activity
20232026
most citedTowards Rationality in Language and Multimodal Agents: A Survey

5 citations · 14 across the 13 of their papers we have counts for

collaborators

13 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.CV2025

Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes

Zhaoyang Wei, Bowen Jiang, Xumeng Han +6

While Multimodal Large Language Models (MLLMs) demonstrate impressive performance in benign scenarios, their cognitive reliability deteriorates significantly in complex scenes unde…

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.CL2025★ 1 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…

cs.CV2025

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…

cs.CL2024★ 2 cited

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…

cs.AI2024★ 5 cited

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…

cs.CV2024★ 1 cited

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…

cs.AI2024★ 4 cited

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…

cs.CV2023★ 1 cited

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…

cs.CV2023

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…