arXiv subjects

Alison Robey

Publications and source records attributed to Alison Robey.

4 recordsLinked to original sources

arXiv2024

A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick

Keyword mnemonics are memorable explanations that link new terms to simpler keywords. Prior work generates mnemonics for students, but they do not train models using mnemonics students prefer and aid learning. We build SMART, a mnemonic generator trained on feedback from real students learning new terms. To train SMART, we first fine-tune LLaMA-2 on a curated set of user-written mnemonics. We then use LLM alignment to enhance SMART: we deploy mnemonics generated by SMART in a flashcard app to find preferences on mnemonics students favor. We gather 2684 preferences from 45 students across two types: expressed (inferred from ratings) and observed (inferred from student learning), yielding three key findings. First, expressed and observed preferences disagree; what students think is helpful does not always capture what is truly helpful. Second, Bayesian models can synthesize complementary data from multiple preference types into a single effectiveness signal. SMART is tuned via Direct Preference Optimization on this signal, which resolves ties and missing labels in the typical method of pairwise comparisons, augmenting data for LLM output quality gains. Third, mnemonic experts assess SMART as matching GPT-4 at much lower deployment costs, showing the utility of capturing diverse student feedback to align LLMs in education.

cs.CL↗

arXiv2021

Sensitivity of airborne transmission of enveloped viruses to seasonal variation in indoor relative humidity

In temperate climates, infection rates of enveloped viruses peak during the winter. While these seasonal trends are established in influenza and human coronaviruses, the mechanisms driving the variation remain poorly understood and thus difficult to extend to similar viruses like SARS-CoV-2. In this study, we use the Quadrature-based model of Respiratory Aerosol and Droplets (QuaRAD) to explore the sensitivity of airborne transmission to the seasonal variation in indoor relative humidity across the wide range of relevant conditions, using SARS-CoV-2 as an example. Relative humidity impacts the evaporation rate and equilibrium size of airborne particles, which in turn may impact particle removal rates and virion viability. Across a large ensemble of scenarios, we found that the dry indoor conditions typical of the winter season lead to slower inactivation than in the more humid summer season; in poorly ventilated spaces, this reduction in inactivation rates increases the concentration of active virions, but this effect was important when the susceptible person was farther than 2 m downwind of the infectious person. On the other hand, changes in particle settling velocity with relative humidity did not significantly affect the removal or travel distance of virus-laden scenarios.

physics.med-ph↗

arXiv2021

High efficacy of layered controls for reducing transmission of airborne pathogens

To optimize strategies for curbing the transmission of airborne pathogens, the efficacy of three key controls -- face masks, ventilation, and physical distancing -- must be well understood. In this study we used the Quadrature-based model of Respiratory Aerosol and Droplets to quantify the reduction in exposure to airborne pathogens from various combinations of controls. For each combination of controls, we simulated thousands of scenarios that represent the tremendous variability in factors governing airborne transmission and the efficacy of mitigation strategies. While the efficacy of any individual control was highly variable among scenarios, combining universal mask-wearing with distancing of 1~m or more reduced the median exposure by more than 99\% relative to a close, unmasked conversation, with further reductions if ventilation is also enhanced. The large reductions in exposure to airborne pathogens translated to large reductions in the risk of initial infection in a new host. These findings suggest that layering controls is highly effective for reducing transmission of airborne pathogens and will be critical for curbing outbreaks of novel viruses in the future.

physics.med-ph↗

arXiv2021

Simulating near-field enhancement in transmission of airborne viruses with a quadrature-based model

Airborne viruses, such as influenza, tuberculosis, and SARS-CoV-2, are transmitted through virus-laden particles expelled when an infectious person sneezes, coughs, talks, or breathes. These virus-laden particles are more highly concentrated in the expiratory jet of an infectious person than in a well-mixed room, but this near-field enhancement in virion exposure has not been well quantified. Transmission of airborne viruses depends on factors that are inherently variable and, in many cases, poorly constrained, and quantifying this uncertainty requires large ensembles of model simulations that span the variability in input parameters. However, models that are well-suited to simulate the near-field evolution of respiratory particles are also computationally expensive, which limits the exploration of parametric uncertainty. In order to perform many simulations that span the wide variability in factors governing transmission, we developed the Quadrature-based model of Respiratory Aerosol and Droplets (QuaRAD). QuaRAD is an efficient framework for simulating the evolution of virus-laden particles after they are expelled from an infectious person, their deposition to the nasal cavity of a susceptible person, and the subsequent risk of initial infection. We simulated 10,000 scenarios to quantify the risk of initial infection by a particular virus, SARS-CoV-2. The predicted risk of infection was highly variable among scenarios and, in each scenario, was strongly enhanced near the infectious individual. In more than 50% of scenarios, the physical distancing needed to avoid near-field enhancements in airborne transmission was beyond the recommended safe distance of two meters (six feet) if the infectious person is not wearing a mask, though this distance defining the near-field extent was also highly variable among scenarios.

physics.med-ph↗