21 citations · 21 across the 3 of their papers we have counts for
4 papers
Generalizing Multimodal Foundational Models in Context-Driven Class Incremental Learning
Avi Gupta, Nilotpal Sinha, Vishnu Raj +4
Class-Incremental Learning (CIL) aims to learn new classes continuously without forgetting the previously learned ones. Recent works in CIL have significantly advanced across vario…
Listen, Look, and Learn: Learning Without Forgetting through SAM-Audio
Avi Gupta, Nilotpal Sinha, Vishnu Raj +4
Class-Incremental Learning (CIL) aims to continuously learn new classes without forgetting previously acquired knowledge. While recent CIL advances have spurred significant interes…
Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning
Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi +2
Safety aligned Large Language Models (LLMs) are vulnerable to harmful fine-tuning attacks -- a few harmful data mixed in the fine-tuning dataset can break the LLMs's safety alignme…
CodeGemma: Open Code Models Based on Gemma
CodeGemma Team, Heri Zhao, Jeffrey Hui +24
This paper introduces CodeGemma, a collection of specialized open code models built on top of Gemma, capable of a variety of code and natural language generation tasks. We release…