7 papers
Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion Transformers
Yuxi Liu, Yipeng Hu, Zekun Zhang +2
While Diffusion Transformers (DiTs) have achieved notable progress in video generation, this long-sequence generation task remains constrained by the quadratic complexity inherent…
LISA: Linear-Indexed Sparse Attention for Efficient Long-Context Reasoning
Yu Zhao, Zekun Zhang, Fan Jiang +6
Recent advances in long chain-of-thought reasoning models such as DeepSeek-R1 have led to increasingly longer inference context lengths under the test-time scaling paradigm. Howeve…
OMG-Agent: Toward Robust Missing Modality Generation with Decoupled Coarse-to-Fine Agentic Workflows
Ruiting Dai, Zheyu Wang, Haoyu Yang +6
Data incompleteness severely impedes the reliability of multimodal systems. Existing reconstruction methods face distinct bottlenecks: conventional parametric/generative models are…
Preference-Aware Memory Update for Long-Term LLM Agents
Haoran Sun, Zekun Zhang, Shaoning Zeng
One of the key factors influencing the reasoning capabilities of LLM-based agents is their ability to leverage long-term memory. Integrating long-term memory mechanisms allows agen…
An Uncertainty-Driven Adaptive Self-Alignment Framework for Large Language Models
Haoran Sun, Zekun Zhang, Shaoning Zeng
Large Language Models (LLMs) have demonstrated remarkable progress in instruction following and general-purpose reasoning. However, achieving high-quality alignment with human inte…
A Novel Self-Evolution Framework for Large Language Models
Haoran Sun, Zekun Zhang, Shaoning Zeng
The capabilities of Large Language Models (LLMs) are limited to some extent by pre-training, so some researchers optimize LLMs through post-training. Existing post-training strateg…