182 citations · 326 across the 10 of their papers we have counts for
13 papers
MemWM: Memory-Augmented Text-Based World Model
Yujun Wang, Tao Zhang, Jinhe Bi +9
World models are increasingly used to support planning in agents by predicting how environment states evolve in response to agent actions. Yet fluent next-state predictions can sti…
Why Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generation
Kushal Arora, Layla El Asri, Hareesh Bahuleyan +1
Current language generation models suffer from issues such as repetition, incoherence, and hallucinations. An often-repeated hypothesis is that this brittleness of generation model…
Diverse Keyphrase Generation with Neural Unlikelihood Training
Hareesh Bahuleyan, Layla El Asri
In this paper, we study sequence-to-sequence (S2S) keyphrase generation models from the perspective of diversity. Recent advances in neural natural language generation have made po…
A Study of State Aliasing in Structured Prediction with RNNs
Layla El Asri, Adam Trischler
End-to-end reinforcement learning agents learn a state representation and a policy at the same time. Recurrent neural networks (RNNs) have been trained successfully as reinforcemen…
From FiLM to Video: Multi-turn Question Answering with Multi-modal Context
Dat Tien Nguyen, Shikhar Sharma, Hannes Schulz +1
Understanding audio-visual content and the ability to have an informative conversation about it have both been challenging areas for intelligent systems. The Audio Visual Scene-awa…
Towards Solving Text-based Games by Producing Adaptive Action Spaces
Ruo Yu Tao, Marc-Alexandre Côté, Xingdi Yuan +1
To solve a text-based game, an agent needs to formulate valid text commands for a given context and find the ones that lead to success. Recent attempts at solving text-based games…
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction
Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz +5
Conditional text-to-image generation is an active area of research, with many possible applications. Existing research has primarily focused on generating a single image from avail…
TextWorld: A Learning Environment for Text-based Games
Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan +10
We introduce TextWorld, a sandbox learning environment for the training and evaluation of RL agents on text-based games. TextWorld is a Python library that handles interactive play…
Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language Generation
Shikhar Sharma, Layla El Asri, Hannes Schulz +1
Automated metrics such as BLEU are widely used in the machine translation literature. They have also been used recently in the dialogue community for evaluating dialogue response g…
A Frame Tracking Model for Memory-Enhanced Dialogue Systems
Hannes Schulz, Jeremie Zumer, Layla El Asri +1
Recently, resources and tasks were proposed to go beyond state tracking in dialogue systems. An example is the frame tracking task, which requires recording multiple frames, one fo…
Frames: A Corpus for Adding Memory to Goal-Oriented Dialogue Systems
Layla El Asri, Hannes Schulz, Shikhar Sharma +5
This paper presents the Frames dataset (Frames is available at http://datasets.maluuba.com/Frames), a corpus of 1369 human-human dialogues with an average of 15 turns per dialogue.…
A Sequence-to-Sequence Model for User Simulation in Spoken Dialogue Systems
Layla El Asri, Jing He, Kaheer Suleman
User simulation is essential for generating enough data to train a statistical spoken dialogue system. Previous models for user simulation suffer from several drawbacks, such as th…
Policy Networks with Two-Stage Training for Dialogue Systems
Mehdi Fatemi, Layla El Asri, Hannes Schulz +2
In this paper, we propose to use deep policy networks which are trained with an advantage actor-critic method for statistically optimised dialogue systems. First, we show that, on…