8 citations · 10 across the 21 of their papers we have counts for
10 papers · 1 filter
Risk-minimizing GUE-implementations of truthful reporting in a Dynamic Social Choice Problem
Endre Csóka, Máté Viczián
The Guaranteed Utility Mechanism (GUM) was introduced to implement efficiency in Guaranteed Utility Equilibrium (GUE) in dynamic social choice problems. We show that this mechanism…
DIET: Deletion-response Expert Trimming for Video Diffusion Transformers
Jiachang Zhang, Teng Hu, Bohao Feng +4
Video diffusion transformers (DiTs) increasingly adopt mixture-of-experts (MoE) architectures to reduce active computation, but their full expert storage remains costly. Existing o…
TRACE-Bench: Decomposing and Diagnosing Multi-Reference Image Generation
Haoran Wang, Chaofan Ma, Ran Yi +1
Despite recent advances in unified multimodal models for multi-reference image generation, existing benchmarks remain organized around predefined task types (e.g., "subject composi…
Efficient Audio-Visual Generation via Synchrony-Aware Cross-Modal Sparse Attention
Shengchuan Gao, Teng Hu, Bohao Feng +4
Recent audio-visual generation models can synthesize synchronized video and sound in a unified diffusion process, but their inference cost remains high because long video token seq…
PhysAgent: Reflective Agentic Physics Control for Physically Plausible Video Generation
Qirui Li, Jinkun Hao, Yibo Li +3
Recent advances in physics-grounded video generation leverage physics simulation as a physical prior to guide video synthesis toward physically plausible outcomes. The simulation p…
Cycle-World: Mitigating Error Accumulation in Long-term Video World Models via Reverse-Prediction Cycle Consistency
Zihan Su, Teng Hu, Jiangning Zhang +4
Autoregressive diffusion models have enabled high-quality video generation, yet their sequential nature inherently suffers from error accumulation. In long-horizon video synthesis,…
MetaWorld: Scaling Multi-Agent Video World Model from Single-view Video Data
Teng Hu, Mingchun Lu, Yating Wang +6
Video world models are a foundational generative technology for embodied AI and the Metaverse, yet existing approaches are inherently limited to a single agent observing from a sin…
Advancing Narrative Long Video Generation via Training-Free Identity-Aware Memory
Jinzhuo Liu, Jiangning Zhang, Wencan Jiang +5
Autoregressive video generation has improved rapidly in visual fidelity and interactivity, but it still suffers from long-term inconsistency and memory degradation. Most existing s…
Evolution of Video Generative Foundations
Teng Hu, Jiangning Zhang, Hongrui Huang +7
The rapid advancement of Artificial Intelligence Generated Content (AIGC) has revolutionized video generation, enabling systems ranging from proprietary pioneers like OpenAI's Sora…
UniICL: Systematizing Unified Multimodal In-context Learning through a Capability-Oriented Taxonomy
Yicheng Xu, Jiangning Zhang, Zhucun Xue +5
In-context learning (ICL) enables fast task adaptation from demonstrations without per-task parameter updates but remains highly sensitive to example selection and formatting. In u…