activity
20242026
most citedPreble: Efficient Distributed Prompt Scheduling for LLM Serving

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Search Your Block Floating Point Scales!

Tanmaey Gupta, Hayden Prairie, Xiaoxia Wu +10

Quantization has emerged as a standard technique for accelerating inference for generative models by enabling faster low-precision computations and reduced memory transfers. Recent…

cs.AI2025

OSWorld-Human: Benchmarking the Efficiency of Computer-Use Agents

Reyna Abhyankar, Qi Qi, Yiying Zhang

Generative AI is being leveraged to solve a variety of computer-use tasks involving desktop applications. State-of-the-art systems have focused solely on improving accuracy on lead…

cs.LG2025

Cognify: Supercharging Gen-AI Workflows With Hierarchical Autotuning

Zijian He, Reyna Abhyankar, Vikranth Srivatsa +1

Today's gen-AI workflows that involve multiple ML model calls, tool/API calls, data retrieval, or generic code execution are often tuned manually in an ad-hoc way that is both time…

cs.DC20241 cited

Preble: Efficient Distributed Prompt Scheduling for LLM Serving

Vikranth Srivatsa, Zijian He, Reyna Abhyankar +2

Prompts to large language models (LLMs) have evolved beyond simple user questions. For LLMs to solve complex problems, today's practices are to include domain-specific instructions…

cs.LG2024

InferCept: Efficient Intercept Support for Augmented Large Language Model Inference

Reyna Abhyankar, Zijian He, Vikranth Srivatsa +2

Large language models are increasingly integrated with external environments, tools, and agents like ChatGPT plugins to extend their capability beyond language-centric tasks. Howev…