4 papers
GrOCE:Graph-Guided Online Concept Erasure for Text-to-Image Diffusion Models
Ning Han, Zhenyu Ge, Feng Han +3
Concept erasure aims to remove harmful, inappropriate, or copyrighted content from text-to-image diffusion models while preserving non-target semantics. However, existing methods e…
SynerGen: Contextualized Generative Recommender for Unified Search and Recommendation
Vianne R. Gao, Chen Xue, Marc Versage +11
The dominant retrieve-then-rank pipeline in large-scale recommender systems suffers from mis-calibration and engineering overhead due to its architectural split and differing optim…
Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval
Yuxiang Liu, Tian Wang, Gourab Kundu +6
Transformer-based models such as BERT and E5 have significantly advanced text embedding by capturing rich contextual representations. However, many complex real-world queries requi…
InfoPO: On Mutual Information Maximization for Large Language Model Alignment
Teng Xiao, Zhen Ge, Sujay Sanghavi +5
We study the post-training of large language models (LLMs) with human preference data. Recently, direct preference optimization and its variants have shown considerable promise in…