most citedHARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection

4 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG20244 cited

HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection

Yuxin Wang, Duanyu Feng, Yongfu Dai +5

Data serves as the fundamental foundation for advancing deep learning, particularly tabular data presented in a structured format, which is highly conducive to modeling. However, e…

cs.CL2024

Dishonesty in Helpful and Harmless Alignment

Youcheng Huang, Jingkun Tang, Duanyu Feng +4

People tell lies when seeking rewards. Large language models (LLMs) are aligned to human values with reinforcement learning where they get rewards if they satisfy human preference.…

cs.CL2024

Towards Understanding the Influence of Reward Margin on Preference Model Performance

Bowen Qin, Duanyu Feng, Xi Yang

Reinforcement Learning from Human Feedback (RLHF) is a widely used framework for the training of language models. However, the process of using RLHF to develop a language model tha…

cs.CL20241 cited

Towards Analyzing and Understanding the Limitations of DPO: A Theoretical Perspective

Duanyu Feng, Bowen Qin, Chen Huang +2

Direct Preference Optimization (DPO), which derives reward signals directly from pairwise preference data, has shown its effectiveness on aligning Large Language Models (LLMs) with…

cs.CL20241 cited

Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English

Xiao Zhang, Ruoyu Xiang, Chenhan Yuan +8

Despite Spanish's pivotal role in the global finance industry, a pronounced gap exists in Spanish financial natural language processing (NLP) and application studies compared to En…

cs.IR20241 cited

DREditor: An Time-efficient Approach for Building a Domain-specific Dense Retrieval Model

Chen Huang, Duanyu Feng, Wenqiang Lei +1

Deploying dense retrieval models efficiently is becoming increasingly important across various industries. This is especially true for enterprise search services, where customizing…