18 citations · 33 across the 5 of their papers we have counts for
18 papers
Multimodal Knowledge Alignment with Reinforcement Learning
Youngjae Yu, Jiwan Chung, Heeseung Yun +8
Large language models readily adapt to novel settings, even without task-specific training data. Can their zero-shot capacity be extended to multimodal inputs? In this work, we pro…
CommonsenseQA 2.0: Exposing the Limits of AI through Gamification
Alon Talmor, Ori Yoran, Ronan Le Bras +4
Constructing benchmarks that test the abilities of modern natural language understanding models is difficult - pre-trained language models exploit artifacts in benchmarks to achiev…
proScript: Partially Ordered Scripts Generation via Pre-trained Language Models
Keisuke Sakaguchi, Chandra Bhagavatula, Ronan Le Bras +3
Scripts - standardized event sequences describing typical everyday activities - have been shown to help understand narratives by providing expectations, resolving ambiguity, and fi…
NaturalProofs: Mathematical Theorem Proving in Natural Language
Sean Welleck, Jiacheng Liu, Ronan Le Bras +3
Understanding and creating mathematics using natural mathematical language - the mixture of symbolic and natural language used by humans - is a challenging and important problem fo…
UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark
Nicholas Lourie, Ronan Le Bras, Chandra Bhagavatula +1
Commonsense AI has long been seen as a near impossible goal -- until recently. Now, research interest has sharply increased with an influx of new benchmarks and models. We propose…
Analyzing Commonsense Emergence in Few-shot Knowledge Models
Jeff Da, Ronan Le Bras, Ximing Lu +2
Recently, commonsense knowledge models - pretrained language models (LM) fine-tuned on knowledge graph (KG) tuples - showed that considerable amounts of commonsense knowledge can b…