3 citations · 6 across the 6 of their papers we have counts for
6 papers
Game-Theoretic Lens on LLM-based Multi-Agent Systems
Jianing Hao, Han Ding, Yuanjian Xu +5
Large language models (LLMs) have demonstrated strong reasoning, planning, and communication abilities, enabling them to operate as autonomous agents in open environments. While si…
Interpolative Decoding: Exploring the Spectrum of Personality Traits in LLMs
Eric Yeh, John Cadigan, Ran Chen +3
Recent research has explored using very large language models (LLMs) as proxies for humans in tasks such as simulation, surveys, and studies. While LLMs do not possess a human psyc…
Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey
Rui Shao, Wei Li, Lingsen Zhang +4
Robotic manipulation, a key frontier in robotics and embodied AI, requires precise motor control and multimodal understanding, yet traditional rule-based methods fail to scale or g…
GHPO: Adaptive Guidance for Stable and Efficient LLM Reinforcement Learning
Ziru Liu, Cheng Gong, Xinyu Fu +7
Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as a powerful paradigm for facilitating the self-improvement of large language models (LLMs), particularl…
SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning
Peixian Ma, Xialie Zhuang, Chengjin Xu +3
Natural Language to SQL (NL2SQL) enables intuitive interactions with databases by transforming natural language queries into structured SQL statements. Despite recent advancements…
LLM4DESIGN: An Automated Multi-Modal System for Architectural and Environmental Design
Ran Chen, Xueqi Yao, Xuhui Jiang
This study introduces LLM4DESIGN, a highly automated system for generating architectural and environmental design proposals. LLM4DESIGN, relying solely on site conditions and desig…