28 citations · 39 across the 6 of their papers we have counts for
6 papers · 1 filter
Lyra: Orchestrating Dual Correction in Automated Theorem Proving
Chuanyang Zheng, Haiming Wang, Enze Xie +6
Large Language Models (LLMs) present an intriguing avenue for exploration in the field of formal theorem proving. Nevertheless, their full potential, particularly concerning the mi…
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Longhui Yu, Weisen Jiang, Han Shi +7
Large language models (LLMs) have pushed the limits of natural language understanding and exhibited excellent problem-solving ability. Despite the great success, most existing open…
Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering
Juan Zha, Zheng Li, Ying Wei +1
Few-Shot Text Classification (FSTC) imitates humans to learn a new text classifier efficiently with only few examples, by leveraging prior knowledge from historical tasks. However,…
Accelerating Attention through Gradient-Based Learned Runtime Pruning
Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh +2
Self-attention is a key enabler of state-of-art accuracy for various transformer-based Natural Language Processing models. This attention mechanism calculates a correlation score f…
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning
Zheng Li, Xin Li, Ying Wei +3
Joint extraction of aspects and sentiments can be effectively formulated as a sequence labeling problem. However, such formulation hinders the effectiveness of supervised methods d…
Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification
Zheng Li, Ying Wei, Yu Zhang +3
Aspect-level sentiment classification (ASC) aims at identifying sentiment polarities towards aspects in a sentence, where the aspect can behave as a general Aspect Category (AC) or…