{"total":20,"rows":[{"id":"2505.22618","title":"Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding","created":"2025-05-28","cited_by_count":420,"area":"inference"},{"id":"2203.16487","title":"Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation","created":"2022-03-30","cited_by_count":171,"area":"inference"},{"id":"2403.09054","title":"Keyformer: KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference","created":"2024-03-14","cited_by_count":126,"area":"inference"},{"id":"2106.04970","title":"Instantaneous Grammatical Error Correction with Shallow Aggressive Decoding","created":"2021-06-09","cited_by_count":53,"area":"inference"},{"id":"2410.04466","title":"Large Language Model Inference Acceleration: A Comprehensive Hardware Perspective","created":"2024-10-06","cited_by_count":38,"area":"inference"},{"id":"2203.01670","title":"A Simple Hash-Based Early Exiting Approach For Language Understanding and Generation","created":"2022-03-03","cited_by_count":32,"area":"inference"},{"id":"2404.04997","title":"Adapting LLMs for Efficient Context Processing through Soft Prompt Compression","created":"2024-04-07","cited_by_count":22,"area":"inference"},{"id":"2305.12228","title":"Dynamic Transformers Provide a False Sense of Efficiency","created":"2023-05-20","cited_by_count":14,"area":"inference"},{"id":"2210.13304","title":"ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and Effective Text Generation","created":"2022-10-24","cited_by_count":10,"area":"inference"},{"id":"2406.01283","title":"Focus on the Core: Efficient Attention via Pruned Token Compression for Document Classification","created":"2024-06-03","cited_by_count":7,"area":"inference"},{"id":"2508.15813","title":"SCOPE: A Generative Approach for LLM Prompt Compression","created":"2025-08-16","cited_by_count":6,"area":"inference"},{"id":"2601.10729","title":"OrbitFlow: SLO-Aware Long-Context LLM Serving with Fine-Grained KV Cache Reconfiguration","created":"2026-01-05","cited_by_count":6,"area":"inference"},{"id":"2412.07682","title":"TRIM: Token Reduction and Inference Modeling for Cost-Effective Language Generation","created":"2024-12-10","cited_by_count":2,"area":"inference"},{"id":"2501.13111","title":"iServe: An Intent-based Serving System for LLMs","created":"2025-01-08","cited_by_count":1,"area":"inference"},{"id":"2508.15371","title":"Confidence-Modulated Speculative Decoding for Large Language Models","created":"2025-08-21","cited_by_count":1,"area":"inference"},{"id":"2512.03643","title":"Optical Context Compression Is Just (Bad) Autoencoding","created":"2025-12-03","cited_by_count":1,"area":"inference"},{"id":"2604.23277","title":"From Similarity to Structure: Training-free LLM Context Compression with Hybrid Graph Priors","created":"2026-04-25","cited_by_count":1,"area":"inference"},{"id":"2408.00539","title":"Intermittent Semi-Working Mask: A New Masking Paradigm for LLMs","created":"2024-08-01","cited_by_count":0,"area":"inference"},{"id":"2503.04521","title":"Dynamic Pricing for On-Demand DNN Inference in the Edge-AI Market","created":"2025-03-06","cited_by_count":0,"area":"inference"},{"id":"2605.23389","title":"AlignedServe: Orchestrating Prefix-aware Batching to Build a High-throughput and Computing-efficient LLM Serving System","created":"2026-05-22","cited_by_count":0,"area":"inference"}],"next_cursor":null}