arXiv:2210.12478
공식 코드 · Papers with Code
DiscoSense: Commonsense Reasoning with Discourse Connectives
원문 초록
We present DiscoSense, a benchmark for commonsense reasoning via understanding a wide variety of discourse connectives. We generate compelling distractors in DiscoSense using Conditional Adversarial Filtering, an extension of Adversarial Filtering that employs conditional generation. We show that state-of-the-art pre-trained language models struggle to perform well on DiscoSense, which makes this dataset ideal for evaluating next-generation commonsense reasoning systems.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
KatzBot: Revolutionizing Academic Chatbot for Enhanced Communication
Mixture-of-Subspaces in Low-Rank Adaptation
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
Language Model Sentence Completion with a Parser-Driven Rhetorical Control Method
Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
토론
이 논문과 연결된 포럼 글이 아직 없습니다.