4 papers · 1 filter
Exploration of Summarization by Generative Language Models for Automated Scoring of Long Essays
Haowei Hua, Hong Jiao, Xinyi Wang
BERT and its variants are extensively explored for automated scoring. However, a limit of 512 tokens for these encoder-based models showed the deficiency in automated scoring of lo…
Encoder-Decoder or Decoder-Only? Revisiting Encoder-Decoder Large Language Model
Biao Zhang, Yong Cheng, Siamak Shakeri +3
Recent large language model (LLM) research has undergone an architectural shift from encoder-decoder modeling to nowadays the dominant decoder-only modeling. This rapid transition,…
Language and Task Arithmetic with Parameter-Efficient Layers for Zero-Shot Summarization
Alexandra Chronopoulou, Jonas Pfeiffer, Joshua Maynez +3
Parameter-efficient fine-tuning (PEFT) using labeled task data can significantly improve the performance of large language models (LLMs) on the downstream task. However, there are…
Inducing Generalization across Languages and Tasks using Featurized Low-Rank Mixtures
Chu-Cheng Lin, Xinyi Wang, Jonathan H. Clark +4
Adapting pretrained large language models (LLMs) to various downstream tasks in tens or hundreds of human languages is computationally expensive. Parameter-efficient fine-tuning (P…