We view large language models (LLMs) as stochastic language layers in
a ...
Humans learn to master open-ended repertoires of skills by imagining and...
Progress in NLP is increasingly measured through benchmarks; hence,
cont...
Qualitative analysis of textual contents unpacks rich and valuable
infor...
Building open-ended agents that can autonomously discover a diversity of...
Students' ability to ask curious questions is a crucial skill that impro...
Large Language Models (LLMs) have in recent years demonstrated impressiv...
Training keyphrase generation (KPG) models requires a large amount of
an...
To solve difficult tasks, humans ask questions to acquire knowledge from...
Humans have the capability, aided by the expressive compositionality of ...
Interactive machine reading comprehension (iMRC) is machine comprehensio...
Faceted summarization provides briefings of a document from different
pe...
Given a simple request (e.g., Put a washed apple in the kitchen fridge),...
Recent years have seen a flourishing of neural keyphrase generation work...
Graph neural networks (GNNs) have been attracting increasing popularity ...
Knowledge Distillation (KD) is a common method for transferring the
“kno...
Playing text-based games requires skill in processing natural language a...
We are interested in learning how to update Knowledge Graphs (KG) from t...
A hallmark of human intelligence is the ability to understand and commun...
Recently, concatenating multiple keyphrases as a target sequence has bee...
Humans observe and interact with the world to acquire knowledge. However...
Existing machine reading comprehension (MRC) models do not scale effecti...
This paper tackles the problem of reading comprehension over long narrat...
To solve a text-based game, an agent needs to formulate valid text comma...
We propose a neural machine-reading model that constructs dynamic knowle...
Existing keyphrase generation studies suffer from the problems of genera...
We introduce TextWorld, a sandbox learning environment for the training ...
We propose a recurrent RL agent with an episodic exploration mechanism t...
We describe a mechanism by which artificial neural networks can learn ra...
A hallmark of human intelligence and cognition is its flexibility. One o...
We propose a two-stage neural model to tackle question generation from
d...
We propose a generative machine comprehension model that learns jointly ...
We propose a recurrent neural model that generates natural-language ques...
We present NewsQA, a challenging machine comprehension dataset of over
1...
We present the EpiReader, a novel model for machine comprehension of tex...
Understanding unstructured text is a major goal within natural language
...