4 papers · 1 filter
SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment
Yuqing Huang, Rongyang Zhang, Qimeng Wang +9
Recent advancements in large language models (LLMs) have revolutionized natural language processing through their remarkable capabilities in understanding and executing diverse tas…
Locating and Mitigating Gender Bias in Large Language Models
Yuchen Cai, Ding Cao, Rongxi Guo +3
Large language models(LLM) are pre-trained on extensive corpora to learn facts and human cognition which contain human preferences. However, this process can inadvertently lead to…
Editing Knowledge Representation of Language Model via Rephrased Prefix Prompts
Yuchen Cai, Ding Cao, Rongxi Guo +3
Neural language models (LMs) have been extensively trained on vast corpora to store factual knowledge about various aspects of the world described in texts. Current technologies ty…
Towards Generalist Prompting for Large Language Models by Mental Models
Haoxiang Guan, Jiyan He, Shuxin Zheng +3
Large language models (LLMs) have demonstrated impressive performance on many tasks. However, to achieve optimal performance, specially designed prompting methods are still needed.…