67 citations · 73 across the 22 of their papers we have counts for
26 papers
Learning More by Training Less: Uncertainty-Guided Progressive Contraction for Efficient Reasoning Post-Training
Suorong Yang, Jiaxin Wang, Jiaming Su +4
Large language models have achieved remarkable advances in complex reasoning. However, scaling reasoning post-training with ever-larger corpora can substantially increase training…
Semantic Error Control Coding with Foundation Models for Future Communications
Chentao Yue, Gaoyang Pang, Branka Vucetic +1
Classical channel decoding typically treats all information sequences as equally likely and relies primarily on the channel observations and code structure, without exploiting stat…
Semantic-Aided Iterative Decoding for Uplink Non-Orthogonal Transmission
Wenjing Wei, Chentao Yue, Branka Vucetic +1
This paper proposes semantic-aided iterative decoding (Sem-IR) for uplink non-orthogonal transmission of a shared natural-language source. K users each hold one segment of a common…
Semantic Ordered Statistics Decoding
Chentao Yue, Branka Vucetic, Yonghui Li
We propose a Semantic Ordered Statistics Decoder (sem-OSD), a soft decoder for short linear block codes carrying byte-streamed sources such as natural-language text. Sem-OSD inject…
Semantic Error Correction and Decoding for Short Block Codes
Jiafu Hao, Chentao Yue, Wanchun Liu +2
This paper presents a semantic-enhanced receiver framework for transmitting natural language sentences over noisy wireless channels using multiple short block codes. After ASCII en…
LLM-Viterbi: Semantic-Aware Decoding for Convolutional Codes
Zhengtong Li, Chentao Yue, Jiafu Hao +2
Traditional wireless communications rely solely on bit-level channel coding for error correction, without exploiting the inherent linguistic structure of the data source. This pape…
BCH Coding Assisted Imaging
Hao Jiang, Shuang Liu, Chentao Yue +1
In modern correlation imaging systems, also known as ghost imaging (GI), particularly under low-light or noisy conditions, preserving high image fidelity presents a significant cha…
Toward Wireless Human-Machine Collaboration in the 6G Era
Gaoyang Pang, Wanchun Liu, Chentao Yue +4
The next industrial revolution, Industry 5.0, will be driven by advanced technologies that foster human-machine collaboration (HMC). It will leverage human creativity, judgment, an…
Policy-Guided MCTS for near Maximum-Likelihood Decoding of Short Codes
Y. Tian, C. Yue, P. Cheng +3
In this paper, we propose a policy-guided Monte Carlo Tree Search (MCTS) decoder that achieves near maximum-likelihood decoding (MLD) performance for short block codes. The MCTS de…
Medical Referring Image Segmentation via Next-Token Mask Prediction
Xinyu Chen, Yiran Wang, Gaoyang Pang +4
Medical Referring Image Segmentation (MRIS) involves segmenting target regions in medical images based on natural language descriptions. While achieving promising results, recent a…
Short Wins Long: Short Codes with Language Model Semantic Correction Outperform Long Codes
Jiafu Hao, Chentao Yue, Hao Chang +2
This paper presents a novel semantic-enhanced decoding scheme for transmitting natural language sentences with multiple short block codes over noisy wireless channels. After ASCII…
Optimal Linear MAP Decoding of Convolutional Codes
Yonghui Li, Chentao Yue, Branka Vucetic
In this paper, we propose a linear representation of BCJR maximum a posteriori probability (MAP) decoding of a rate 1/2 convolutional code (CC), referred to as the linear MAP decod…
GNN-based Auto-Encoder for Short Linear Block Codes: A DRL Approach
Kou Tian, Chentao Yue, Changyang She +2
This paper presents a novel auto-encoder based end-to-end channel encoding and decoding. It integrates deep reinforcement learning (DRL) and graph neural networks (GNN) in code des…
Half a Century of Distributed Byzantine Fault-Tolerant Consensus: Design Principles and Evolutionary Pathways
Huanyu Wu, Chentao Yue, Yixuan Fan +2
The concept of distributed consensus originated in the 1970s and gained widespread attention following Leslie Lamport's influential publication on the Byzantine Generals Problem in…
The Guesswork of Ordered Statistics Decoding: Guesswork Complexity and Decoder Design
Chentao Yue, Changyang She, Branka Vucetic +1
This paper investigates guesswork over ordered statistics and formulates the achievable guesswork complexity of ordered statistics decoding (OSD) in binary additive white Gaussian…
When Distributed Consensus Meets Wireless Connected Autonomous Systems: A Review and A DAG-based Approach
Huanyu Wu, Chentao Yue, Lei Zhang +2
The connected and autonomous systems (CAS) and auto-driving era is coming into our life. To support CAS applications such as AI-driven decision-making and blockchain-based smart da…
Efficient Near Maximum-Likelihood Reliability-Based Decoding for Short LDPC Codes
Weiyang Zhang, Chentao Yue, Yonghui Li +1
In this paper, we propose an efficient decoding algorithm for short low-density parity check (LDPC) codes by carefully combining the belief propagation (BP) decoding and order stat…
A Scalable Graph Neural Network Decoder for Short Block Codes
Kou Tian, Chentao Yue, Changyang She +2
In this work, we propose a novel decoding algorithm for short block codes based on an edge-weighted graph neural network (EW-GNN). The EW-GNN decoder operates on the Tanner graph w…
Bayesian Neural Network Detector for an Orthogonal Time Frequency Space Modulation
Alva Kosasih, Xinwei Qu, Wibowo Hardjawana +2
The orthogonal time-frequency space (OTFS) modulation is proposed for beyond 5G wireless systems to deal with high mobility communications. The existing low complexity OTFS detecto…
Ordered-Statistics Decoding with Adaptive Gaussian Elimination Reduction for Short Codes
Chentao Yue, Mahyar Shirvanimoghaddam, Branka Vucetic +1
In this paper, we propose an efficient ordered-statistics decoding (OSD) algorithm with an adaptive Gaussian elimination (GE) reduction technique. The proposed decoder utilizes two…
Efficient Decoders for Short Block Length Codes in 6G URLLC
Chentao Yue, Vera Miloslavskaya, Mahyar Shirvanimoghaddam +2
This paper reviews the potential channel decoding techniques for ultra-reliable low-latency communications (URLLC). URLLC is renowned for its stringent requirements including ultra…
Density Evolution Analysis of the Iterative Joint Ordered-Statistics Decoding for NOMA
Chentao Yue, Mahyar Shirvanimoghaddam, Alva Kosasih +5
In this paper, we develop a density evolution (DE) framework for analyzing the iterative joint decoding (JD) for non-orthogonal multiple access (NOMA) systems, where the ordered-st…
NOMA Joint Decoding based on Soft-Output Ordered-Statistics Decoder for Short Block Codes
Chentao Yue, Alva Kosasih, Mahyar Shirvanimoghaddam +5
In this paper, we design the joint decoding (JD) of non-orthogonal multiple access (NOMA) systems employing short block length codes. We first proposed a low-complexity soft-output…
Linear-Equation Ordered-Statistics Decoding
Chentao Yue, Mahyar Shirvanimoghaddam, Giyoon Park +3
In this paper, we propose a new linear-equation ordered-statistics decoding (LE-OSD). Unlike the OSD, LE-OSD uses high reliable parity bits rather than information bits to recover…