7 citations · 7 across the 1 of their papers we have counts for
3 papers
cs.CL2023★ 7 cited
One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support
Ronja Stern, Vishvaksenan Rasiah, Veton Matoshi +5
Recent strides in Large Language Models (LLMs) have saturated many Natural Language Processing (NLP) benchmarks, emphasizing the need for more challenging ones to properly assess L…
cs.CL2020
RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms
Pei Zhou, Rahul Khanna, Seyeon Lee +4
Pre-trained language models (PTLMs) have achieved impressive performance on commonsense inference benchmarks, but their ability to employ commonsense to make robust inferences, whi…
cs.CV2017
Improvements to context based self-supervised learning
T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen
We develop a set of methods to improve on the results of self-supervised learning using context. We start with a baseline of patch based arrangement context learning and go from th…