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Related Papers
Impact of Citing Papers for Summarisation of Clinical Documents
In this paper we show that information from citing papers can help perform ex- tractive summarisation of medical publica- tions, especially when the amount of text available for development is …...
Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization
AbstractDeep reinforcement learning (RL) has been a commonly-used strategy for the abstractive summarization task to address both the exposure bias and non-differentiable task issues. However, the conventional reward Rouge-L simply …...
Putting the Horse before the Cart: A Generator-Evaluator Framework for Question Generation from Text
AbstractAutomatic question generation (QG) is a useful yet challenging task in NLP. Recent neural network-based approaches represent the state-of-the-art in this task. In this work, we attempt to strengthen them …...
Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives
AbstractThis paper tackles the problem of reading comprehension over long narratives where documents easily span over thousands of tokens. We propose a curriculum learning (CL) based Pointer-Generator framework for reading/sampling …...
PyMT5: multi-mode translation of natural language and Python code with transformers
AbstractSimultaneously modeling source code and natural language has many exciting applications in automated software development and understanding. Pursuant to achieving such technology, we introduce PyMT5, the Python method text-to-text transfer …...
DESCGEN: A Distantly Supervised Datasetfor Generating Entity Descriptions
AbstractShort textual descriptions of entities provide summaries of their key attributes and have been shown to be useful sources of background knowledge for tasks such as entity linking and question …...
Mathematical Word Problem Generation from Commonsense Knowledge Graph and Equations
AbstractThere is an increasing interest in the use of mathematical word problem (MWP) generation in educational assessment. Different from standard natural question generation, MWP generation needs to maintain the underlying …...
Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study
AbstractRecent advancements in open-domain question answering (ODQA), that is, finding answers from large open-domain corpus like Wikipedia, have led to human-level performance on many datasets. However, progress in QA over …...
ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and Effective Text Generation
AbstractWe study the text generation task under the approach of pre-trained language models (PLMs). Typically, an auto-regressive (AR) method is adopted for generating texts in a token-by-token manner. Despite many …...
Gui at MixMT 2022 : English-Hinglish : An MT Approach for Translation of Code Mixed Data
AbstractCode-mixed machine translation has become an important task in multilingual communities and extending the task of machine translation to code mixed data has become a common task for these languages. …...
SIT at MixMT 2022: Fluent Translation Built on Giant Pre-trained Models
AbstractThis paper describes the Stevens Institute of Technology’s submission for the WMT 2022 Shared Task: Code-mixed Machine Translation (MixMT). The task consisted of two subtasks, subtask 1 Hindi/English to Hinglish …...
Element-aware Summarization with Large Language Models: Expert-aligned Evaluation and Chain-of-Thought Method
AbstractAutomatic summarization generates concise summaries that contain key ideas of source documents. As the most mainstream datasets for the news sub-domain, CNN/DailyMail and BBC XSum have been widely used for …...