arXiv subjects

Joseph Williams

Publications and source records attributed to Joseph Williams.

4 recordsLinked to original sources

arXiv2024

Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness

Although engagement in self-directed wellness exercises typically declines over time, integrating social support such as coaching can sustain it. However, traditional forms of support are often inaccessible due to the high costs and complex coordination. Large Language Models (LLMs) show promise in providing human-like dialogues that could emulate social support. Yet, in-depth, in situ investigations of LLMs to support behavior change remain underexplored. We conducted two randomized experiments to assess the impact of LLM agents on user engagement with mindfulness exercises. First, a single-session study, involved 502 crowdworkers; second, a three-week study, included 54 participants. We explored two types of LLM agents: one providing information and another facilitating self-reflection. Both agents enhanced users' intentions to practice mindfulness. However, only the information-providing LLM, featuring a friendly persona, significantly improved engagement with the exercises. Our findings suggest that specific LLM agents may bridge the social support gap in digital health interventions.

cs.HC↗

arXiv2022

Testing the key role of the stellar mass-halo mass relation in galaxy merger rates and morphologies via DECODE, a novel Discrete statistical sEmi-empiriCal mODEl

The relative roles of mergers and star formation in regulating galaxy growth are still a matter of intense debate. We here present our DECODE, a new Discrete statistical sEmi-empiriCal mODEl specifically designed to predict rapidly and efficiently, in a full cosmological context, galaxy assembly and merger histories for any given input stellar mass-halo mass (SMHM) relation. DECODE generates object-by-object dark matter merger trees (hence discrete) from accurate subhalo mass and infall redshift probability functions (hence statistical) for all subhaloes, including those residing within other subhaloes, with virtually no resolution limits on mass or volume. Merger trees are then converted into galaxy assembly histories via an input, redshift dependent SMHM relation, which is highly sensitive to the significant systematics in the galaxy stellar mass function and on its evolution with cosmic time. DECODE can accurately reproduce the predicted mean galaxy merger rates and assembly histories of hydrodynamic simulations and semi-analytic models, when adopting in input their SMHM relations. In the present work we use DECODE to prove that only SMHM relations implied by stellar mass functions characterized by large abundances of massive galaxies and significant redshift evolution, at least at $M_\star \gtrsim 10^{11} \, M_\odot$, can simultaneously reproduce the local abundances of satellite galaxies, the galaxy (major merger) pairs since $z \sim 3$, and the growth of Brightest Cluster Galaxies. The same models can also reproduce the local fraction of elliptical galaxies, on the assumption that these are strictly formed by major mergers, but not the full bulge-to-disc ratio distributions, which require additional processes.

astro-ph.CO↗

arXiv2019

Nonequilibrium dynamics of spontaneous symmetry breaking into a hidden state of charge-density wave

Nonequilibrium phase transition plays a pivotal role in a broad physical context from condensed matter to cosmology. Tracking the formation of non-equilibrium phases in condensed matter is challenging and requires a resolution of the long-range cooperativity on ultra-short timescales. Here, we study the spontaneous symmetry breaking transformation of a charge-density wave system from a stripe phase into a checkerboard state. Such a state is thermodynamically forbidden, but is introduced through a system quench using ultrashort, intense laser pulses. The dynamics is mediated by the soft modes that unfold spontaneously and order the field on a timescale ~1 ps. Using the coherent electron diffraction with ~100 fs resolution, we capture the entire course and demonstrate nonergodic behavior proximal to symmetry breaking that is crucial for stabilizing the hidden states. Remarkably, the thermalization due to carriers cooling arrests the remnants of the transient orders into the topological defects in the eventual state with distinct new properties that last for more than 1 ns. The fundamental dynamics observed here opens an intriguing perspective of controlling phase transitions in quantum materials far from equilibrium.

cond-mat.mes-hall↗

arXiv2013

Evaluating computational models of explanation using human judgments

We evaluate four computational models of explanation in Bayesian networks by comparing model predictions to human judgments. In two experiments, we present human participants with causal structures for which the models make divergent predictions and either solicit the best explanation for an observed event (Experiment 1) or have participants rate provided explanations for an observed event (Experiment 2). Across two versions of two causal structures and across both experiments, we find that the Causal Explanation Tree and Most Relevant Explanation models provide better fits to human data than either Most Probable Explanation or Explanation Tree models. We identify strengths and shortcomings of these models and what they can reveal about human explanation. We conclude by suggesting the value of pursuing computational and psychological investigations of explanation in parallel.

cs.AI↗