5 citations · 14 across the 15 of their papers we have counts for
15 papers
Limitations of Synthetic Data Generation in Specialized Data-Scarce Domains
Edward Zhang, Marcel Hussing, Tanay Tandon +12
Advances in diffusion-based generative models have motivated the use of synthetic image generation to alleviate data scarcity in vision tasks. While this strategy has shown promise…
PersonaMem-v3: Toward Omni-Platform Personal Intelligence for Holistic User Understanding, Recommendation, and Agentic Tasks
Bowen Jiang, Yuan Yuan, Zhuoqun Hao +12
Personal intelligence is becoming a central frontier for user-facing AI agents. To be helpful in everyday life, agents must understand users across the digital contexts where their…
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…
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…
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…
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…
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…
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…
ControlText: Unlocking Controllable Fonts in Multilingual Text Rendering without Font Annotations
Bowen Jiang, Yuan Yuan, Xinyi Bai +6
This work demonstrates that diffusion models can achieve font-controllable multilingual text rendering using just raw images without font label annotations.Visual text rendering re…
A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners
Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao +5
This study introduces a hypothesis-testing framework to assess whether large language models (LLMs) possess genuine reasoning abilities or primarily depend on token bias. We go bey…
Towards Rationality in Language and Multimodal Agents: A Survey
Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang +6
This work discusses how to build more rational language and multimodal agents and what criteria define rationality in intelligent systems. Rationality is the quality of being guide…
Multi-Agent VQA: Exploring Multi-Agent Foundation Models in Zero-Shot Visual Question Answering
Bowen Jiang, Zhijun Zhuang, Shreyas S. Shivakumar +2
This work explores the zero-shot capabilities of foundation models in Visual Question Answering (VQA) tasks. We propose an adaptive multi-agent system, named Multi-Agent VQA, to ov…
WildfireGPT: Tailored Large Language Model for Wildfire Analysis
Yangxinyu Xie, Bowen Jiang, Tanwi Mallick +10
Recent advancement of large language models (LLMs) represents a transformational capability at the frontier of artificial intelligence. However, LLMs are generalized models, traine…
Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge
Bowen Jiang, Zhijun Zhuang, Shreyas S. Shivakumar +1
This work introduces an enhanced approach to generating scene graphs by incorporating both a relationship hierarchy and commonsense knowledge. Specifically, we begin by proposing a…
Instance-Agnostic Geometry and Contact Dynamics Learning
Mengti Sun, Bowen Jiang, Bibit Bianchini +2
This work presents an instance-agnostic learning framework that fuses vision with dynamics to simultaneously learn shape, pose trajectories, and physical properties via the use of…