1k citations · 2.7k across the 61 of their papers we have counts for
12 papers · 1 filter
Searching for Effective Multilingual Fine-Tuning Methods: A Case Study in Summarization
Yiwei Qin, Graham Neubig, Pengfei Liu
Recently, a large number of tuning strategies have been proposed to adapt pre-trained language models to downstream tasks. In this paper, we perform an extensive empirical evaluati…
T5Score: Discriminative Fine-tuning of Generative Evaluation Metrics
Yiwei Qin, Weizhe Yuan, Graham Neubig +1
Modern embedding-based metrics for evaluation of generated text generally fall into one of two paradigms: discriminative metrics that are trained to directly predict which outputs…
Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation
Yixin Liu, Alexander R. Fabbri, Pengfei Liu +8
Human evaluation is the foundation upon which the evaluation of both summarization systems and automatic metrics rests. However, existing human evaluation studies for summarization…
PAL: Program-aided Language Models
Luyu Gao, Aman Madaan, Shuyan Zhou +5
Large language models (LLMs) have recently demonstrated an impressive ability to perform arithmetic and symbolic reasoning tasks, when provided with a few examples at test time ("f…
Artificial Neural Networks for Finger Vein Recognition: A Survey
Yimin Yin, Renye Zhang, Pengfei Liu +4
Finger vein recognition is an emerging biometric recognition technology. Different from the other biometric features on the body surface, the venous vascular tissue of the fingers…
KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models
Haris Widjaja, Kiril Gashteovski, Wiem Ben Rim +5
Knowledge Graphs (KGs) store information in the form of (head, predicate, tail)-triples. To augment KGs with new knowledge, researchers proposed models for KG Completion (KGC) task…
reStructured Pre-training
Weizhe Yuan, Pengfei Liu
In this work, we try to decipher the internal connection of NLP technology development in the past decades, searching for essence, which rewards us with a (potential) new learning…
Are All the Datasets in Benchmark Necessary? A Pilot Study of Dataset Evaluation for Text Classification
Yang Xiao, Jinlan Fu, See-Kiong Ng +1
In this paper, we ask the research question of whether all the datasets in the benchmark are necessary. We approach this by first characterizing the distinguishability of datasets…
Polyglot Prompt: Multilingual Multitask PrompTraining
Jinlan Fu, See-Kiong Ng, Pengfei Liu
This paper aims for a potential architectural improvement for multilingual learning and asks: Can different tasks from different languages be modeled in a monolithic framework, i.e…
BRIO: Bringing Order to Abstractive Summarization
Yixin Liu, Pengfei Liu, Dragomir Radev +1
Abstractive summarization models are commonly trained using maximum likelihood estimation, which assumes a deterministic (one-point) target distribution in which an ideal model wil…
DataLab: A Platform for Data Analysis and Intervention
Yang Xiao, Jinlan Fu, Weizhe Yuan +5
Despite data's crucial role in machine learning, most existing tools and research tend to focus on systems on top of existing data rather than how to interpret and manipulate data.…
Group Gated Fusion on Attention-based Bidirectional Alignment for Multimodal Emotion Recognition
Pengfei Liu, Kun Li, Helen Meng
Emotion recognition is a challenging and actively-studied research area that plays a critical role in emotion-aware human-computer interaction systems. In a multimodal setting, tem…