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Editing large language models: Problems, methods, and opportunities
Despite the ability to train capable LLMs, the methodology for maintaining their relevancy
and rectifying errors remains elusive. To this end, the past few years have witnessed a surge …
and rectifying errors remains elusive. To this end, the past few years have witnessed a surge …
Large knowledge model: Perspectives and challenges
Humankind's understanding of the world is fundamentally linked to our perception and
cognition, with\emph {human languages} serving as one of the major carriers of\emph {world …
cognition, with\emph {human languages} serving as one of the major carriers of\emph {world …
Larimar: Large language models with episodic memory control
Efficient and accurate updating of knowledge stored in Large Language Models (LLMs) is
one of the most pressing research challenges today. This paper presents Larimar-a novel …
one of the most pressing research challenges today. This paper presents Larimar-a novel …
Instructedit: Instruction-based knowledge editing for large language models
Knowledge editing for large language models can offer an efficient solution to alter a
model's behavior without negatively impacting the overall performance. However, the …
model's behavior without negatively impacting the overall performance. However, the …
Configurable foundation models: Building llms from a modular perspective
Advancements in LLMs have recently unveiled challenges tied to computational efficiency
and continual scalability due to their requirements of huge parameters, making the …
and continual scalability due to their requirements of huge parameters, making the …
College: Concept embedding generation for large language models
Current language models are unable to quickly learn new concepts on the fly, often
requiring a more involved finetuning process to learn robustly. Prompting in-context is not …
requiring a more involved finetuning process to learn robustly. Prompting in-context is not …
Perturbation-restrained sequential model editing
Model editing is an emerging field that focuses on updating the knowledge embedded within
large language models (LLMs) without extensive retraining. However, current model editing …
large language models (LLMs) without extensive retraining. However, current model editing …
Editing Personality for Large Language Models
This paper introduces an innovative task focused on editing the personality traits of Large
Language Models (LLMs). This task seeks to adjust the models' responses to opinion …
Language Models (LLMs). This task seeks to adjust the models' responses to opinion …
ChroKnowledge: Unveiling Chronological Knowledge of Language Models in Multiple Domains
Large language models (LLMs) have significantly impacted many aspects of our lives.
However, assessing and ensuring their chronological knowledge remains challenging …
However, assessing and ensuring their chronological knowledge remains challenging …
Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing
Large language models (LLMs) have achieved remarkable performance on various natural
language tasks. However, they are trained on static corpora and their knowledge can …
language tasks. However, they are trained on static corpora and their knowledge can …