77 citations · 190 across the 13 of their papers we have counts for
16 papers
Semantic Bandits: In-Context Exploration-Exploitation is Biased by Semantic Priors
David Eric Austin, Kaheer Suleman, Jackie Chi Kit Cheung
Large language models (LLMs) are increasingly deployed as decision-making agents in settings that require sophisticated environmental exploration. However, existing work has raised…
CASSANDRA: Programmatic and Probabilistic Learning and Inference for Stochastic World Modeling
Panagiotis Lymperopoulos, Abhiramon Rajasekharan, Ian Berlot-Attwell +2
Building world models is essential for planning in real-world domains such as businesses. Since such domains have rich semantics, we can leverage world knowledge to effectively mod…
Mini Amusement Parks (MAPs): A Testbed for Modelling Business Decisions
Stéphane Aroca-Ouellette, Ian Berlot-Attwell, Panagiotis Lymperopoulos +5
Despite rapid progress in artificial intelligence, current systems struggle with the interconnected challenges that define real-world decision making. Practical domains such as bus…
TopiOCQA: Open-domain Conversational Question Answering with Topic Switching
Vaibhav Adlakha, Shehzaad Dhuliawala, Kaheer Suleman +2
In a conversational question answering scenario, a questioner seeks to extract information about a topic through a series of interdependent questions and answers. As the conversati…
An Analysis of Dataset Overlap on Winograd-Style Tasks
Ali Emami, Adam Trischler, Kaheer Suleman +1
The Winograd Schema Challenge (WSC) and variants inspired by it have become important benchmarks for common-sense reasoning (CSR). Model performance on the WSC has quickly progress…
Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Text
Ian Porada, Kaheer Suleman, Jackie Chi Kit Cheung
Modeling semantic plausibility requires commonsense knowledge about the world and has been used as a testbed for exploring various knowledge representations. Previous work has focu…
Improving Neural Question Generation using World Knowledge
Deepak Gupta, Kaheer Suleman, Mahmoud Adada +2
In this paper, we propose a method for incorporating world knowledge (linked entities and fine-grained entity types) into a neural question generation model. This world knowledge h…
Playing log(N)-Questions over Sentences
Peter Potash, Kaheer Suleman
We propose a two-agent game wherein a questioner must be able to conjure discerning questions between sentences, incorporate responses from an answerer, and keep track of a hypothe…
How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG
Paul Trichelair, Ali Emami, Adam Trischler +2
Recent studies have significantly improved the state-of-the-art on common-sense reasoning (CSR) benchmarks like the Winograd Schema Challenge (WSC) and SWAG. The question we ask in…
A Knowledge Hunting Framework for Common Sense Reasoning
Ali Emami, Noelia De La Cruz, Adam Trischler +2
We introduce an automatic system that achieves state-of-the-art results on the Winograd Schema Challenge (WSC), a common sense reasoning task that requires diverse, complex forms o…
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.…
NewsQA: A Machine Comprehension Dataset
Adam Trischler, Tong Wang, Xingdi Yuan +4
We present NewsQA, a challenging machine comprehension dataset of over 100,000 human-generated question-answer pairs. Crowdworkers supply questions and answers based on a set of ov…
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…
Natural Language Comprehension with the EpiReader
Adam Trischler, Zheng Ye, Xingdi Yuan +1
We present the EpiReader, a novel model for machine comprehension of text. Machine comprehension of unstructured, real-world text is a major research goal for natural language proc…
Natural Language Generation in Dialogue using Lexicalized and Delexicalized Data
Shikhar Sharma, Jing He, Kaheer Suleman +2
Natural language generation plays a critical role in spoken dialogue systems. We present a new approach to natural language generation for task-oriented dialogue using recurrent ne…
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…