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Found 7 papers, 4 papers with code
Continual Learning of Large Language Models: A Comprehensive Survey
In this survey, we provide a comprehensive overview of the current research progress on LLMs within the context of CL.
LLM Jailbreak Attack versus Defense Techniques -- A Comprehensive Study
Large Language Models (LLMS) have increasingly become central to generating content with potential societal impacts.
Continual Learning via Manifold Expansion Replay
To address this problem, we propose a novel replay strategy called Manifold Expansion Replay (MaER).
Taxonomy-Structured Domain Adaptation
Domain adaptation aims to mitigate distribution shifts among different domains.
Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation
To address this challenge, we first provide a formal definition of domain index from the probabilistic perspective, and then propose an adversarial variational Bayesian framework that infers domain indices from multi-domain data, thereby providing additional insight on domain relations and improving domain adaptation performance.
Graph-Relational Domain Adaptation
In this work, we relax such uniform alignment by using a domain graph to encode domain adjacency, e. g., a graph of states in the US with each state as a domain and each edge indicating adjacency, thereby allowing domains to align flexibly based on the graph structure.
Visual Rhythm Prediction with Feature-Aligning Network
In this paper, we propose a data-driven visual rhythm prediction method, which overcomes the previous works' deficiency that predictions are made primarily by human-crafted hard rules.
