Chengwei Qin

Contrastive Learning with Generated Representations for Inductive Knowledge Graph Embedding

2023

With the evolution of Knowledge Graphs (KGs), new entities emerge which are not seen before. Representation learning of KGs in such an inductive setting aims to capture and transfer the structural patterns from existing entities …

PromptSum: Parameter-Efficient Controllable Abstractive Summarization

2023 · arXiv (Cornell University)

Prompt tuning (PT), a parameter-efficient technique that only tunes the additional prompt embeddings while keeping the backbone pre-trained language model (PLM) frozen, has shown promising results in language understanding tasks, especially in low-resource scenarios. However, …

ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?

2023 · arXiv (Cornell University)

Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce. Through instruction-tuning a large language model (LLM) with supervised fine-tuning and reinforcement …

Is GPT-3 a Good Data Annotator?

2023

Bosheng Ding, Chengwei Qin, Linlin Liu, Yew Ken Chia, Boyang Li, Shafiq Joty, Lidong Bing. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.

Is ChatGPT a General-Purpose Natural Language Processing Task Solver?

2023

Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot—i.e., without adaptation on downstream data. Recently, the debut of ChatGPT has …