coherent syntactic framework for supporting a semantically-informed syntactic approach to statistical machine translation. Semantically enriched syntactic…