4 citations · 4 across the 9 of their papers we have counts for
9 papers
CalibForge: Adversarial Solver Calibration for Scaling Learnable Terminal Tasks
Fanzhe Meng, Guoxin Chen, Jiale Zhao +7
Training terminal agents requires executable and verifiable tasks that are not merely solvable, but appropriately challenging for learning. Executable validation establishes feasib…
Unified Synthesis of Compositional Speech and Sound from Free-Form Text Prompts
Yuyue Wang, Xihua Wang, Xin Cheng +2
Audio generation has made significant progress, yet synthesizing unified audio where speech and sounds are naturally composited remains a challenge. Current methods either rely on…
AgenticVBench: Can AI Agents Complete Real-World Post-Production Tasks?
Zongheng Cao, Yi Zheng, Rui Song +1
Video production workflows offer a rich and demanding arena for evaluating multimodal AI agents: they require composite capabilities across text, image, audio, and video understand…
What-If World: A Causal Benchmark for General World Models in Embodied Scenarios
Kunlin Cai, Rui Song, Jinghuai Zhang +7
Video generation models are increasingly used as world simulators for tasks like driving and robotic manipulation. What matters in these settings is not whether a single video look…
Toward Autonomous Long-Horizon Engineering for ML Research
Guoxin Chen, Jie Chen, Lei Chen +7
Agentic systems increasingly automate pieces of AI research. Yet turning underspecified research objectives into runnable, experimentally validated ML systems remains a central bot…
IterResearch: Rethinking Long-Horizon Agents with Interaction Scaling
Guoxin Chen, Zile Qiao, Xuanzhong Chen +13
Recent advances in deep-research agents have shown promise for autonomous knowledge construction through dynamic reasoning over external sources. However, existing approaches rely…
ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization
Guoxin Chen, Jing Wu, Xinjie Chen +6
Autoformalization, which translates natural language mathematics into machine-verifiable formal statements, is critical for using formal mathematical reasoning to solve math proble…
MARS: Co-evolving Dual-System Deep Research via Multi-Agent Reinforcement Learning
Guoxin Chen, Zile Qiao, Wenqing Wang +10
Large Reasoning Models (LRMs) face two fundamental limitations: excessive token consumption when overanalyzing simple information processing tasks, and inability to access up-to-da…
What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction Tuning
Yifan Du, Hangyu Guo, Kun Zhou +6
Visual instruction tuning is crucial for enhancing the zero-shot generalization capability of Multi-modal Large Language Models (MLLMs). In this paper, we aim to investigate a fund…