Cheng Qian
@qiancheng1231
UIUC PhD @uiuc_nlp advised by @hengjinlp | Prev THU Undergrad @TsinghuaNLP advised by @zibuyu9 | Current intern @salesforce | #LLM #Agent
📢 New Paper Drop: From Solving to Modeling! LLMs can solve math problems — but can they model the real world? 🌍 📄 arXiv: arxiv.org/pdf/2505.15068 💻 Code: github.com/qiancheng0/Mod… Introducing ModelingAgent, a breakthrough system for real-world mathematical modeling with LLMs.
Won't be at ACL in person this time, but come and chat with Emre about our new paper on mitigation of tool overuse!
I'll be @aclmeeting in Vienna to present our recent agent papers SMART and CoALM! 🇦🇹🤖 #acl2025 Feel free to stop by our posters to exchange ideas and discuss agents together!
I'll be @aclmeeting in Vienna to present our recent agent papers SMART and CoALM! 🇦🇹🤖 #acl2025 Feel free to stop by our posters to exchange ideas and discuss agents together!
Write a blog to share my recent thoughts about knowledge boundaries & tool use & language agent. This is the first time to propose three laws of knowledge boundaries!🔥 candle-walker-56d.notion.site/NAACL-2025-Ora… Chinese Version: mp.weixin.qq.com/s/XzjiLUFAr1Yc…
🧠 How can AI evolve from statically 𝘵𝘩𝘪𝘯𝘬𝘪𝘯𝘨 𝘢𝘣𝘰𝘶𝘵 𝘪𝘮𝘢𝘨𝘦𝘴 → dynamically 𝘵𝘩𝘪𝘯𝘬𝘪𝘯𝘨 𝘸𝘪𝘵𝘩 𝘪𝘮𝘢𝘨𝘦𝘴 as cognitive workspaces, similar to the human mental sketchpad? 🔍 What’s the 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗿𝗼𝗮𝗱𝗺𝗮𝗽 from tool-use → programmatic…
🧠Let’s teach LLMs to learn smarter, not harder💥[arxiv.org/pdf/2506.06972] 🤖How can LLMs verify complex scientific information efficiently? 🚀We propose modular, reusable atomic reasoning skills that reduce LLMs’ cognitive load to verify scientific claims with little data.…
Excited to share that EmbodiedBench was selected for an Oral at ICML 2025! We recently added results for new models (InternVL3, Gemma3, Ovis2) and released a large agent trajectory dataset on 🤗: embodiedbench.github.io Try training and evaluating your MLLM for embodied agents!
🤖Can MLLM agents reason about spatial relationships and plan atomic actions for navigation & manipulation? 🔥 Meet EmbodiedBench 🏆—the first fine-grained benchmark for MLLM-based embodied agents! 📄 Paper: arxiv.org/abs/2502.09560 🌐 Website & code: embodiedbench.github.io
What is key of agent decision making? Is there a decision making boundary? I am always thinking of the potential boundary of correct decision making and the uncertainty of this boundary. The alignment of decision making boundary and tool-use boundary led by @WangCarrey…
What’s is the agent? What is the optimal behavior to achieve the predefined goal? And how to learn that behavior policy? We formally introduce a systematic Theory of Agent (ToA), analogous to the cognitive framework of Theory of Mind (ToM). Where ToM refers to the ability to…
Can LLMs make rational decisions like human experts? 📖Introducing DecisionFlow: Advancing Large Language Model as Principled Decision Maker We introduce a novel framework that constructs a semantically grounded decision space to evaluate trade-offs in hard decision-making…
Theory of Agent: From reasoning and tool use, we are defining agent from a knowledge and behavior driven perspective. Welcome to check our newest release!! arxiv.org/pdf/2506.00886
What’s is the agent? What is the optimal behavior to achieve the predefined goal? And how to learn that behavior policy? We formally introduce a systematic Theory of Agent (ToA), analogous to the cognitive framework of Theory of Mind (ToM). Where ToM refers to the ability to…
What’s is the agent? What is the optimal behavior to achieve the predefined goal? And how to learn that behavior policy? We formally introduce a systematic Theory of Agent (ToA), analogous to the cognitive framework of Theory of Mind (ToM). Where ToM refers to the ability to…
(1/5) Want to make your LLM a skilled persuader? Check out our latest paper: "ToMAP: Training Opponent-Aware LLM Persuaders with Theory of Mind"! For details: 📄Arxiv: arxiv.org/pdf/2505.22961 🛠️GitHub: github.com/ulab-uiuc/ToMAP
Mathematical modeling is a key way for our humans to understand how the world runs. If you truly believe in your agent, you should test them on our new benchmark!
📢 New Paper Drop: From Solving to Modeling! LLMs can solve math problems — but can they model the real world? 🌍 📄 arXiv: arxiv.org/pdf/2505.15068 💻 Code: github.com/qiancheng0/Mod… Introducing ModelingAgent, a breakthrough system for real-world mathematical modeling with LLMs.
While building Agents for Enterprise applications, one thing is very important: not to overuse tool-calling with LLMs - that makes your AI agent very expensive. In our new ACL paper, we show a method to mitigate over-use of tools using a SMART way. Read more from post below 👇
📣 SMARTAgent is accepted to ACL 2025 Findings! It’s increasingly important to form an agent’s metacognition, which we believe should guide its action and reasoning. We are continuing on this way!! Position paper will be released soon!
📣 EscapeBench is accepted to ACL 2025 Main! Creativity is what many current agent works neglect, but will be extremely important for agent to reach human level intelligence and be applied to solve real world challenges. Another paper continuing this work is also on the way!
💡Want to know your language model's CREATIVITY? Check our newest paper here! 📖EscapeBench: Pushing Language Models to Think Outside the Box 🌐arxiv.org/pdf/2412.13549 📊github.com/qiancheng0/Esc… Challenge your LM to innovatively use tools and escape from conventional thoughts!