Otters++ realizes TTFS via measured device decay in optical synapses, uses hybrid QNN-equivalent training with noise awareness, and reports 84.17% average GLUE score with energy gains over prior spiking transformers.
Pushing large language models to the 6G edge: Vision, challenges, and opportunities
6 Pith papers cite this work. Polarity classification is still indexing.
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TrimCaching introduces parameter-sharing edge caching for AI models, formulates it as a submodular maximization problem with submodular constraints, provides approximation algorithms for special and general cases, and shows improved cache hit ratios in simulations.
PragLocker generates function-preserving but non-portable prompts for LLM agents via code-symbol semantic anchoring followed by target-model feedback noise injection.
MM-Telco creates multimodal benchmarks for telecom and demonstrates that fine-tuned LLMs and VLMs achieve significant performance gains on domain-specific tasks.
PA-LLM-RAG adds policy retrieval and dual-LLM verification to enable reliable low-latency mission orchestration in simulated IoBT environments, with Gemma-2B reaching 100% policy compliance at 4.17s latency.
The survey introduces personalized federated intelligence (PFI) as a framework integrating federated learning and foundation models to support privacy-aware personalization of AI models.
citing papers explorer
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Otters++: A Time-to-first-spike Based Energy Efficient Optical Spiking Transformer
Otters++ realizes TTFS via measured device decay in optical synapses, uses hybrid QNN-equivalent training with noise awareness, and reports 84.17% average GLUE score with energy gains over prior spiking transformers.
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TrimCaching: Parameter-sharing Edge Caching for AI Model Downloading
TrimCaching introduces parameter-sharing edge caching for AI models, formulates it as a submodular maximization problem with submodular constraints, provides approximation algorithms for special and general cases, and shows improved cache hit ratios in simulations.
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PragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Prompts
PragLocker generates function-preserving but non-portable prompts for LLM agents via code-symbol semantic anchoring followed by target-model feedback noise injection.
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MM-Telco: Benchmarks and Multimodal Large Language Models for Telecom Applications
MM-Telco creates multimodal benchmarks for telecom and demonstrates that fine-tuned LLMs and VLMs achieve significant performance gains on domain-specific tasks.
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Policy-Aware Edge LLM-RAG Framework for Internet of Battlefield Things Mission Orchestration
PA-LLM-RAG adds policy retrieval and dual-LLM verification to enable reliable low-latency mission orchestration in simulated IoBT environments, with Gemma-2B reaching 100% policy compliance at 4.17s latency.
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A Survey on Foundation Models for Personalized Federated Intelligence
The survey introduces personalized federated intelligence (PFI) as a framework integrating federated learning and foundation models to support privacy-aware personalization of AI models.