3 citations · 5 across the 10 of their papers we have counts for
10 papers
SynAct: A Reasoning-Acting Large Language Model Agent for Adaptive Synthesis Optimization
Fangzhou Liu, Peiyi Han, Jiawei Liu +5
Logic synthesis transforms RTL designs into gate-level netlists, where PPA results are highly sensitive to the choice of optimization commands, making synthesis tuning both high-di…
Agentic Electronic Design Automation: A Handoff Perspective
Jiawei Liu, Peiyi Han, Yuntao Lu +3
Electronic design automation (EDA) is multi-stage and handoff-heavy, relying on transfers among humans, design artifacts, and multiple tools. LLM-based agents now participate in th…
Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning
Yiming Huang, Zhenbo Shi, Shuzheng Gao +3
Reinforcement Learning with Verifiable Rewards (RLVR) is an essential paradigm that enhances the reasoning capabilities of Large Language Models (LLMs). However, existing methods t…
Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs
Yiming Huang, Zhenbo Shi, Xin-Cheng Wen +4
Unsupervised reinforcement learning (RL) has emerged as a promising paradigm for enabling self-improvement in large language models (LLMs). However, existing unsupervised RL-based…
SPFT-SQL: Enhancing Large Language Model for Text-to-SQL Parsing by Self-Play Fine-Tuning
Yuhao Zhang, Shaoming Duan, Jinhang Su +2
Despite the significant advancements of self-play fine-tuning (SPIN), which can transform a weak large language model (LLM) into a strong one through competitive interactions betwe…
CRED-SQL: Enhancing Real-world Large Scale Database Text-to-SQL Parsing through Cluster Retrieval and Execution Description
Shaoming Duan, Zirui Wang, Chuanyi Liu +5
Recent advances in large language models (LLMs) have significantly improved the accuracy of Text-to-SQL systems. However, a critical challenge remains: the semantic mismatch betwee…
Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities
Yiming Huang, Jiyu Guo, Wenxin Mao +4
Converting natural language (NL) questions into SQL queries, referred to as Text-to-SQL, has emerged as a pivotal technology for facilitating access to relational databases, especi…
TCSR-SQL: Towards Table Content-aware Text-to-SQL with Self-retrieval
Wenbo Xu, Liang Yan, Chuanyi Liu +5
Large Language Model-based (LLM-based) Text-to-SQL methods have achieved important progress in generating SQL queries for real-world applications. When confronted with table conten…
Generative Data Augmentation for Non-IID Problem in Decentralized Clinical Machine Learning
Zirui Wang, Shaoming Duan, Chengyue Wu +4
Swarm learning (SL) is an emerging promising decentralized machine learning paradigm and has achieved high performance in clinical applications. SL solves the problem of a central…
Fed-TDA: Federated Tabular Data Augmentation on Non-IID Data
Shaoming Duan, Chuanyi Liu, Peiyi Han +3
Non-independent and identically distributed (non-IID) data is a key challenge in federated learning (FL), which usually hampers the optimization convergence and the performance of…