11 citations · 21 across the 13 of their papers we have counts for
13 papers
AdaR: A Framework for Equipping LLMs with Adaptive Reasoning
Zhejian Lai, Xiang Geng, Zhijun Wang +7
Mathematical reasoning is a primary indicator of large language models (LLMs) intelligence. However, existing LLMs exhibit failures in robustness and generalization. This paper att…
Alleviating Distribution Shift in Synthetic Data for Machine Translation Quality Estimation
Xiang Geng, Zhejian Lai, Jiajun Chen +2
Quality Estimation (QE) models evaluate the quality of machine translations without reference translations, serving as the reward models for the translation task. Due to the data s…
"I've Heard of You!": Generate Spoken Named Entity Recognition Data for Unseen Entities
Jiawei Yu, Xiang Geng, Yuang Li +8
Spoken named entity recognition (NER) aims to identify named entities from speech, playing an important role in speech processing. New named entities appear every day, however, ann…
Why Not Transform Chat Large Language Models to Non-English?
Xiang Geng, Ming Zhu, Jiahuan Li +14
The scarcity of non-English data limits the development of non-English large language models (LLMs). Transforming English-centric LLMs to non-English has been identified as an effe…
From Handcrafted Features to LLMs: A Brief Survey for Machine Translation Quality Estimation
Haofei Zhao, Yilun Liu, Shimin Tao +6
Machine Translation Quality Estimation (MTQE) is the task of estimating the quality of machine-translated text in real time without the need for reference translations, which is of…
MAPO: Advancing Multilingual Reasoning through Multilingual Alignment-as-Preference Optimization
Shuaijie She, Wei Zou, Shujian Huang +4
Though reasoning abilities are considered language-agnostic, existing LLMs exhibit inconsistent reasoning abilities across different languages, e.g., reasoning in the dominant lang…
Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine Translation
Xu Huang, Zhirui Zhang, Xiang Geng +3
This study investigates how Large Language Models (LLMs) leverage source and reference data in machine translation evaluation task, aiming to better understand the mechanisms behin…
Unify word-level and span-level tasks: NJUNLP's Participation for the WMT2023 Quality Estimation Shared Task
Xiang Geng, Zhejian Lai, Yu Zhang +4
We introduce the submissions of the NJUNLP team to the WMT 2023 Quality Estimation (QE) shared task. Our team submitted predictions for the English-German language pair on all two…
CoP: Factual Inconsistency Detection by Controlling the Preference
Shuaijie She, Xiang Geng, Shujian Huang +1
Abstractive summarization is the process of generating a summary given a document as input. Although significant progress has been made, the factual inconsistency between the docum…
DirectQE: Direct Pretraining for Machine Translation Quality Estimation
Qu Cui, Shujian Huang, Jiahuan Li +4
Machine Translation Quality Estimation (QE) is a task of predicting the quality of machine translations without relying on any reference. Recently, the predictor-estimator framewor…
Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm
Bin Gu, Guodong Liu, Yanfu Zhang +2
Modern machine learning algorithms usually involve tuning multiple (from one to thousands) hyperparameters which play a pivotal role in terms of model generalizability. Black-box o…
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization
Wanli Shi, Bin Gu, Xiang Li +2
Semi-supervised learning is pervasive in real-world applications, where only a few labeled data are available and large amounts of instances remain unlabeled. Since AUC is an impor…
Scalable Semi-Supervised SVM via Triply Stochastic Gradients
Xiang Geng, Bin Gu, Xiang Li +3
Semi-supervised learning (SSL) plays an increasingly important role in the big data era because a large number of unlabeled samples can be used effectively to improve the performan…