A scalable cross-attention Transformer fuses multi-AP OFDM uplink signals to produce decoder-ready LLRs without channel estimation and outperforms classical and neural baselines on realistic Wi-Fi channels.
Attention is all you need
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pcsp is a shared RL policy using LLM persona embeddings, low-rank projection, and PPO+InfoNCE+KL training that delivers 17x above-chance zero-shot persona identification and 22x faster inference on a 300-persona benchmark.
BitFlipScope localizes bit-flip corruptions in transformer-based LLMs via differential analysis or perturbation profiling and enables recovery without fine-tuning.
FM-BFF-Net combines focal modulation attention with bidirectional encoder-decoder fusion in a CNN-transformer architecture and reports higher Dice and Jaccard scores than recent methods across eight medical image datasets.
citing papers explorer
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Scalable Cross-Attention Transformer for Cooperative Multi-AP OFDM Uplink Reception
A scalable cross-attention Transformer fuses multi-AP OFDM uplink signals to produce decoder-ready LLRs without channel estimation and outperforms classical and neural baselines on realistic Wi-Fi channels.
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One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents
pcsp is a shared RL policy using LLM persona embeddings, low-rank projection, and PPO+InfoNCE+KL training that delivers 17x above-chance zero-shot persona identification and 22x faster inference on a 300-persona benchmark.
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BitFlipScope: Scalable Fault Localization and Recovery for Bit-Flip Corruptions in LLMs
BitFlipScope localizes bit-flip corruptions in transformer-based LLMs via differential analysis or perturbation profiling and enables recovery without fine-tuning.
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Focal Modulation and Bidirectional Feature Fusion Network for Medical Image Segmentation
FM-BFF-Net combines focal modulation attention with bidirectional encoder-decoder fusion in a CNN-transformer architecture and reports higher Dice and Jaccard scores than recent methods across eight medical image datasets.