6 papers
Sink-Sparse Hybrid Attention for Efficient Inference in T2I/T2V Diffusion Transformers
Bingxin Xing, Yu Zhang, Jiatong Ding +2
Diffusion Transformers (DiTs) have become a common backbone for high-quality text-to-image and text-to-video generation, but repeated dense self-attention remains a major inference…
HyQuant: Hybrid-Precision Quantization for LLM Attention
Jiatong Ding, Bingxin Xing, Yu Zhang +9
Quantization has been widely adopted in LLM training and inference to reduce cost and improve efficiency. However, low-bit quantization of the \emph{attention} module often introdu…
Fragmenting Diffusion Pathways Confers Extraordinary Radiation Resistance in Refractory Multicomponent Alloys
Bin Xing, Bijun Xie, Wanjuan Zou +11
The accumulation and growth of vacancy clusters under irradiation is a pivotal degradation mode for structural materials in extreme environments. Even tungsten undergoes rapid defe…
Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought
Tencent Hunyuan Team, Ao Liu, Botong Zhou +248
As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…
Divergent Evolution of Slip Banding in Alloys
Bijun Xie, Hangman Chen, Pengfei Wang +8
Metallic materials under high stress often exhibit deformation localization, manifesting as slip banding. Over seven decades ago, Frank and Read introduced the well-known model of…
Atomic-scale tunable phonon transport at tailored grain boundaries and Their Impact on Thermal Conductivity
Xiaowang Wang, Chaitanya A. Gadre, Wanjuan Zou +16
Grain boundaries (GBs) strongly influence thermal transport in crystalline solids by disrupting lattice periodicity and scattering phonons. Due to the atomic-level disorder and str…