Blog
LAPP: Large Language Model Feedback for Preference-Driven Reinforcement Learning
We introduce Large Language Model-Assisted Preference Prediction (LAPP), a novel framework for robot learning that enables efficient, customizable, and expressive behavior acquisition with minimum human effort. Unlike prior approaches that rely heavily on reward engineering, human demonstrations, motion capture, or expensive pairwise...
Agent for User: Testing Multi-User Interactive Features in TikTok
TikTok, a widely-used social media app boasting over a billion monthly active users, requires effective app quality assurance for its intricate features. Feature testing is crucial in achieving this goal. However, the multi-user interactive features within the app, such as live streaming,...
Unifying Image Counterfactuals and Feature Attributions with Latent-Space Adversarial Attacks
Counterfactuals are a popular framework for interpreting machine learning predictions. These what if explanations are notoriously challenging to create for computer vision models: standard gradient-based methods are prone to produce adversarial examples, in which imperceptible modifications to image pixels provoke large changes...
Under Pressure: Contextualizing Workplace Stress Towards User-Centered Interventions
Stress is a pervasive challenge that significantly impacts worker health and well-being. Workplace stress is driven by various factors, ranging from organizational changes to poor workplace design. Although individual stress management strategies have been shown to be effective, current interventions often overlook...
A Sensor-Driven Optimization Framework for Asset Management in Energy Systems: Implications for Full and Partial Digital Transformation in Hydro Fleets
This paper proposes a novel prognostics-driven approach to optimize operations and maintenance (O&M) decisions in hydropower systems. Our approach harnesses the insights from sensor data to accurately predict the remaining lifetime distribution of critical generation assets in hydropower systems, i.e., thrust bearings,...
The Impact of Plasma Angular Momentum on Magnetically Arrested Flows and Relativistic Jets in Hot Accretion Flows Around Black Holes
In certain scenarios, the accreted angular momentum of plasma onto a black hole could be low; however, how the accretion dynamics depend on the angular momentum content of the plasma is still not fully understood. We present three-dimensional, general relativistic magnetohydrodynamic simulations...
A dual-stage constitutive modeling framework based on finite strain data-driven identification and physics-augmented neural networks
In this contribution, we present a novel consistent dual-stage approach for the automated generation of hyperelastic constitutive models which only requires experimentally measurable data. To generate input data for our approach, an experiment with full-field measurement has to be conducted to gather...
Nonreciprocal wave-mediated interactions power a classical time crystal
An acoustic standing wave acts as a lattice of evenly spaced potential energy wells for sub-wavelength-scale objects. Trapped particles interact with each other by exchanging waves that they scatter from the standing wave. Unless the particles have identical scattering properties, their wave-mediated...
Baryon Acoustic Oscillations in tomographic Angular Density and Redshift Fluctuations
In this work we examine the baryon acoustic oscillations (BAO) in 2D angular and redshift space $\{\theta, \Delta z\}$, with $\Delta z$ denoting the redshift difference between two given angular shells. We thus work in the context of tomographic analyses of the...
SimulS2S-LLM: Unlocking Simultaneous Inference of Speech LLMs for Speech-to-Speech Translation
Simultaneous speech translation (SST) outputs translations in parallel with streaming speech input, balancing translation quality and latency. While large language models (LLMs) have been extended to handle the speech modality, streaming remains challenging as speech is prepended as a prompt for the...