Search Results for author:
Found 10 papers, 6 papers with code
Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents
In this work, we introduce LCoW, a framework for Learning language models to Contextualize complex Web pages into a more comprehensible form, thereby enhancing decision making by LLM agents.
MobileSafetyBench: Evaluating Safety of Autonomous Agents in Mobile Device Control
In this work, we introduce MobileSafetyBench, a benchmark designed to evaluate the safety of device-control agents within a realistic mobile environment based on Android emulators.
Benchmarking Mobile Device Control Agents across Diverse Configurations
In this work, we introduce B-MoCA: a novel benchmark with interactive environments for evaluating and developing mobile device control agents.
LiFT: Unsupervised Reinforcement Learning with Foundation Models as Teachers
We propose a framework that leverages foundation models as teachers, guiding a reinforcement learning agent to acquire semantically meaningful behavior without human feedback.
Hyperbolic VAE via Latent Gaussian Distributions
We propose a Gaussian manifold variational auto-encoder (GM-VAE) whose latent space consists of a set of Gaussian distributions.
Style-Agnostic Reinforcement Learning
We present a novel method of learning style-agnostic representation using both style transfer and adversarial learning in the reinforcement learning framework.
A Rotated Hyperbolic Wrapped Normal Distribution for Hierarchical Representation Learning
We present a rotated hyperbolic wrapped normal distribution (RoWN), a simple yet effective alteration of a hyperbolic wrapped normal distribution (HWN).
Semi-supervised Image Classification with Grad-CAM Consistency
Consistency training, which exploits both supervised and unsupervised learning with different augmentations on image, is an effective method of utilizing unlabeled data in semi-supervised learning (SSL) manner.
National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?
SARIMAX-ANN, SARIMAX-SVR, and SARIMAX-LSTM are used for the hybrid models.
Efficient discovery of multiple minimum action pathways using Gaussian process
We present a new efficient transition pathway search method based on the least action principle and the Gaussian process regression method.
Bayesian Inference
Computational Physics
Statistical Mechanics
