626 citations · 1.7k across the 87 of their papers we have counts for
11 papers · 1 filter
Improved Latent Tree Induction with Distant Supervision via Span Constraints
Zhiyang Xu, Andrew Drozdov, Jay Yoon Lee +6
For over thirty years, researchers have developed and analyzed methods for latent tree induction as an approach for unsupervised syntactic parsing. Nonetheless, modern systems stil…
Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration
Shufan Wang, Laure Thompson, Mohit Iyyer
Phrase representations derived from BERT often do not exhibit complex phrasal compositionality, as the model relies instead on lexical similarity to determine semantic relatedness.…
Do Long-Range Language Models Actually Use Long-Range Context?
Simeng Sun, Kalpesh Krishna, Andrew Mattarella-Micke +1
Language models are generally trained on short, truncated input sequences, which limits their ability to use discourse-level information present in long-range context to improve th…
The Perils of Using Mechanical Turk to Evaluate Open-Ended Text Generation
Marzena Karpinska, Nader Akoury, Mohit Iyyer
Recent text generation research has increasingly focused on open-ended domains such as story and poetry generation. Because models built for such tasks are difficult to evaluate au…
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning
Tu Vu, Minh-Thang Luong, Quoc V. Le +2
Despite their recent successes in tackling many NLP tasks, large-scale pre-trained language models do not perform as well in few-shot settings where only a handful of training exam…
TABBIE: Pretrained Representations of Tabular Data
Hiroshi Iida, Dung Thai, Varun Manjunatha +1
Existing work on tabular representation learning jointly models tables and associated text using self-supervised objective functions derived from pretrained language models such as…
Revisiting Simple Neural Probabilistic Language Models
Simeng Sun, Mohit Iyyer
Recent progress in language modeling has been driven not only by advances in neural architectures, but also through hardware and optimization improvements. In this paper, we revisi…
IGA : An Intent-Guided Authoring Assistant
Simeng Sun, Wenlong Zhao, Varun Manjunatha +5
While large-scale pretrained language models have significantly improved writing assistance functionalities such as autocomplete, more complex and controllable writing assistants h…
Changing the Mind of Transformers for Topically-Controllable Language Generation
Haw-Shiuan Chang, Jiaming Yuan, Mohit Iyyer +1
Large Transformer-based language models can aid human authors by suggesting plausible continuations of text written so far. However, current interactive writing assistants do not a…
Weakly-Supervised Open-Retrieval Conversational Question Answering
Chen Qu, Liu Yang, Cen Chen +3
Recent studies on Question Answering (QA) and Conversational QA (ConvQA) emphasize the role of retrieval: a system first retrieves evidence from a large collection and then extract…
Hurdles to Progress in Long-form Question Answering
Kalpesh Krishna, Aurko Roy, Mohit Iyyer
The task of long-form question answering (LFQA) involves retrieving documents relevant to a given question and using them to generate a paragraph-length answer. While many models h…