10 citations · 27 across the 10 of their papers we have counts for
10 papers
OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
Zhiyong Wu, Chengcheng Han, Zichen Ding +5
Autonomous interaction with the computer has been a longstanding challenge with great potential, and the recent proliferation of large language models (LLMs) has markedly accelerat…
DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models
Chengcheng Han, Xiaowei Du, Che Zhang +4
Chain-of-Thought (CoT) prompting has proven to be effective in enhancing the reasoning capabilities of Large Language Models (LLMs) with at least 100 billion parameters. However, i…
Exchanging-based Multimodal Fusion with Transformer
Renyu Zhu, Chengcheng Han, Yong Qian +5
We study the problem of multimodal fusion in this paper. Recent exchanging-based methods have been proposed for vision-vision fusion, which aim to exchange embeddings learned from…
When Gradient Descent Meets Derivative-Free Optimization: A Match Made in Black-Box Scenario
Chengcheng Han, Liqing Cui, Renyu Zhu +5
Large pre-trained language models (PLMs) have garnered significant attention for their versatility and potential for solving a wide spectrum of natural language processing (NLP) ta…
Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives
Qiushi Sun, Chengcheng Han, Nuo Chen +4
Large language models (LLMs) have shown increasing power on various natural language processing (NLP) tasks. However, tuning these models for downstream tasks usually needs exorbit…
Meta-Learning Siamese Network for Few-Shot Text Classification
Chengcheng Han, Yuhe Wang, Yingnan Fu +4
Few-shot learning has been used to tackle the problem of label scarcity in text classification, of which meta-learning based methods have shown to be effective, such as the prototy…
Meta-Learning Triplet Network with Adaptive Margins for Few-Shot Named Entity Recognition
Chengcheng Han, Renyu Zhu, Jun Kuang +5
Meta-learning methods have been widely used in few-shot named entity recognition (NER), especially prototype-based methods. However, the Other(O) class is difficult to be represent…
SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognition
Jianing Wang, Chengcheng Han, Chengyu Wang +5
Few-shot Named Entity Recognition (NER) aims to identify named entities with very little annotated data. Previous methods solve this problem based on token-wise classification, whi…
Programming Knowledge Tracing: A Comprehensive Dataset and A New Model
Renyu Zhu, Dongxiang Zhang, Chengcheng Han +4
In this paper, we study knowledge tracing in the domain of programming education and make two important contributions. First, we harvest and publish so far the most comprehensive d…
Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification
ChengCheng Han, Zeqiu Fan, Dongxiang Zhang +3
Meta-learning has emerged as a trending technique to tackle few-shot text classification and achieved state-of-the-art performance. However, existing solutions heavily rely on the…