Brain-CLIPLM recovers compressed semantic anchors from EEG via contrastive learning and uses retrieval-grounded LLM reasoning to achieve 67.55% top-5 and 85% top-25 sentence retrieval accuracy, supporting the view that EEG encodes semantic content rather than full linguistic structure.
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The authors develop a model to compute energy efficiency for GPU-based data processing in LHCb's HLT1 by linking throughput to GPU core count, clock frequency, memory bandwidth, and thermal design power.
Review of helioseismic inversions shows the solar modelling problem remains unsolved with broad implications for stellar seismology and fields relying on precise stellar parameters.
citing papers explorer
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Brain-CLIPLM: Decoding Compressed Semantic Representations in EEG for Language Reconstruction
Brain-CLIPLM recovers compressed semantic anchors from EEG via contrastive learning and uses retrieval-grounded LLM reasoning to achieve 67.55% top-5 and 85% top-25 sentence retrieval accuracy, supporting the view that EEG encodes semantic content rather than full linguistic structure.
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Energy efficiency of a GPU-based computing system for High Energy Physics experiments
The authors develop a model to compute energy efficiency for GPU-based data processing in LHCb's HLT1 by linking throughput to GPU core count, clock frequency, memory bandwidth, and thermal design power.
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Progress in global helioseismology: a new light on the solar modelling problem and its implications for solar-like stars
Review of helioseismic inversions shows the solar modelling problem remains unsolved with broad implications for stellar seismology and fields relying on precise stellar parameters.