9 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…
Chinese Metaphor Recognition Using a Multi-stage Prompting Large Language Model
Jie Wang, Jin Wang, Xuejie Zhang
Metaphors are common in everyday language, and the identification and understanding of metaphors are facilitated by models to achieve a better understanding of the text. Metaphors…
Zero-Shot Cross-Domain Dialogue State Tracking via Dual Low-Rank Adaptation
Xiang Luo, Zhiwen Tang, Jin Wang +1
Zero-shot dialogue state tracking (DST) seeks to enable dialogue systems to transition to unfamiliar domains without manual annotation or extensive retraining. Prior research has a…
Instruction Tuning with Retrieval-based Examples Ranking for Aspect-based Sentiment Analysis
Guangmin Zheng, Jin Wang, Liang-Chih Yu +1
Aspect-based sentiment analysis (ABSA) identifies sentiment information related to specific aspects and provides deeper market insights to businesses and organizations. With the em…