163 citations · 539 across the 205 of their papers we have counts for
7 papers · 1 filter
DenoiseRank: Learning to Rank by Diffusion Models
Ying Wang, Preslav Nakov, Shangsong Liang
Learning to rank (LTR) is one of the core tasks in Machine Learning. Traditional LTR models have made great progress, but nearly all of them are implemented from discriminative per…
FinCARDS: Card-Based Analyst Reranking for Financial Document Question Answering
Yixi Zhou, Fan Zhang, Yu Chen +3
Financial question answering (QA) over long corporate filings requires evidence to satisfy strict constraints on entities, financial metrics, fiscal periods, and numeric values. Ho…
VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration
Jiahui Geng, Qing Li, Zongxiong Chen +7
The rapid advancement of vision-language models (VLMs) has brought a lot of attention to their safety alignment. However, existing methods have primarily focused on model undersafe…
Fast or Better? Balancing Accuracy and Cost in Retrieval-Augmented Generation with Flexible User Control
Jinyan Su, Jennifer Healey, Preslav Nakov +1
Retrieval-Augmented Generation (RAG) has emerged as a powerful approach to mitigate large language model (LLM) hallucinations by incorporating external knowledge retrieval. However…
Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under Adversarial Poisoning Attacks
Jinyan Su, Jin Peng Zhou, Zhengxin Zhang +2
Retrieval-Augmented Generation (RAG) systems have emerged as a promising solution to mitigate LLM hallucinations and enhance their performance in knowledge-intensive domains. Howev…
FIRE: Fact-checking with Iterative Retrieval and Verification
Zhuohan Xie, Rui Xing, Yuxia Wang +5
Fact-checking long-form text is challenging, and it is therefore common practice to break it down into multiple atomic claims. The typical approach to fact-checking these atomic cl…
Corpus Poisoning via Approximate Greedy Gradient Descent
Jinyan Su, Preslav Nakov, Claire Cardie
Dense retrievers are widely used in information retrieval and have also been successfully extended to other knowledge intensive areas such as language models, e.g., Retrieval-Augme…