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From the 1 of 21 linked papers with an AI index.

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21 papers

cs.CV2026

Hybrid-LUT: Channel-Aware Hybrid Lookup Table and Filtering for Efficient Image Denoising

Zhilin Ai, Boyu Li, Sidi Yang +5

Lookup table (LUT)-based image denoising methods have attracted increasing attention due to their high efficiency and hardware-friendly properties. However, existing RGB-LUT approa…

cs.LG2026

Approximate Speculative Decoding

Yuannuo Feng, Zegang Peng, Yuxin Xie +5

Speculative decoding accelerates autoregressive generation by verifying a draft block with a target model in parallel. Under standard greedy verification, decoding stops at the fir…

cs.LG2026

NANQ: Noise-Floor-Aware Mixed-Precision Non-Uniform Quantization for Analog Compute-in-Memory

Yizhe Chen, Wenshuai Yao, Saiya Wang +6

Analog compute-in-memory (CIM) enables energy-efficient neural network inference, but device variation and read noise can severely degrade low-bit quantized models. Existing CIM-or…

cs.AR2026

Selective KV Cache Protection for Noise-Resilient LLM Inference on Analog Compute-In-Memory Systems

Yuannuo Feng, Wenyong Zhou, Yuang Ma +5

Analog compute-in-memory (CIM) arrays have emerged as a promising substrate for energy-efficient LLM inference, particularly for weight-stationary computations in linear layers. Ho…

cs.CL2026

Recall Before You Rank: Similarity-Guided Top- Reuse for Efficient Long-Context Attention

Wenshuai Yao, Wenyong Zhou, Hanyong Shao +5

The paper proposes ReTopK, a training‑free technique that speeds up dynamic top‑K sparse attention for long‑context language models by reusing supports from historically similar qu…

cs.CV2026

PatchINR: Patch-Based Implicit Neural Representations for Efficient and Scalable Inference

Jiachen Ren, Wenyong Zhou, Taiqiang Wu +4

Implicit Neural Representation (INR) provides an effective approach for continuous signal modeling, but classical per-pixel inference results in quadratic growth in inference count…