3 papers
cs.LG2026
Fast Forward: Accelerating LLM Prefill with Predictive FFN Sparsity
Aayush Gautam, Mukul Gagrani, Junyoung Park +3
The prefill stage of large language model (LLM) inference is a key computational bottleneck for long-context workloads. At short-to-moderate context lengths (1K--16K tokens), Feed-…
cs.LG2025
Polar Sparsity: High Throughput Batched LLM Inferencing with Scalable Contextual Sparsity
Susav Shrestha, Brad Settlemyer, Nikoli Dryden +1
Accelerating large language model (LLM) inference is critical for real-world deployments requiring high throughput and low latency. Contextual sparsity, where each token dynamicall…
cs.CL2025
Token-Driven GammaTune: Adaptive Calibration for Enhanced Speculative Decoding
Aayush Gautam, Susav Shrestha, Narasimha Reddy
Speculative decoding accelerates large language model (LLM) inference by using a smaller draft model to propose tokens, which are then verified by a larger target model. However, s…