1 citations · 3 across the 8 of their papers we have counts for
8 papers
Inference Time Context Sparsity: Illusion or Opportunity?
Sahil Joshi, Prithvi Dixit, Agniva Chowdhury +5
Sparsity has long been a central theme in LLM efficiency, but its role in context processing remains unresolved. As LLM workloads shift toward longer contexts and agentic interacti…
Let the Barbarians In: How AI Can Accelerate Systems Performance Research
Audrey Cheng, Shu Liu, Melissa Pan +18
Artificial Intelligence (AI) is beginning to transform the research process by automating the discovery of new solutions. This shift depends on the availability of reliable verifie…
How Reasoning Influences Intersectional Biases in Vision Language Models
Adit Desai, Sudipta Roy, Mohna Chakraborty
Vision Language Models (VLMs) are increasingly deployed across downstream tasks, yet their training data often encode social biases that surface in outputs. Unlike humans, who inte…
Barbarians at the Gate: How AI is Upending Systems Research
Audrey Cheng, Shu Liu, Melissa Pan +14
Artificial Intelligence (AI) is starting to transform the research process as we know it by automating the discovery of new solutions. Given a task, the typical AI-driven approach…
vAttention: Verified Sparse Attention
Aditya Desai, Kumar Krishna Agrawal, Shuo Yang +5
State-of-the-art sparse attention methods for reducing decoding latency fall into two main categories: approximate top- (and its extension, top-) and recently introduced samp…
The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks
Alejandro Cuadron, Dacheng Li, Wenjie Ma +13
Large Reasoning Models (LRMs) represent a breakthrough in AI problem-solving capabilities, but their effectiveness in interactive environments can be limited. This paper introduces…
vCache: Verified Semantic Prompt Caching
Luis Gaspar Schroeder, Aditya Desai, Alejandro Cuadron +7
Semantic caches return cached responses for semantically similar prompts to reduce LLM inference latency and cost. They embed cached prompts and store them alongside their response…
HashAttention: Semantic Sparsity for Faster Inference
Aditya Desai, Shuo Yang, Alejandro Cuadron +3
Leveraging long contexts is crucial for advanced AI systems, but attention computation poses a scalability challenge. While scaled dot-product attention (SDPA) exhibits token spars…