PaperMetrixEvidence-aware discovery
EN
Interface language English EN العربية AR Türkçe TR
Create account
Researcher profile

Iulian Vlad Serban

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. The RLLChatbot: a solution to the ConvAI challenge

    2018 · arXiv (Cornell University)

    Current conversational systems can follow simple commands and answer basic questions, but they have difficulty maintaining coherent and open-ended conversations about specific topics. Competitions like the Conversational Intelligence (ConvAI) challenge are being organized to push …

  2. How Teachers Can Use Large Language Models and Bloom's Taxonomy to Create Educational Quizzes

    2024 · arXiv (Cornell University)

    Question generation (QG) is a natural language processing task with an abundance of potential benefits and use cases in the educational domain. In order for this potential to be realized, QG systems must be designed …

  3. A Survey of Available Corpora for Building Data-Driven Dialogue Systems

    2015 · arXiv (Cornell University)

    During the past decade, several areas of speech and language understanding have witnessed substantial breakthroughs from the use of data-driven models. In the area of dialogue systems, the trend is less obvious, and most practical …

  4. How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation

    2016 · arXiv (Cornell University)

    We investigate evaluation metrics for dialogue response generation systems where supervised labels, such as task completion, are not available. Recent works in response generation have adopted metrics from machine translation to compare a model's generated …

  5. Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation

    2017 · Proceedings of the AAAI Conference on Artificial Intelligence

    We introduce a new class of models called multiresolution recurrent neural networks, which explicitly model natural language generation at multiple levels of abstraction. The models extend the sequence-to-sequence framework to generate two parallel stochastic processes: …

  6. Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models

    2016 · Proceedings of the AAAI Conference on Artificial Intelligence

    We investigate the task of building open domain, conversational dialogue systems based on large dialogue corpora using generative models. Generative models produce system responses that are autonomously generated word-by-word, opening up the possibility for realistic, …