6 papers
Carefully Considering Culture: Analyzing LLM Alignment in Single- and Multi-Cultural Settings using Cultural Consensus Theory
Krishna Pothugunta, John P. Lalor
Recent work in NLP has probed large language models for their understanding of cultural norms across countries. However, this work typically considers distributional patterns, igno…
Every Eval Ever: A Unifying Schema and Community Repository for AI Evaluation Results
Jan Batzner, Sree Harsha Nelaturu, Damian Stachura +45
AI evaluations are widely used for testing and understanding progress. However, the diverse evaluators bring with them inconsistencies that challenge analysis and comparison. First…
TopoCL: Topological Contrastive Learning for Medical Imaging
Guangyu Meng, Pengfei Gu, Peixian Liang +3
Contrastive learning (CL) has become a powerful approach for learning representations from unlabeled images. However, existing CL methods focus predominantly on visual appearance f…
A Psychology-based Unified Dynamic Framework for Curriculum Learning
Guangyu Meng, Qingkai Zeng, John P. Lalor +1
Directly learning from examples of varying difficulty levels is often challenging for both humans and machine learning models. A more effective strategy involves exposing learners…
From Stars to Insights: Exploration and Implementation of Unified Sentiment Analysis with Distant Supervision
Wenchang Li, John P. Lalor, Yixing Chen +1
Sentiment analysis is integral to understanding the voice of the customer and informing businesses' strategic decisions. Conventional sentiment analysis involves three separate tas…
Bridging the LLM Accessibility Divide? Performance, Fairness, and Cost of Closed versus Open LLMs for Automated Essay Scoring
Kezia Oketch, John P. Lalor, Yi Yang +1
Closed large language models (LLMs) such as GPT-4 have set state-of-the-art results across a number of NLP tasks and have become central to NLP and machine learning (ML)-driven sol…