1 citations · 1 across the 8 of their papers we have counts for
8 papers
Self-Evolving World Models for LLM Agent Planning
Xuan Zhang, Wenxuan Zhang, See-Kiong Ng +1
World models offer a principled way to equip long-horizon LLM agents with foresight: predictions of action consequences before execution. However, unreliable foresight can be ignor…
IntentionNav: A Benchmark for Intent-Driven Object Navigation from Implicit Human Instruction
Lin Qian, Shijie Li, Sihao Lin +4
Existing object navigation benchmarks usually tell an embodied agent which object category to find, such as microwave or chair. Human-facing embodied AI is often asked something le…
AI for Auto-Research: Roadmap & User Guide
Lingdong Kong, Xian Sun, Wei Chow +17
AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents can execute experiments, draf…
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond
Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47
As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a central bottleneck. Agents that ma…
Multilingual Agent-Based World Modeling for Social Science
Xuan Zhang, Wenxuan Zhang, Anxu Wang +2
Multi-agent role-playing has recently shown promise for studying social behavior with language agents, but existing simulations are mostly monolingual without cross-lingual interac…
3D-TAFS: A Training-free Framework for 3D Affordance Segmentation
Meng Chu, Xuan Zhang, Zhedong Zheng +1
Translating high-level linguistic instructions into precise robotic actions in the physical world remains challenging, particularly when considering the feasibility of interacting…
Ask-before-Plan: Proactive Language Agents for Real-World Planning
Xuan Zhang, Yang Deng, Zifeng Ren +2
The evolution of large language models (LLMs) has enhanced the planning capabilities of language agents in diverse real-world scenarios. Despite these advancements, the potential o…
On the Multi-turn Instruction Following for Conversational Web Agents
Yang Deng, Xuan Zhang, Wenxuan Zhang +3
Web agents powered by Large Language Models (LLMs) have demonstrated remarkable abilities in planning and executing multi-step interactions within complex web-based environments, f…