4 papers
DERELAB: Probing Defeasible Reasoning and Confirmation Bias in LLMs with a Generative Benchmark
Jayanta Sadhu, Sayem Shahad, Kenneth Marino
Defeasible reasoning is a type of reasoning where inferences are drawn from plausible current evidence, but can be retracted upon the introduction of newer evidence. Although recen…
Language-Critique Imitation Learning from Suboptimal Demonstrations
Chih-Han Yang, Dai-Jie Wu, Yun-Ping Huang +3
Prior work on imitation learning from suboptimal demonstrations typically relies on compressed supervision signals such as confidence estimates, discriminator scores, or importance…
BriefMe: A Legal NLP Benchmark for Assisting with Legal Briefs
Jesse Woo, Fateme Hashemi Chaleshtori, Ana Marasović +1
A core part of legal work that has been under-explored in Legal NLP is the writing and editing of legal briefs. This requires not only a thorough understanding of the law of a juri…
Language Agents Mirror Human Causal Reasoning Biases. How Can We Help Them Think Like Scientists?
Anthony GX-Chen, Dongyan Lin, Mandana Samiei +4
Language model (LM) agents are increasingly used as autonomous decision-makers which need to actively gather information to guide their decisions. A crucial cognitive skill for suc…