34 citations · 93 across the 19 of their papers we have counts for
5 papers · 1 filter
TopicGPT: A Prompt-based Topic Modeling Framework
Chau Minh Pham, Alexander Hoyle, Simeng Sun +2
Topic modeling is a well-established technique for exploring text corpora. Conventional topic models (e.g., LDA) represent topics as bags of words that often require "reading the t…
Exploring the impact of low-rank adaptation on the performance, efficiency, and regularization of RLHF
Simeng Sun, Dhawal Gupta, Mohit Iyyer
During the last stage of RLHF, a large language model is aligned to human intents via PPO training, a process that generally requires large-scale computational resources. In this t…
PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documents
Simeng Sun, Yang Liu, Shuohang Wang +2
Strategies such as chain-of-thought prompting improve the performance of large language models (LLMs) on complex reasoning tasks by decomposing input examples into intermediate ste…
How Does In-Context Learning Help Prompt Tuning?
Simeng Sun, Yang Liu, Dan Iter +2
Fine-tuning large language models is becoming ever more impractical due to their rapidly-growing scale. This motivates the use of parameter-efficient adaptation methods such as pro…
Efficiently Upgrading Multilingual Machine Translation Models to Support More Languages
Simeng Sun, Maha Elbayad, Anna Sun +1
With multilingual machine translation (MMT) models continuing to grow in size and number of supported languages, it is natural to reuse and upgrade existing models to save computat…