most citedBridging Neural Networks and Wireless Systems with MIMO-OFDM Semantic Communications

6 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IT2026

Symbol Distributions in Semantic Communications: A Source-Channel Equilibrium Perspective

Hanju Yoo, Dongha Choi, Songkuk Kim +2

Semantic communication systems often use end-to-end neural networks to map input data into continuous symbols. These symbols, which are essentially neural network features, have fi…

cs.IT20266 cited

Bridging Neural Networks and Wireless Systems with MIMO-OFDM Semantic Communications

Hanju Yoo, Dongha Choi, Yonghwi Kim +4

Semantic communications aim to enhance transmission efficiency by jointly optimizing source coding, channel coding, and modulation. While prior research has demonstrated promising…

cs.IR2026

Aligning Sentence Embeddings to Human Concepts via Sparse Autoencoders

Wonseok Shin, Songkuk Kim

Dense sentence embeddings are fundamental to modern Retrieval-Augmented Generation (RAG) systems but suffer from a lack of interpretability due to feature superposition. This opaci…

cs.CV2026

DebFilter: Eradicating Biases Stashed in Value

Seung Hyuk Lee, Songkuk Kim

Text-to-image diffusion models, which are theoretically equivalent to score-based generative models, generate images through a multi-step denoising process guided by text embedding…

cs.CV2026

Sparsity as a Key: Unlocking New Insights from Latent Structures for Out-of-Distribution Detection

Ahyoung Oh, Wonseok Shin, Songkuk Kim

Sparse Autoencoders (SAEs) have demonstrated significant success in interpreting Large Language Models (LLMs) by decomposing dense representations into sparse, semantic components.…