5 papers
ChainSpace: A Chained-Reasoning Paradigm for Spatial Intelligence
Xiaohan Zhang, Feng Gu, Xudong Rao +4
Spatial intelligence requires foundation models to maintain coherent spatial state across interactions with the physical world. However, existing data-centric approaches typically…
Marco DeepResearch: Unlocking Efficient Deep Research Agents via Verification-Centric Design
Bin Zhu, Qianghuai Jia, Tian Lan +6
Deep research agents autonomously conduct open-ended investigations, integrating complex information retrieval with multi-step reasoning across diverse sources to solve real-world…
MindWatcher: Toward Smarter Multimodal Tool-Integrated Reasoning
Jiawei Chen, Xintian Shen, Lihao Zheng +43
Traditional workflow-based agents exhibit limited intelligence when addressing real-world problems requiring tool invocation. Tool-integrated reasoning (TIR) agents capable of auto…
MindGPT-4ov: An Enhanced MLLM via a Multi-Stage Post-Training Paradigm
Wei Chen, Chaoqun Du, Feng Gu +14
We present MindGPT-4ov, a multimodal large language model (MLLM) that introduces a general post-training paradigm spanning data production, model training, and efficient deployment…
Reverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer?
Nishant Balepur, Feng Gu, Abhilasha Ravichander +3
Question answering (QA), giving correct answers to questions, is a popular task, but we test reverse question answering (RQA): for an input answer, give a question with that answer…