4 citations · 6 across the 4 of their papers we have counts for
7 papers · 1 filter
SAPO: Self-Adaptive Process Optimization Makes Small Reasoners Stronger
Kaiyuan Chen, Guangmin Zheng, Jin Wang +2
Existing self-evolution methods overlook the influence of fine-grained reasoning steps, which leads to the reasoner-verifier gap. The computational inefficiency of Monte Carlo (MC)…
Sample-aware Adaptive Structured Pruning for Large Language Models
Jun Kong, Xinge Ma, Jin Wang +1
Large language models (LLMs) have achieved outstanding performance in natural language processing, but enormous model sizes and high computational costs limit their practical deplo…
Multi-Attribute Multi-Grained Adaptation of Pre-Trained Language Models for Text Understanding from Bayesian Perspective
You Zhang, Jin Wang, Liang-Chih Yu +2
Current neural networks often employ multi-domain-learning or attribute-injecting mechanisms to incorporate non-independent and identically distributed (non-IID) information for te…
SoftMCL: Soft Momentum Contrastive Learning for Fine-grained Sentiment-aware Pre-training
Jin Wang, Liang-Chih Yu, Xuejie Zhang
The pre-training for language models captures general language understanding but fails to distinguish the affective impact of a particular context to a specific word. Recent works…
HPCC-YNU at SemEval-2020 Task 9: A Bilingual Vector Gating Mechanism for Sentiment Analysis of Code-Mixed Text
Jun Kong, Jin Wang, Xuejie Zhang
It is fairly common to use code-mixing on a social media platform to express opinions and emotions in multilingual societies. The purpose of this task is to detect the sentiment of…
YNU-HPCC at SemEval-2020 Task 11: LSTM Network for Detection of Propaganda Techniques in News Articles
Jiaxu Dao, Jin Wang, Xuejie Zhang
This paper summarizes our studies on propaganda detection techniques for news articles in the SemEval-2020 task 11. This task is divided into the SI and TC subtasks. We implemented…