16 citations · 31 across the 11 of their papers we have counts for
11 papers
Flexi-LoRA with Input-Adaptive Ranks: Efficient Finetuning for Speech and Reasoning Tasks
Zongqian Li, Yixuan Su, Han Zhou +2
Parameter-efficient fine-tuning methods like Low-Rank Adaptation (LoRA) have become essential for deploying large language models, yet their static parameter allocation remains sub…
Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective
Huayang Li, Tian Lan, Zihao Fu +5
There are a number of diverging hypotheses about the neural text degeneration problem, i.e., generating repetitive and dull loops, which makes this problem both interesting and con…
BAND: Biomedical Alert News Dataset
Zihao Fu, Meiru Zhang, Zaiqiao Meng +3
Infectious disease outbreaks continue to pose a significant threat to human health and well-being. To improve disease surveillance and understanding of disease spread, several surv…
Biomedical Named Entity Recognition via Dictionary-based Synonym Generalization
Zihao Fu, Yixuan Su, Zaiqiao Meng +1
Biomedical named entity recognition is one of the core tasks in biomedical natural language processing (BioNLP). To tackle this task, numerous supervised/distantly supervised appro…
Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder
Zihao Fu, Wai Lam, Qian Yu +4
The sequence-to-sequence (seq2seq) task aims at generating the target sequence based on the given input source sequence. Traditionally, most of the seq2seq task is resolved by the…
COFFEE: A Contrastive Oracle-Free Framework for Event Extraction
Meiru Zhang, Yixuan Su, Zaiqiao Meng +2
Event extraction is a complex information extraction task that involves extracting events from unstructured text. Prior classification-based methods require comprehensive entity an…
A Stability Analysis of Fine-Tuning a Pre-Trained Model
Zihao Fu, Anthony Man-Cho So, Nigel Collier
Fine-tuning a pre-trained model (such as BERT, ALBERT, RoBERTa, T5, GPT, etc.) has proven to be one of the most promising paradigms in recent NLP research. However, numerous recent…
On the Effectiveness of Parameter-Efficient Fine-Tuning
Zihao Fu, Haoran Yang, Anthony Man-Cho So +3
Fine-tuning pre-trained models has been ubiquitously proven to be effective in a wide range of NLP tasks. However, fine-tuning the whole model is parameter inefficient as it always…
Informative Text Generation from Knowledge Triples
Zihao Fu, Yijiang River Dong, Lidong Bing +1
As the development of the encoder-decoder architecture, researchers are able to study the text generation tasks with broader types of data. Among them, KB-to-text aims at convertin…
A Theoretical Analysis of the Repetition Problem in Text Generation
Zihao Fu, Wai Lam, Anthony Man-Cho So +1
Text generation tasks, including translation, summarization, language models, and etc. see rapid growth during recent years. Despite the remarkable achievements, the repetition pro…
Partially-Aligned Data-to-Text Generation with Distant Supervision
Zihao Fu, Bei Shi, Wai Lam +2
The Data-to-Text task aims to generate human-readable text for describing some given structured data enabling more interpretability. However, the typical generation task is confine…