Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing
The study focuses on Large Language Models (LLMs) and their ability to handle complex reasoning tasks. It…
Intent Assurance using LLMs guided by Intent Drift
The paper discusses Intent-Based Networking (IBN), a network management paradigm that aligns intents and business objectives with…
FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game
This academic article is about the Factorized Multi-Agent MiniMax Q-Learning (FM3Q), a new framework for two-team zero-sum…
Improving the accuracy of freight mode choice models: A case study using the 2017 CFS PUF data set and ensemble learning techniques
The research paper ‘Improving the Accuracy of Freight Mode Choice Models’ by Diyi Liu et al. investigates…
Modeling Freight Mode Choice Using Machine Learning Classifiers: A Comparative Study Using the Commodity Flow Survey (CFS) Data
This research explores the use of machine learning classifiers for modeling freight mode choice. Eight common machine…
Combining the Strengths of Dutch Survey and Register Data in a Data Challenge to Predict Fertility (PreFer)
The paper discusses the creation of two datasets for studying the predictability of fertility outcomes in the…
Explaining Text Classifiers with Counterfactual Representations
The paper presents a method for explaining text classifiers using counterfactual representations. Counterfactuals are hypothetical events identical…
Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation
This research paper discusses the concept of predictive multiplicity, which refers to the presence of multiple competing…
MobilityDL: A Review of Deep Learning From Trajectory Data
This review paper provides an overview of deep learning approaches for trajectory data. The authors identify eight…
Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data
The paper explores the benefits of transformer-based models’ ability to learn in context from unstructured data during…