{"total":44,"rows":[{"id":"2504.18583","title":"PARD: Accelerating LLM Inference with Low-Cost PARallel Draft Model Adaptation","created":"2025-04-23","cited_by_count":29,"area":"inference"},{"id":"2502.19732","title":"Speculative Decoding and Beyond: An In-Depth Survey of Techniques","created":"2025-02-27","cited_by_count":23,"area":"inference"},{"id":"2508.16201","title":"SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning","created":"2025-08-22","cited_by_count":20,"area":"inference"},{"id":"2603.18567","title":"SpecForge: A Flexible and Efficient Open-Source Training Framework for Speculative Decoding","created":"2026-03-19","cited_by_count":16,"area":"inference"},{"id":"2507.01449","title":"LogitSpec: Accelerating Retrieval-based Speculative Decoding via Next Next Token Speculation","created":"2025-07-02","cited_by_count":14,"area":"inference"},{"id":"2505.16162","title":"KNN-SSD: Enabling Dynamic Self-Speculative Decoding via Nearest Neighbor Layer Set Optimization","created":"2025-05-22","cited_by_count":11,"area":"inference"},{"id":"2505.24196","title":"CLaSp: In-Context Layer Skip for Self-Speculative Decoding","created":"2025-05-30","cited_by_count":11,"area":"inference"},{"id":"2511.22972","title":"Training-Free Loosely Speculative Decoding: Accepting Semantically Correct Drafts Beyond Exact Match","created":"2025-11-28","cited_by_count":10,"area":"inference"},{"id":"2504.05598","title":"DEL: Context-Aware Dynamic Exit Layer for Efficient Self-Speculative Decoding","created":"2025-04-08","cited_by_count":8,"area":"inference"},{"id":"2512.02337","title":"SpecPV: Improving Self-Speculative Decoding for Long-Context Generation via Partial Verification","created":"2025-12-02","cited_by_count":7,"area":"inference"},{"id":"2602.07223","title":"Vegas: Self-Speculative Decoding with Verification-Guided Sparse Attention","created":"2026-02-06","cited_by_count":7,"area":"inference"},{"id":"2411.11055","title":"FastDraft: How to Train Your Draft","created":"2024-11-17","cited_by_count":6,"area":"inference"},{"id":"2605.20104","title":"Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding","created":"2026-05-19","cited_by_count":6,"area":"inference"},{"id":"2602.20217","title":"KnapSpec: Self-Speculative Decoding via Adaptive Layer Selection as a Knapsack Problem","created":"2026-02-23","cited_by_count":5,"area":"inference"},{"id":"2604.05650","title":"See the Forest for the Trees: Loosely Speculative Decoding via Visual-Semantic Guidance for Efficient Inference of Video LLMs","created":"2026-04-07","cited_by_count":5,"area":"inference"},{"id":"2604.26412","title":"When Hidden States Drift: Can KV Caches Rescue Long-Range Speculative Decoding?","created":"2026-04-29","cited_by_count":5,"area":"inference"},{"id":"2504.04104","title":"SpecPipe: Accelerating Pipeline Parallelism-based LLM Inference with Speculative Decoding","created":"2025-04-05","cited_by_count":4,"area":"inference"},{"id":"2507.02659","title":"OmniDraft: A Cross-vocabulary, Online Adaptive Drafter for On-device Speculative Decoding","created":"2025-07-03","cited_by_count":4,"area":"inference"},{"id":"2510.26843","title":"CAS-Spec: Cascade Adaptive Self-Speculative Decoding for On-the-Fly Lossless Inference Acceleration of LLMs","created":"2025-10-30","cited_by_count":4,"area":"inference"},{"id":"2510.01336","title":"HiSpec: Hierarchical Speculative Decoding for LLMs","created":"2025-10-01","cited_by_count":3,"area":"inference"},{"id":"2601.08273","title":"HIPPO: Accelerating Video Large Language Models Inference via Holistic-aware Parallel Speculative Decoding","created":"2026-01-13","cited_by_count":3,"area":"inference"},{"id":"2604.14612","title":"ConfLayers: Adaptive Confidence-based Layer Skipping for Self-Speculative Decoding","created":"2026-04-16","cited_by_count":3,"area":"inference"},{"id":"2505.22757","title":"Pre-Training Curriculum for Multi-Token Prediction in Language Models","created":"2025-05-28","cited_by_count":2,"area":"inference"},{"id":"2512.11280","title":"AdaSD: Adaptive Speculative Decoding for Efficient Language Model Inference","created":"2025-12-12","cited_by_count":2,"area":"inference"},{"id":"2609.09662","title":"PELM: Power Efficient On-Device LLM Inference with Speculative Decoding and Dynamic Voltage Frequency Scaling","created":"2026-09-09","cited_by_count":2,"area":"inference"},{"id":"2509.18344","title":"Speculate Deep and Accurate: Lossless and Training-Free Acceleration for Offloaded LLMs via Substitute Speculative Decoding","created":"2025-09-22","cited_by_count":1,"area":"inference"},{"id":"2509.19368","title":"Pipeline Parallelism is All You Need for Optimized Early-Exit Based Self-Speculative Decoding","created":"2025-09-19","cited_by_count":1,"area":"inference"},{"id":"2510.18525","title":"From Quarter to All: Accelerating Speculative LLM Decoding via Floating-Point Exponent Remapping and Parameter Sharing","created":"2025-10-21","cited_by_count":1,"area":"inference"},{"id":"2512.09963","title":"GoodSpeed: Optimizing Fair Goodput with Adaptive Speculative Decoding in Distributed Edge Inference","created":"2025-12-10","cited_by_count":1,"area":"inference"},{"id":"2601.20357","title":"TABED: Test-Time Adaptive Ensemble Drafting for Robust Speculative Decoding in LVLMs","created":"2026-01-28","cited_by_count":1,"area":"inference"},{"id":"2604.20503","title":"FASER: Fine-Grained Phase Management for Speculative Decoding in Dynamic LLM Serving","created":"2026-04-22","cited_by_count":1,"area":"inference"},{"id":"2605.01106","title":"Component-Aware Self-Speculative Decoding in Hybrid Language Models","created":"2026-05-01","cited_by_count":1,"area":"inference"},{"id":"2609.17943","title":"ASPIRE: Asynchronous Batched Self-Speculative Decoding for Long-Context LLM Inference","created":"2026-09-16","cited_by_count":1,"area":"inference"},{"id":"2602.05499","title":"SDFP: Speculative Decoding with FIT-Pruned Models for Training-Free and Plug-and-Play LLM Acceleration","created":"2026-02-05","cited_by_count":0,"area":"inference"},{"id":"2604.13634","title":"Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference","created":"2026-04-15","cited_by_count":0,"area":"inference"},{"id":"2605.11186","title":"CATS: Cascaded Adaptive Tree Speculation for Memory-Limited LLM Inference Acceleration","created":"2026-05-11","cited_by_count":0,"area":"inference"},{"id":"2605.26558","title":"Cassandra: Enabling Reasoning LLMs at Edge via Self-Speculative Decoding","created":"2026-05-26","cited_by_count":0,"area":"inference"},{"id":"2606.12243","title":"VIA-SD: Verification via Intra-Model Routing for Speculative Decoding","created":"2026-06-10","cited_by_count":0,"area":"inference"},{"id":"2608.05926","title":"BALANCE: Hybrid Autoregressive-Speculative LLM Inference at the Network Edge","created":"2026-08-06","cited_by_count":0,"area":"inference"},{"id":"2608.28846","title":"A rigor-matched audit of periodic-step layer skipping for efficient llm inference: conflayers versus swift, with a supplemental analysis of trained routing alternatives","created":"2026-08-28","cited_by_count":0,"area":"inference"},{"id":"2609.09338","title":"Osprey: Target-agnostic Pre-training Makes Stronger Drafters in Speculative Decoding","created":"2026-09-08","cited_by_count":0,"area":"inference"},{"id":"2609.36590","title":"SEED: Self-Speculative Decoding via Implicit Encoder-Decoder","created":"2026-09-29","cited_by_count":0,"area":"inference"},{"id":"2610.02800","title":"BitNest: Bit-Nested Speculative Decoding for Memory-Efficient LLM Inference Acceleration","created":"2026-10-02","cited_by_count":0,"area":"inference"},{"id":"2610.13202","title":"S$^3$R: Fast and Faithful RL Rollouts via Self-Sparse Speculative Decoding","created":"2026-10-09","cited_by_count":0,"area":"inference"}],"next_cursor":null}