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Moo-Ai is thinking... Processing hyper-cognitive insights for 'Decoding'
https://arxiv.org/html/2605.00038v2

Lottery BP: Unlocking Quantum Error Decoding at Scale

Content selection saved. Describe the issue below: Entering the megaquop era with millions of qubits towards quantum utility, quantum error correction (QEC) is leveraged to achieve fault tolerant quan...
https://arxiv.org/html/2605.01149v1

ADaPT: Adaptive-window Decoding for Practical fault-Tolerance

Content selection saved. Describe the issue below: Window decoding, first proposed to reduce decoding complexity for real-time decoding, is an essential component to realize scalable, universal-fault ...
https://arxiv.org/html/2602.01582v1

On the Fragility of AI-Based Channel Decoders under Small Channel...

Recent advances in deep learning have led to AI-based error correction decoders that report empirical performance improvements over traditional belief-propagation (BP) decoding on AWGN channels. While...
https://arxiv.org/html/2605.03620v1

Leveraging Code Automorphisms for Improved Syndrome-Based Neural ...

Content selection saved. Describe the issue below: Syndrome-based neural decoding (SBND) has emerged as a promising deep learning approach for soft-decision decoding of high-rate, short-length codes. ...
https://arxiv.org/html/2605.02325v1

DriftDecode: One-Step Wireless Image Decoding via Drifting-Inspir...

Content selection saved. Describe the issue below: Generative receivers for wireless image transmission can improve reconstruction quality, but diffusion-based and flow-based decoding relies on iterat...
https://iharare.com/police-arrest-zimbabweans-for-buying-openview-decoders-following-raids

Police Arrest Zimbabweans For Buying OpenView Decoders After Raid...

Police Arrest Zimbabweans For Buying OpenView Decoders Following Raids The Zimbabwe Republic Police arrested 11 people and seized dozens of OpenView decoders following raids conducted in Beitbridge in...
https://arxiv.org/html/2604.27689v1

Bitwise Over-Parameterized Neural Polar Decoding: A Theoretical P...

Content selection saved. Describe the issue below: This paper proposes a bitwise over-parameterized neural network (ONN) decoder for polar-coded transmission and develops atractable theoretical perfor...
https://arxiv.org/html/2509.16622v3

Audio-Conditioned Diffusion LLMs for ASR and Deliberation Process...

Content selection saved. Describe the issue below: Diffusion-based large language models (DLLMs) have recently attracted growing interest as an alternative to autoregressive decoders. In this work, we...
https://arxiv.org/html/2605.03218v1

Edge-Based Anisotropic Decoding for Generalized Bicycle Codes

Content selection saved. Describe the issue below: Quantum low-density parity-check (QLDPC) codes provide non vanishing rates, distance scaling with the blocklength of the code, and facilitate fast it...
https://arxiv.org/html/2602.01602v2

Spectral-Aligned Pruning for Universal Error-Correcting Code Tran...

Recently, the Foundation Error Correction Code Transformer (FECCT) has emerged as a promisinguniversalchannel decoder, achieving competitive decoding performance across diverse code families by relyin...
https://arxiv.org/html/2605.01035v1

A Scalable FPGA Architecture for Real-Time Decoding of Quantum LD...

Content selection saved. Describe the issue below: In this work, we introduce a new hardware architecture for decoding correlated errors in quantum LDPC codes. The decoder is based on message passing ...
https://www.kdnuggets.com/2021/01/attention-mechanism-deep-learning-explained.html

Attention mechanism in Deep Learning, Explained - KDnuggets

Attention is a powerful mechanism developed to enhance the performance of the Encoder-Decoder architecture on neural network-based machine translation tasks. Learn more about how this process works an...
https://arxiv.org/html/2605.04892v1

Real-time Surface-Code Error Correction Using an FPGA-based Neura...

Content selection saved. Describe the issue below: Quantum error correction (QEC) is essential for achieving low error rates required for fault-tolerant quantum computation. In stabilizer-based codes ...
https://arxiv.org/html/2605.01708v1

SplitZip: Ultra Fast Lossless KV Compression for Disaggregated LL...

Content selection saved. Describe the issue below: Contemporary systems serving large language models (LLMs) have adopted prefill-decode disaggregation to better load-balance between the compute-bound...
https://arxiv.org/html/2502.01068v7

FastKV: Decoupling of Context Reduction and KV Cache Compression ...

Content selection saved. Describe the issue below: While large language models (LLMs) excel at handling long-context sequences, they require substantial prefill computation and key-value (KV) cache, w...
https://www.slideshare.net/slideshow/low-power-ldpc-decoder-implementation-using-layer-decoding/19297340

Low power ldpc decoder implementation using layer decoding | PPTX

This document proposes a low-power LDPC decoder implementation using layered decoding. It discusses how LDPC codes can be used for reliable data transmission and are finding increasing use. It describ...
https://arxiv.org/html/2604.25777v1

SpecFed: Accelerating Federated LLM Inference with Speculative De...

Content selection saved. Describe the issue below: Federated inference enhances LLM performance in edge computing through weighted averaging of distributed model predictions. However, autoregressive L...
https://arxiv.org/html/2602.01174v1

Reducing ORBGRAND Latency via Partial Gaussian Elimination This w...

Guessing Random Additive Noise Decoding (GRAND) is a universal framework for decoding all block codes by testing candidate error patterns (EPs). Ordered Reliability Bits GRAND (ORBGRAND) facilitates p...
https://arxiv.org/html/2502.00085v2

Efficient Beam Search for LLMs Using Trie-Based Decoding

This work presents a novel trie (prefix-tree)-based parallel decoding method that addresses the memory inefficiency of batch-based beam search. By sharing a single KV cache across beams with common pr...
https://arxiv.org/html/2511.02633v2

Relaxed vs. Full Local Decodability with Few Queries: Equivalence...

Algorithm A locally decodable code (LDC)C:{0,1}k→{0,1}nC\colon\{0,1\}^{k}\to\{0,1\}^{n}is an error-correcting code that allows one to recover any bit of the original message with good probability whil...