Hugging Face's logo
Pavan Kumar Balijepalli's picture
28 11 28

Pavan Kumar Balijepalli

pavankumarbalijepalli
Lingalingeswaran's profile picture regisss's profile picture LeroyDyer's profile picture
·

AI & ML interests

Learn. Build. Teach.

Recent Activity

new activity about 1 month ago
huggingface/InferenceSupport:indiehackers/mistral-tenglish-april5_2
posted an update about 2 months ago
The quadratic bottleneck of long-context LLMs just hit a massive speed wall. Processing long-context sequences in LLMs is computationally expensive due to the quadratic complexity of self-attention. Existing sparse attention methods often rely on sorting or cumulative summation (Top-k/Top-p), which are slow and struggle to prune the "long-tail" of irrelevant tokens. - FlashPrefill achieves a 27.78× speedup on 256K sequences by replacing heavy sorting with a Max-based Dynamic Thresholding mechanism. - It introduces "Instantaneous Pattern Discovery" using block-level approximations, bypassing the need for expensive, full-attention score calculations. - Unlike previous methods that struggle with shorter contexts, it maintains a 1.71× speedup even at 4K, proving its robustness across all scales. - The framework is fully compatible with existing LLM/VLM architectures and integrates seamlessly into vLLM for real-world deployment. This breakthrough significantly reduces Time-to-First-Token (TTFT) for long-context applications, making massive document analysis and long-video understanding practical and cost-effective. It turns a major performance bottleneck into a streamlined, hardware-efficient process. How much compute are we wasting on "long-tail" tokens that don't actually matter? FlashPrefill suggests the answer is: a lot. #AI #LLMs #MachineLearning #DeepLearning #TechInnovation #GPUComputing Source: https://arxiv.org/pdf/2603.06199
updated a Space 2 months ago
pavankumarbalijepalli/portfolio
View all activity

Organizations

Social Post Explorers's profile picture HappyDevCorp's profile picture Hugging Face Context Course's profile picture