5 accepted papers
Embedding invisible and temporally consistent watermarks into dynamic 4D Gaussian Splatting (4DGS) models poses unique challenges due to continuous spatio-temporal deformation of Gaussians and diverse motion dynamics. Existing 3DGS watermarking methods, which directly fine-tune parameters within Gau
Can language models (LMs) self-refine their own responses? This question is increasingly relevant as more than 10% of real-world user interactions involve refinement requests (see Appendix G). Yet prior studies have largely tested LMs on verifiable tasks such as competition math or symbolic reasonin…
Text-to-motion generation has significant potential in a wide range of applications including animation, robotics, and AR/VR. While recent works on masked motion models are promising, the task remains challenging due to the inherent ambiguity in text and the complexity of human motion dynamics. To o…
Vision-and-Language Models (VLMs) have shown impressive capabilities on single-turn benchmarks, yet real-world applications often demand more intricate multi-turn dialogues. Existing multi-turn datasets (e.g, MMDU, ConvBench) only partially capture the breadth and depth of conversational scenarios e…
Mathematical question answering over long-form documents is challenging across domains like finance or Wikipedia due to the abundance of candidate arguments within evidence, which complicates recognizing proper arguments for mathematical reasoning and poses hard to learning. In this paper, we propos…