activity
20162022
most citedA Joint Model for Question Answering and Question Generation

83 citations · 129 across the 7 of their papers we have counts for

collaborators

22 papers

cs.CL2022

Selecting Better Samples from Pre-trained LLMs: A Case Study on Question Generation

Xingdi Yuan, Tong Wang, Yen-Hsiang Wang +5

Large Language Models (LLMs) have in recent years demonstrated impressive prowess in natural language generation. A common practice to improve generation diversity is to sample mul…

cs.CL20222 cited

One-Shot Learning from a Demonstration with Hierarchical Latent Language

Nathaniel Weir, Xingdi Yuan, Marc-Alexandre Côté +5

Humans have the capability, aided by the expressive compositionality of their language, to learn quickly by demonstration. They are able to describe unseen task-performing procedur…

cs.CL20211 cited

Interactive Machine Comprehension with Dynamic Knowledge Graphs

Xingdi Yuan

Interactive machine reading comprehension (iMRC) is machine comprehension tasks where knowledge sources are partially observable. An agent must interact with an environment sequent…

cs.CL20211 cited

Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents

Rui Meng, Khushboo Thaker, Lei Zhang +4

Faceted summarization provides briefings of a document from different perspectives. Readers can quickly comprehend the main points of a long document with the help of a structured…

cs.CL2020

ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté +3

Given a simple request like Put a washed apple in the kitchen fridge, humans can reason in purely abstract terms by imagining action sequences and scoring their likelihood of succe…

cs.CL2020

An Empirical Study on Neural Keyphrase Generation

Rui Meng, Xingdi Yuan, Tong Wang +3

Recent years have seen a flourishing of neural keyphrase generation (KPG) works, including the release of several large-scale datasets and a host of new models to tackle them. Mode…