5 citations · 6 across the 6 of their papers we have counts for
3 papers · 1 filter
MiraMind: Benchmarking Reliable Mental Health Reasoning beyond Answer Accuracy
Mengxi Xiao, Kailai Yang, Pengde Zhao +12
Mental-health reasoning with large language models (LLMs) is an evidence-constrained judgment problem: models must transform limited, subjective, and often ambiguous evidence into…
Scalable Multi-Domain Adaptation of Language Models using Modular Experts
Peter Schafhalter, Shun Liao, Yanqi Zhou +3
Domain-specific adaptation is critical to maximizing the performance of pre-trained language models (PLMs) on one or multiple targeted tasks, especially under resource-constrained…
What Are the Odds? Language Models Are Capable of Probabilistic Reasoning
Akshay Paruchuri, Jake Garrison, Shun Liao +5
Language models (LM) are capable of remarkably complex linguistic tasks; however, numerical reasoning is an area in which they frequently struggle. An important but rarely evaluate…