3 papers
cs.CL2025
Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data
Siqi Guo, Ilgee Hong, Vicente Balmaseda +6
Supervised fine-tuning (SFT) has become a crucial step for aligning pretrained large language models (LLMs) using supervised datasets of input-output pairs. However, despite being…
cs.LG2025
Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
Vicente Balmaseda, Bokun Wang, Ching-Long Lin +1
In self-supervised contrastive learning, negative pairs are typically constructed using an anchor image and a sample drawn from the entire dataset, excluding the anchor. However, t…
cs.DS2024
Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better
Vicente Balmaseda, Ying Xu, Yixin Cao +1
Cluster deletion is an NP-hard graph clustering objective with applications in computational biology and social network analysis, where the goal is to delete a minimum number of ed…