2 papers
cs.CL2025
Evaluating the Retrieval Robustness of Large Language Models
Shuyang Cao, Karthik Radhakrishnan, David Rosenberg +4
Retrieval-augmented generation (RAG) generally enhances large language models' (LLMs) ability to solve knowledge-intensive tasks. But RAG may also lead to performance degradation d…
cs.CL2025
Understanding and Mitigating Risks of Generative AI in Financial Services
Sebastian Gehrmann, Claire Huang, Xian Teng +9
To responsibly develop Generative AI (GenAI) products, it is critical to define the scope of acceptable inputs and outputs. What constitutes a "safe" response is an actively debate…