{"total":30,"rows":[{"id":"2410.21465","title":"ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference","created":"2024-10-28","cited_by_count":134,"area":"inference"},{"id":"2405.14366","title":"MiniCache: KV Cache Compression in Depth Dimension for Large Language Models","created":"2024-05-23","cited_by_count":125,"area":"inference"},{"id":"2409.17422","title":"Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction","created":"2024-09-25","cited_by_count":39,"area":"inference"},{"id":"2503.18292","title":"Jenga: Effective Memory Management for Serving LLM with Heterogeneity","created":"2025-03-24","cited_by_count":25,"area":"inference"},{"id":"2410.01805","title":"Locret: Enhancing Eviction in Long-Context LLM Inference with Trained Retaining Heads on Consumer-Grade Devices","created":"2024-10-02","cited_by_count":15,"area":"inference"},{"id":"2411.03786","title":"The N-Grammys: Accelerating Autoregressive Inference with Learning-Free Batched Speculation","created":"2024-11-06","cited_by_count":14,"area":"inference"},{"id":"2412.15803","title":"WebLLM: A High-Performance In-Browser LLM Inference Engine","created":"2024-12-20","cited_by_count":14,"area":"inference"},{"id":"2508.13666","title":"The Hidden Cost of Readability: How Code Formatting Silently Consumes Your LLM Budget","created":"2025-08-19","cited_by_count":12,"area":"inference"},{"id":"2410.08391","title":"KV Prediction for Improved Time to First Token","created":"2024-10-10","cited_by_count":11,"area":"inference"},{"id":"2412.01380","title":"Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking","created":"2024-12-02","cited_by_count":11,"area":"inference"},{"id":"2502.15075","title":"Quantize What Counts: More for Keys, Less for Values","created":"2025-02-20","cited_by_count":10,"area":"inference"},{"id":"2507.11953","title":"IAM: Efficient Inference through Attention Mapping between Different-scale LLMs","created":"2025-07-16","cited_by_count":10,"area":"inference"},{"id":"2505.12942","title":"A3 : an Analytical Low-Rank Approximation Framework for Attention","created":"2025-05-19","cited_by_count":8,"area":"inference"},{"id":"2411.11055","title":"FastDraft: How to Train Your Draft","created":"2024-11-17","cited_by_count":6,"area":"inference"},{"id":"2504.14992","title":"Efficient Pretraining Length Scaling","created":"2025-04-21","cited_by_count":6,"area":"inference"},{"id":"2508.02751","title":"SmallKV: Small Model Assisted Compensation of KV Cache Compression for Efficient LLM Inference","created":"2025-08-03","cited_by_count":6,"area":"inference"},{"id":"2602.05929","title":"KV-CoRE: Benchmarking Data-Dependent Low-Rank Compressibility of KV-Caches in LLMs","created":"2026-02-05","cited_by_count":5,"area":"inference"},{"id":"2502.06474","title":"UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths","created":"2025-02-10","cited_by_count":4,"area":"inference"},{"id":"2411.16003","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","created":"2024-11-24","cited_by_count":3,"area":"inference"},{"id":"2605.18053","title":"Protection Is (Nearly) All You Need: Structural Protection Dominates Scoring in Globally Capped KV Eviction","created":"2026-05-18","cited_by_count":3,"area":"inference"},{"id":"2606.23581","title":"Kamera: Unified Position-Invariant Multimodal KV Cache for Training-Free Reuse","created":"2026-06-22","cited_by_count":3,"area":"inference"},{"id":"2505.02380","title":"EntroLLM: Entropy Encoded Weight Compression for Efficient Large Language Model Inference on Edge Devices","created":"2025-05-05","cited_by_count":2,"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":"2510.13161","title":"Mirror Speculative Decoding: Breaking the Serial Barrier in LLM Inference","created":"2025-10-15","cited_by_count":2,"area":"inference"},{"id":"2409.14091","title":"Normalized Narrow Jump To Conclusions: Normalized Narrow Shortcuts for Parameter Efficient Early Exit Transformer Prediction","created":"2024-09-21","cited_by_count":1,"area":"inference"},{"id":"2608.30295","title":"CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration","created":"2026-08-31","cited_by_count":1,"area":"inference"},{"id":"2503.19950","title":"LogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy Preservation","created":"2025-03-25","cited_by_count":0,"area":"inference"},{"id":"2504.13984","title":"One Jump Is All You Need: Short-Cutting Transformers for Early Exit Prediction with One Jump to Fit All Exit Levels","created":"2025-04-18","cited_by_count":0,"area":"inference"},{"id":"2607.21985","title":"Unified Static-Dynamic Pruning for Efficient LLM Inference","created":"2026-07-24","cited_by_count":0,"area":"inference"},{"id":"2609.34380","title":"DPS: Dual-Mode Precision LLM Serving with Semi-Unified Memory","created":"2026-09-28","cited_by_count":0,"area":"inference"}],"next_cursor":null}