Semantic communication exploits the meaning of the payload, which bit-level processing discards. When channel decoding fails on a natural language payload, the errors appear as corrupted characters in the recovered text. A large language model (LLM) infers the intended characters from the semantic context, but it can a...
Sojeong Park, Hyeonsu Lyu, Jaehyun Choi et al.· 1 citation
TAP is a one-shot neural framework that unifies the speed of DL with the mathematical interpretability of CS, replacing iterative pursuit with a lightweight 1D neural network that extracts dominant continuous propagation delays from temporal channel sequences via a differentiable sub-grid interpolation operator.
Minwoo Kim, Hyeonsu Lyu, Sehyun Ryu et al.· 0 citations
LUCID is presented, an LLM-agent--orchestrated, uplink-aware cloud-robotics pipeline that moves TP--RRM from solving a fixed formulation to dynamically orchestrating optimization problem schemas within a DITL environment and robustly adapts to changing intents, active-robot counts, and scenes.
Hyeonsu Lyu, Minwoo Kim, Sehyun Ryu et al.· 0 citations
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