4 papers
TopoGuard: Graph Theory Based Defenses Against Split-Knowledge Attacks on RAG
Chahana Dahal, Zuobin Xiong
Production Retrieval Augmented Generation (RAG) systems rely on aggregating multiple external documents to answer complex queries. However, the retrieved documents introduce a new…
GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping
Chahana Dahal, Ashutosh Balasubramaniam, Zuobin Xiong
Unlearning knowledge is a pressing and challenging task in Large Language Models (LLMs) because of their unprecedented capability to memorize and digest training data at scale, rai…
Federated Retrieval-Augmented Generation: A Systematic Mapping Study
Abhijit Chakraborty, Chahana Dahal, Vivek Gupta
Federated Retrieval-Augmented Generation (Federated RAG) combines Federated Learning (FL), which enables distributed model training without exposing raw data, with Retrieval-Augmen…
Is Architectural Complexity Overrated? Competitive and Interpretable Knowledge Graph Completion with RelatE
Abhijit Chakraborty, Chahana Dahal, Ashutosh Balasubramaniam +2
We revisit the efficacy of simple, real-valued embedding models for knowledge graph completion and introduce RelatE, an interpretable and modular method that efficiently integrates…