From the 1 of 5 linked papers with an AI index.
5 papers
From Critic to Confidence: PPO for Language-Based Quantitative Prediction with Confidence Estimation
Mehak Dhaliwal, Rasta Tadayon, Andong Hua +2
The paper introduces CARE-PPO, a reinforcement‑learning framework that fine‑tunes large language models to make accurate numeric predictions while simultaneously learning confidenc…
Model Collapse in the Self-Consuming Chain of Diffusion Finetuning: A Novel Perspective from Quantitative Trait Modeling
Youngseok Yoon, Dainong Hu, Iain Weissburg +2
Model collapse, the severe degradation of generative models when iteratively trained on their own outputs, has gained significant attention in recent years. This paper examines Cha…
Mix from Failure: Confusion-Pairing Mixup for Long-Tailed Recognition
Youngseok Yoon, Sangwoo Hong, Hyungjun Joo +3
Long-tailed image recognition is a computer vision problem considering a real-world class distribution rather than an artificial uniform. Existing methods typically detour the prob…
LLMs are Biased Teachers: Evaluating LLM Bias in Personalized Education
Iain Weissburg, Sathvika Anand, Sharon Levy +1
With the increasing adoption of large language models (LLMs) in education, concerns about inherent biases in these models have gained prominence. We evaluate LLMs for bias in the p…
A Survey on Data Selection for Language Models
Alon Albalak, Yanai Elazar, Sang Michael Xie +11
A major factor in the recent success of large language models is the use of enormous and ever-growing text datasets for unsupervised pre-training. However, naively training a model…