Search Results for author:
Found 10 papers, 3 papers with code
Dungeons and Dragons as a Dialog Challenge for Artificial Intelligence
In this paper, we frame D&D specifically as a dialogue system challenge, where the tasks are to both generate the next conversational turn in the game and predict the state of the game given the dialogue history.
Measuring Attribution in Natural Language Generation Models
With recent improvements in natural language generation (NLG) models for various applications, it has become imperative to have the means to identify and evaluate whether NLG output is only sharing verifiable information about the external world.
CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning
Compared to standard retrieval tasks, passage retrieval for conversational question answering (CQA) poses new challenges in understanding the current user question, as each question needs to be interpreted within the dialogue context.
Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features
At training time, additional inputs based on these evaluation measures are given to the dialogue model.
Thieves on Sesame Street! Model Extraction of BERT-based APIs
We study the problem of model extraction in natural language processing, in which an adversary with only query access to a victim model attempts to reconstruct a local copy of that model.
Improving Semantic Parsing with Neural Generator-Reranker Architecture
In this work, we propose a generator-reranker architecture for semantic parsing.
Attention Interpretability Across NLP Tasks
The attention layer in a neural network model provides insights into the model's reasoning behind its prediction, which are usually criticized for being opaque.
End-to-End Retrieval in Continuous Space
Most text-based information retrieval (IR) systems index objects by words or phrases.
Coordinating Collaborative Chat in Massive Open Online Courses
An earlier study of a collaborative chat intervention in a Massive Open Online Course (MOOC) identified negative effects on attrition stemming from a requirement for students to be matched with exactly one partner prior to beginning the activity.
Neural Paraphrase Identification of Questions with Noisy Pretraining
We present a solution to the problem of paraphrase identification of questions.
