20 citations · 40 across the 14 of their papers we have counts for
18 papers
DuoCook: An Overcooked-Inspired Benchmark for Visual Planning and Coordination
Ziyi Jiao, Heng Zhang, Drishti Regmi +3
Coordinating two players in a cooking task requires a vision-language agent to track changing scene states, sequence recipe steps, and allocate shared resources under a time budget…
Code4Scene: Benchmarking Coding Agents for Constructing and Editing 3D Scenes
Xiaokang Ye, Siddhant Hitesh Mantri, Zimeng Chen +6
Frontier coding agents can now write and execute code that authors 3D environments, but whether they reliably understand 3D structure and precisely control scene state remains uncl…
Uni-LaDiR: Latent Diffusion Unifies Multimodal Reasoning
Haoqiang Kang, Yizhe Zhang, Nikki Lijing Kuang +3
Multimodal models increasingly think with different modalities such as images, 3D point clouds, and robot states, not just text. Yet each modality is still encoded into its own rep…
SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning
Haoqiang Kang, Xiaokang Ye, Yuhan Liu +5
LLM/VLM-based digital agents have advanced rapidly thanks to scalable sandboxes for coding, web navigation, and computer use, which provide rich interactive training grounds. In co…
LaDi-RL: Latent Diffusion Reasoning Prevents Entropy Collapse in Reinforcement Learning
Haoqiang Kang, Yizhe Zhang, Nikki Lijing Kuang +2
Reinforcement learning has become a central paradigm for improving LLM reasoning, but most existing methods optimize policies over discrete token sequences. This creates a mismatch…
TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models
Fangxu Yu, Xingang Guo, Lingzhi Yuan +6
Time series are ubiquitous in real-world scenarios and crucial for applications ranging from energy management to traffic control. Consequently, the ability to reason over time ser…
PrivacyReasoner: Can LLM Emulate a Human-like Privacy Mind?
Yiwen Tu, Xuan Liu, Lianhui Qin +1
Prior work on LLM-based privacy focuses on norm judgment over synthetic vignettes, rather than how people think about a specific data practice and formulate their opinions. We addr…
Small Drafts, Big Verdict: Information-Intensive Visual Reasoning via Speculation
Yuhan Liu, Lianhui Qin, Shengjie Wang
Large Vision-Language Models (VLMs) have achieved remarkable progress in multimodal understanding, yet they struggle when reasoning over information-intensive images that densely i…
LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning
Haoqiang Kang, Yizhe Zhang, Nikki Lijing Kuang +4
Large Language Models (LLMs) demonstrate their reasoning ability through chain-of-thought (CoT) generation. However, LLM's autoregressive decoding may limit the ability to revisit…
KVFlow: Efficient Prefix Caching for Accelerating LLM-Based Multi-Agent Workflows
Zaifeng Pan, Ajjkumar Patel, Zhengding Hu +6
Large language model (LLM) based agentic workflows have become a popular paradigm for coordinating multiple specialized agents to solve complex tasks. To improve serving efficiency…
Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning
Isadora White, Kolby Nottingham, Ayush Maniar +5
Collaboration is ubiquitous and essential in day-to-day life -- from exchanging ideas, to delegating tasks, to generating plans together. This work studies how LLMs can adaptively…
ControlAgent: Automating Control System Design via Novel Integration of LLM Agents and Domain Expertise
Xingang Guo, Darioush Keivan, Usman Syed +5
Control system design is a crucial aspect of modern engineering with far-reaching applications across diverse sectors including aerospace, automotive systems, power grids, and robo…
Benchmarking the Capabilities of Large Language Models in Transportation System Engineering: Accuracy, Consistency, and Reasoning Behaviors
Usman Syed, Ethan Light, Xingang Guo +4
In this paper, we explore the capabilities of state-of-the-art large language models (LLMs) such as GPT-4, GPT-4o, Claude 3.5 Sonnet, Claude 3 Opus, Gemini 1.5 Pro, Llama 3, and Ll…
Flow of Reasoning: Training LLMs for Divergent Reasoning with Minimal Examples
Fangxu Yu, Lai Jiang, Haoqiang Kang +2
The ability to generate diverse solutions to a given problem is a hallmark of human creativity. This divergent reasoning is also crucial for machines, enhancing their robustness an…
Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra
Darioush Kevian, Usman Syed, Xingang Guo +5
In this paper, we explore the capabilities of state-of-the-art large language models (LLMs) such as GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra in solving undergraduate-level contro…
EduAgent: Generative Student Agents in Learning
Songlin Xu, Xinyu Zhang, Lianhui Qin
Student simulation in online education is important to address dynamic learning behaviors of students with diverse backgrounds. Existing simulation models based on deep learning us…
LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction
Hejie Cui, Zhuocheng Shen, Jieyu Zhang +4
Electronic health records (EHRs) contain valuable patient data for health-related prediction tasks, such as disease prediction. Traditional approaches rely on supervised learning m…
COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability
Xingang Guo, Fangxu Yu, Huan Zhang +2
Jailbreaks on large language models (LLMs) have recently received increasing attention. For a comprehensive assessment of LLM safety, it is essential to consider jailbreaks with di…