paper summaries
The paper discusses the limitations of pre-trained language representations in NLP systems and the need for task-specific datasets and fine-tuning. The authors show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competitiveness with pri
paper summaries
The paper proposes a new network architecture called Transformer that relies solely on attention mechanisms, dispensing with recurrence and convolutions entirely. The Transformer allows for significantly more parallelization and can reach a new state of the art in translation quality while requirin
paper summaries
The paper proposes a novel communicative agent framework named role-playing to facilitate autonomous cooperation among communicative agents and provide insight into their “cognitive” processes. The approach involves using inception prompting to guide chat agents toward task completion while maintai