{"total":24,"rows":[{"id":"2505.09343","title":"Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures","created":"2025-05-14","cited_by_count":39,"area":"moe"},{"id":"2505.19645","title":"MoESD: Unveil Speculative Decoding's Potential for Accelerating Sparse MoE","created":"2025-05-26","cited_by_count":19,"area":"moe"},{"id":"2506.20675","title":"Utility-Driven Speculative Decoding for Mixture-of-Experts","created":"2025-06-17","cited_by_count":13,"area":"moe"},{"id":"2510.10302","title":"SP-MoE: Speculative Decoding and Prefetching for Accelerating MoE-based Model Inference","created":"2025-10-11","cited_by_count":13,"area":"moe"},{"id":"2602.16052","title":"MoE-Spec: Expert Budgeting for Efficient Speculative Decoding","created":"2026-02-17","cited_by_count":12,"area":"moe"},{"id":"2508.21706","title":"Accelerating Mixture-of-Experts Inference by Hiding Offloading Latency with Speculative Decoding","created":"2025-08-29","cited_by_count":8,"area":"moe"},{"id":"2507.08771","title":"BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity","created":"2025-07-11","cited_by_count":6,"area":"moe"},{"id":"2603.09983","title":"MoE-SpAc: Efficient MoE Inference Based on Speculative Activation Utility in Heterogeneous Edge Scenarios","created":"2026-02-12","cited_by_count":5,"area":"moe"},{"id":"2607.14647","title":"D-cut: Adaptive Verification Depth Pruning for Batched Speculative Decoding","created":"2026-07-16","cited_by_count":5,"area":"moe"},{"id":"2604.10152","title":"SpecMoE: A Fast and Efficient Mixture-of-Experts Inference via Self-Assisted Speculative Decoding","created":"2026-04-11","cited_by_count":4,"area":"moe"},{"id":"2605.00342","title":"Making Every Verified Token Count: Adaptive Verification for MoE Speculative Decoding","created":"2026-05-01","cited_by_count":4,"area":"moe"},{"id":"2607.12696","title":"Less Experts, Faster Decoding: Cost-Aware Speculative Decoding for Mixture-of-Experts","created":"2026-07-14","cited_by_count":3,"area":"moe"},{"id":"2512.21911","title":"Accelerate Speculative Decoding with Sparse Computation in Verification","created":"2025-12-26","cited_by_count":2,"area":"moe"},{"id":"2607.24434","title":"DraftExpert: Expansion-Aware Self-Speculative Decoding for End-Device MoE Inference","created":"2026-07-27","cited_by_count":2,"area":"moe"},{"id":"2608.02989","title":"AcceptMoE: Commitment-Weighted Self-Sizing Verifier Expert Sets for Efficient MoE Speculative Decoding","created":"2026-08-04","cited_by_count":1,"area":"moe"},{"id":"2608.18261","title":"Cacheable by Design? Training Mixture-of-Experts Routers for Locality Against the Edge Memory-Bandwidth Wall: A Pre-Registered Negative Result with a Systems Measurement Study","created":"2026-08-18","cited_by_count":1,"area":"moe"},{"id":"2609.22156","title":"The Limits of Speculation: Bounding Speculative Decoding in Mixture-of-Experts","created":"2026-08-26","cited_by_count":1,"area":"moe"},{"id":"2604.14626","title":"ELMoE-3D: Leveraging Intrinsic Elasticity of MoE for Hybrid-Bonding-Enabled Self-Speculative Decoding in On-Premises Serving","created":"2026-04-16","cited_by_count":0,"area":"moe"},{"id":"2605.00254","title":"Rethinking Network Topologies for Cost-Effective Mixture-of-Experts LLM Serving","created":"2026-04-30","cited_by_count":0,"area":"moe"},{"id":"2607.08215","title":"On the Limitations of Non-GPU AI Accelerators for Large-Model Inference: A Field Study of MoE and Multimodal Serving on Huawei Ascend","created":"2026-07-09","cited_by_count":0,"area":"moe"},{"id":"2607.24787","title":"SpecPrefetch: Parameter-Efficient Expert Prefetching for Sparse MoE Foundation Models","created":"2026-06-24","cited_by_count":0,"area":"moe"},{"id":"2608.05303","title":"EdgeXpert: An Edge Device for Memory-Efficient LLM Inference with Mixture-of-Experts and Speculative Decoding","created":"2026-08-05","cited_by_count":0,"area":"moe"},{"id":"2610.05774","title":"AdaSpark: Adaptive DSpark with Online Learning for Tree Verification and N-gram Fill","created":"2026-10-05","cited_by_count":0,"area":"moe"},{"id":"2610.07219","title":"Cascadia: Resident 975B MoE Inference on Eleven AI PCs","created":"2026-10-05","cited_by_count":0,"area":"moe"}],"next_cursor":null}