Search Results for author:
Found 10 papers, 3 papers with code
Novel Chapter Abstractive Summarization using Spinal Tree Aware Sub-Sentential Content Selection
Summarizing novel chapters is a difficult task due to the input length and the fact that sentences that appear in the desired summaries draw content from multiple places throughout the chapter.
Contrastive Training Improves Zero-Shot Classification of Semi-structured Documents
The standard classification setting where categories are fixed during both training and testing falls short in dynamic environments where new document categories could potentially emerge.
Few-shot Reranking for Multi-hop QA via Language Model Prompting
To alleviate the need for a large number of labeled question-document pairs for retriever training, we propose PromptRank, which relies on large language models prompting for multi-hop path reranking.
A Bag of Tricks for Dialogue Summarization
Dialogue summarization comes with its own peculiar challenges as opposed to news or scientific articles summarization.
Zero-Resource Multi-Dialectal Arabic Natural Language Understanding
In this paper, we investigate the zero-shot performance on Dialectal Arabic (DA) when fine-tuning a PLM on modern standard Arabic (MSA) data only -- identifying a significant performance drop when evaluating such models on DA.
Self-Training Pre-Trained Language Models for Zero- and Few-Shot Multi-Dialectal Arabic Sequence Labeling
We propose to self-train pre-trained language models in zero- and few-shot scenarios to improve performance on data-scarce varieties using only resources from data-rich ones.
A Distributional Approach to Controlled Text Generation
From that optimal representation we then train a target controlled Autoregressive LM through an adaptive distributional variant of Policy Gradient.
Extracting Synonyms from Bilingual Dictionaries
We present our progress in developing a novel algorithm to extract synonyms from bilingual dictionaries.
Book Success Prediction with Pretrained Sentence Embeddings and Readability Scores
Predicting the potential success of a book in advance is vital in many applications.
Semantic Source Code Search: A Study of the Past and a Glimpse at the Future
With the recent explosion in the size and complexity of source codebases and software projects, the need for efficient source code search engines has increased dramatically.
