2 citations · 4 across the 5 of their papers we have counts for
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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…
RARE: Retrieval-Aware Robustness Evaluation for Retrieval-Augmented Generation Systems
Yixiao Zeng, Tianyu Cao, Danqing Wang +5
Retrieval-Augmented Generation (RAG) enhances recency and factuality in answers. However, existing evaluations rarely test how well these systems cope with real-world noise, confli…
Out of Style: RAG's Fragility to Linguistic Variation
Tianyu Cao, Neel Bhandari, Akhila Yerukola +2
Despite the impressive performance of Retrieval-augmented Generation (RAG) systems across various NLP benchmarks, their robustness in handling real-world user-LLM interaction queri…
Characterizing Multimodal Long-form Summarization: A Case Study on Financial Reports
Tianyu Cao, Natraj Raman, Danial Dervovic +1
As large language models (LLMs) expand the power of natural language processing to handle long inputs, rigorous and systematic analyses are necessary to understand their abilities…