46 citations · 158 across the 33 of their papers we have counts for
9 papers
On the Limits of Evaluating Embodied Agent Model Generalization Using Validation Sets
Hyounghun Kim, Aishwarya Padmakumar, Di Jin +2
Natural language guided embodied task completion is a challenging problem since it requires understanding natural language instructions, aligning them with egocentric visual observ…
FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization
David Wan, Mohit Bansal
We present FactPEGASUS, an abstractive summarization model that addresses the problem of factuality during pre-training and fine-tuning: (1) We augment the sentence selection strat…
Efficient Few-Shot Fine-Tuning for Opinion Summarization
Arthur Bražinskas, Ramesh Nallapati, Mohit Bansal +1
Abstractive summarization models are typically pre-trained on large amounts of generic texts, then fine-tuned on tens or hundreds of thousands of annotated samples. However, in opi…
How can NLP Help Revitalize Endangered Languages? A Case Study and Roadmap for the Cherokee Language
Shiyue Zhang, Ben Frey, Mohit Bansal
More than 43% of the languages spoken in the world are endangered, and language loss currently occurs at an accelerated rate because of globalization and neocolonialism. Saving and…
Identify, Align, and Integrate: Matching Knowledge Graphs to Commonsense Reasoning Tasks
Lisa Bauer, Mohit Bansal
Integrating external knowledge into commonsense reasoning tasks has shown progress in resolving some, but not all, knowledge gaps in these tasks. For knowledge integration to yield…
Coherent Dialogue with Attention-based Language Models
Hongyuan Mei, Mohit Bansal, Matthew R. Walter
We model coherent conversation continuation via RNN-based dialogue models equipped with a dynamic attention mechanism. Our attention-RNN language model dynamically increases the sc…