5 papers
Can Current Agents Close the Discovery-to-Application Gap? A Case Study in Minecraft
Zhou Ziheng, Huacong Tang, Jinyuan Zhang +9
Discovering causal regularities and applying them to build functional systems--the discovery-to-application loop--is a hallmark of general intelligence, yet evaluating this capacit…
START: Spatial and Textual Learning for Chart Understanding
Zhuoming Liu, Xiaofeng Gao, Feiyang Niu +3
Chart understanding is crucial for deploying multimodal large language models (MLLMs) in real-world scenarios such as analyzing scientific papers and technical reports. Unlike natu…
ProxT2I: Efficient Reward-Guided Text-to-Image Generation via Proximal Diffusion
Zhenghan Fang, Jian Zheng, Qiaozi Gao +2
Diffusion models have emerged as a dominant paradigm for generative modeling across a wide range of domains, including prompt-conditional generation. The vast majority of samplers,…
T2V-Turbo-v2: Enhancing Video Generation Model Post-Training through Data, Reward, and Conditional Guidance Design
Jiachen Li, Qian Long, Jian Zheng +4
In this paper, we focus on enhancing a diffusion-based text-to-video (T2V) model during the post-training phase by distilling a highly capable consistency model from a pretrained T…
TeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in Minecraft
Qian Long, Zhi Li, Ran Gong +3
Collaboration is a cornerstone of society. In the real world, human teammates make use of multi-sensory data to tackle challenging tasks in ever-changing environments. It is essent…