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20242026
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cs.AR2026

WaferTrans: Enabling IOMMU-free Distributed Virtual Address Translation for Wafer-scale GPUs

Xinru Tang, Jingxiang Hou, Guanghong Wu +2

Wafer-scale GPUs (WSGs) provide sufficient on-wafer bandwidth to make near-lossless Unified Memory feasible. However, existing designs still rely on a CPU-IOMMU to translate remote…

cs.AR2026

MOCAP: Wafer-Scale-Chip-Oriented Memory-Orchestrated Chunked Pipelining Framework for Prefill-Only LLM Inference

Zichuan Wang, Huizheng Wang, Yuheng Xiao +6

Large language models (LLMs) are increasingly used in prefill-only workloads, where end-to-end latency is dominated by the prefill phase. For long-context prefill, communication ov…

cs.LG2026

FlexLAM: Resolving the Bottleneck Trade-off in Latent Action Learning

Takanori Yoshimoto, Yang Hu, Naruya Kondo +1

Latent actions provide a compact interface between action-free video and downstream decision-making, yet existing Latent Action Models (LAMs) force every transition through a fixed…

cs.AI2026

Beyond Similarity: Trustworthy Memory Search for Personal AI Agents

Jiawen Zhang, Kejia Chen, Jiachen Ma +7

Personal AI agents increasingly rely on long-term memory to provide persistent personalization across sessions. However, existing memory pipelines are largely driven by semantic si…

cs.AR2026

PADE: A Predictor-Free Sparse Attention Accelerator via Unified Execution and Stage Fusion

Huizheng Wang, Hongbin Wang, Zichuan Wang +5

Attention-based models have revolutionized AI, but the quadratic cost of self-attention incurs severe computational and memory overhead. Sparse attention methods alleviate this by…