7 papers
Perception-aware Sampling for Scatterplot Visualizations
Zafeiria Moumoulidou, Hamza Elhamdadi, Ke Yang +3
Visualizing data is often a crucial first step in data analytics workflows, but growing data sizes pose challenges due to computational and visual perception limitations. As a resu…
CachePrune: Teaching LLMs What Not to Follow via KV-Cache Editing
Rui Wang, Junda Wu, Yu Xia +6
Large Language Models (LLMs) are susceptible to indirect prompt injection attacks, where the model inadvertently responds to instructions injected into the prompt context. This vul…
Pluralistic Off-policy Evaluation and Alignment
Chengkai Huang, Junda Wu, Zhouhang Xie +6
Personalized preference alignment for LLMs with diverse human preferences requires evaluation and alignment methods that capture pluralism. Most existing preference alignment datas…
Personalization of Large Language Models: A Survey
Zhehao Zhang, Ryan A. Rossi, Branislav Kveton +18
Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications. Despite the importance and recent progress, most exist…
RCStat: A Statistical Framework for using Relative Contextualization in Transformers
Debabrata Mahapatra, Shubham Agarwal, Apoorv Saxena +1
Prior work on input-token importance in auto-regressive transformers has relied on Softmax-normalized attention weights, which obscure the richer structure of pre-Softmax query-key…
Cache-Craft: Managing Chunk-Caches for Efficient Retrieval-Augmented Generation
Shubham Agarwal, Sai Sundaresan, Subrata Mitra +6
Retrieval-Augmented Generation (RAG) is often used with Large Language Models (LLMs) to infuse domain knowledge or user-specific information. In RAG, given a user query, a retrieve…