Search Results for author: Hanbing Liu

Found 11 papers, 6 papers with code

TwT: Thinking without Tokens by Habitual Reasoning Distillation with Multi-Teachers' Guidance

no code implementations31 Mar 2025 Jingxian Xu, Mengyu Zhou, Weichang Liu, Hanbing Liu, Shi Han, Dongmei Zhang

To address this challenge, we propose TwT (Thinking without Tokens), a method that reduces inference-time costs through habitual reasoning distillation with multi-teachers' guidance, while maintaining high performance.

Exploiting Task Relationships for Continual Learning Using Transferability-Aware Task Embeddings

no code implementations17 Feb 2025 Yanru Wu, Xiangyu Chen, Jianning Wang, Enming Zhang, Hanbing Liu, Yang Li

Continual learning (CL) has been an essential topic in the contemporary application of deep neural networks, where catastrophic forgetting (CF) can impede a model's ability to acquire knowledge progressively.

Continual Learning Permuted-MNIST

TableMaster: A Recipe to Advance Table Understanding with Language Models

no code implementations31 Jan 2025 Lang Cao, Hanbing Liu

While current language models (LMs) excel at many text-based tasks, they still face challenges in table understanding due to the complex characteristics of tabular data, such as their structured nature.

CodeS: Towards Building Open-source Language Models for Text-to-SQL

1 code implementation26 Feb 2024 Haoyang Li, Jing Zhang, Hanbing Liu, Ju Fan, Xiaokang Zhang, Jun Zhu, Renjie Wei, Hongyan Pan, Cuiping Li, Hong Chen

To address the limitations, we introduce CodeS, a series of pre-trained language models with parameters ranging from 1B to 15B, specifically designed for the text-to-SQL task.

Data Augmentation Diagnostic +3

Enhancing Continuous Domain Adaptation with Multi-Path Transfer Curriculum

no code implementations26 Feb 2024 Hanbing Liu, Jingge Wang, Xuan Zhang, Ye Guo, Yang Li

Specifically, we construct a transfer curriculum over the source and intermediate domains based on Wasserstein distance, motivated by theoretical analysis of CDA.

Capacity Estimation Domain Adaptation +3

ChatPipe: Orchestrating Data Preparation Program by Optimizing Human-ChatGPT Interactions

no code implementations7 Apr 2023 Sibei Chen, Hanbing Liu, Weiting Jin, Xiangyu Sun, Xiaoyao Feng, Ju Fan, Xiaoyong Du, Nan Tang

Orchestrating a high-quality data preparation program is essential for successful machine learning (ML), but it is known to be time and effort consuming.

Cannot find the paper you are looking for? You can Submit a new open access paper.