3 papers
cs.CL2026
Overcoming the "Impracticality" of RAG: Proposing a Real-World Benchmark and Multi-Dimensional Diagnostic Framework
Kenichirou Narita, Siqi Peng, Taku Fukui +3
Performance evaluation of Retrieval-Augmented Generation (RAG) systems within enterprise environments is governed by multi-dimensional and composite factors extending far beyond si…
cs.CL2025
BRIT: Bidirectional Retrieval over Unified Image-Text Graph
Ainulla Khan, Yamada Moyuru, Srinidhi Akella
Retrieval-Augmented Generation (RAG) has emerged as a promising technique to enhance the quality and relevance of responses generated by large language models. While recent advance…
cs.CV2024
Semantic Graph Consistency: Going Beyond Patches for Regularizing Self-Supervised Vision Transformers
Chaitanya Devaguptapu, Sumukh Aithal, Shrinivas Ramasubramanian +2
Self-supervised learning (SSL) with vision transformers (ViTs) has proven effective for representation learning as demonstrated by the impressive performance on various downstream…