Author

Y. Lin

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#artificial intelligence Preprint Oct 2026

SpecFold: Folding Multi-Branch Redundancy for Faster Speculative Decoding in Diffusion Language Models

Diffusion large language models (DLLMs) generate text through iterative block denoising, and multi-branch speculative decoding accelerates this process by verifying a main branch together with multiple draft branches in a single forward pass. While prior DLLM acceleration methods primarily exploit temporal redundancy a...

Chung-En Ho, Wei-Yu Sun, Cheng-Jhih Shih et al. · 0 citations

Preprint Sep 2026

Hardware Acceleration of Block-Diffusion LLM for Edge Devices

The authors co-design WIFiV-LPDDR, a wide-I/O LPDDR system for precision-tagged reads, BRQ-KV for a canonical low-rank-plus-INT8-residual prefix with query-dependent per-entry precision, and DAT-FFN for drift-mapped canonical replacement, adjacent-stage-corrected low-bit delta, or cached-state carry while keeping live...

Wei-Hsing Huang, Kiseok Lee, Ming-Yen Lee et al. · 0 citations

Open access Jul 2025

A3D-MoE: Acceleration of Large Language Models With Mixture of Experts via 3-D Heterogeneous Integration

A3D-MoE addresses large language models' challenges with 3-D heterogeneous integration to improve memory bandwidth and reduce NoC overhead/energy, and a hardware resource-aware operation fusion scheduler that fuses attention/MoE operations to boost performance.

Wei-Hsing Huang, Janak Sharda, Cheng-Jhih Shih et al. · IEEE Journal on Exploratory... · 3 citations