This academic paper discusses the concept of introspective planning for Large Language Models (LLMs). These models, which are used in robots to understand natural language instructions and plan actions, often…
Continue readingThe study introduces a new method, the Conformal Monte Carlo (CMC) meta-learners, for estimating the treatment effect of interventions for decision-making. Traditional methods only provide a point estimate of this…
Continue readingThe research delves into the challenge of sample-based inference (SBI) for Bayesian neural networks (BNNs) due to the size and structure of the network’s parameter space. The authors propose that…
Continue readingThe paper presents a new method called LTAU-FF for estimating the prediction uncertainty in atomistic force fields. The authors use model ensembles and cumulative distribution functions of per-sample errors to…
Continue readingThe article presents the Uncertainty-Aware Language Agent (UALA), a new framework that leverages uncertainty quantification to improve the interaction between language agents and the external world. This approach overcomes the…
Continue readingThe paper investigates the use of modulation spectrum features (MSF) and mel-frequency cepstral coefficients (MFCC) in joint speaker diarization and identification (JSID) using machine learning models like convolutional neural networks…
Continue readingThe research addresses the issue of active view selection and uncertainty quantification in Radiance Fields. The researchers propose a method that utilizes Fisher Information to efficiently quantify observed information within…
Continue readingThe paper introduces a method for predicting the performance of convolutional long short-term memory networks, particularly in tasks that require semantic segmentation. The method involves estimating predictive quality based on…
Continue readingThis research proposed a Bayesian neural controlled differential equation (BNCDE) for estimating treatment effects over time in healthcare. Traditional methods are limited to point estimates, but the BNCDE provides meaningful…
Continue readingThe article ‘High-Dimensional Prediction for Sequential Decision Making’ by Georgy Noarov et al. explores the problem of making predictions for a high-dimensional state chosen by an adversary. The predictions are…
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