56 citations · 137 across the 31 of their papers we have counts for
5 papers · 1 filter
PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference
Yushu Zhao, Zheng Wang, Minjia Zhang
Mixture-of-Experts (MoE) models have shown strong potential in scaling language models efficiently by activating only a small subset of experts per input. However, their widespread…
VoltanaLLM: Energy-Efficient and SLO-Aware Disaggregated LLM Serving via Adaptive Frequency Control and State-Space Routing
Jiahuan Yu, Aryan Taneja, Junfeng Lin +1
The energy cost of Large Language Model (LLM) inference is rapidly becoming a barrier to sustainable and scalable deployment. Although modern serving architectures expose distinct…
MENTOR: Efficient Multimodal-Conditioned Tuning for Autoregressive Vision Generation Models
Haozhe Zhao, Zefan Cai, Shuzheng Si +5
Recent text-to-image models produce high-quality results but still struggle with precise visual control, balancing multimodal inputs, and requiring extensive training for complex m…
MegaFold: Efficient Training of Next-Generation 3D Attention Protein Models on Cross-Platform GPUs
Hoa La, Ahan Gupta, Alex Morehead +2
Recent advances in biomolecular modeling have been catalyzed by models such as AlphaFold3 (AF3), which introduce science-informed changes to the transformer architecture. Unlike tr…
Supervising the search process produces reliable and generalizable information-seeking agents
Guangzhi Xiong, Qiao Jin, Xiao Wang +9
Large language models (LLMs) are transforming web search by shifting from document ranking to synthesizing answers, and are increasingly deployed as autonomous agentic search syste…