46 citations · 50 across the 12 of their papers we have counts for
5 papers · 1 filter
FinRT: Distilling Adaptive Red-Teaming Strategies into Reusable Adversarial Generators in Consumer Finance
Rikhiya Ghosh, Himanshu Kumar, Sriram Venkatapathy +3
In regulated industries like consumer finance, seemingly harmless user queries can exploit large language model vulnerabilities, triggering safety failures and pushing responses da…
Building Safe GenAI Applications: An End-to-End Overview of Red Teaming for Large Language Models
Alberto Purpura, Sahil Wadhwa, Jesse Zymet +5
The rapid growth of Large Language Models (LLMs) presents significant privacy, security, and ethical concerns. While much research has proposed methods for defending LLM systems ag…
Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment
Melissa Kazemi Rad, Huy Nghiem, Andy Luo +3
Large Language Models (LLMs) have demonstrated powerful capabilities that render them valuable in different applications, including conversational AI products. It is paramount to e…
Northeastern Uni at Multilingual Counterspeech Generation: Enhancing Counter Speech Generation with LLM Alignment through Direct Preference Optimization
Sahil Wadhwa, Chengtian Xu, Haoming Chen +3
The automatic generation of counter-speech (CS) is a critical strategy for addressing hate speech by providing constructive and informed responses. However, existing methods often…
Contextualized End-to-End Neural Entity Linking
Haotian Chen, Andrej Zukov-Gregoric, Xi David Li +1
We propose yet another entity linking model (YELM) which links words to entities instead of spans. This overcomes any difficulties associated with the selection of good candidate m…