most citedA RAG-Based Multi-Agent LLM System for Natural Hazard Resilience and Adaptation

1 citations · 1 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2026

One Model, All Roles: Multi-Turn, Multi-Agent Self-Play Reinforcement Learning for Conversational Social Intelligence

Bowen Jiang, Taiwei Shi, Ryo Kamoi +5

This paper introduces OMAR: One Model, All Roles, a reinforcement learning framework that enables AI to develop social intelligence through multi-turn, multi-agent conversational s…

cs.CL2025

PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory

Bowen Jiang, Yuan Yuan, Maohao Shen +13

Personalization is one of the next milestones in advancing AI capability and alignment. We introduce PersonaMem-v2, the state-of-the-art dataset for LLM personalization that simula…

cs.CL2025

GeoGrid-Bench: Can Foundation Models Understand Multimodal Gridded Geo-Spatial Data?

Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang +6

We present GeoGrid-Bench, a benchmark designed to evaluate the ability of foundation models to understand geo-spatial data in the grid structure. Geo-spatial datasets pose distinct…

cs.RO2025

Vysics: Object Reconstruction Under Occlusion by Fusing Vision and Contact-Rich Physics

Bibit Bianchini, Minghan Zhu, Mengti Sun +3

We introduce Vysics, a vision-and-physics framework for a robot to build an expressive geometry and dynamics model of a single rigid body, using a seconds-long RGBD video and the r…

cs.CL20251 cited

A RAG-Based Multi-Agent LLM System for Natural Hazard Resilience and Adaptation

Yangxinyu Xie, Bowen Jiang, Tanwi Mallick +10

Large language models (LLMs) are a transformational capability at the frontier of artificial intelligence and machine learning that can support decision-makers in addressing pressi…

cs.CL2025

Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scale

Bowen Jiang, Zhuoqun Hao, Young-Min Cho +6

Large Language Models (LLMs) have emerged as personalized assistants for users across a wide range of tasks -- from offering writing support to delivering tailored recommendations…