6 citations · 6 across the 9 of their papers we have counts for
7 papers · 1 filter
LBI: Parallel Scan Backpropagation via Latent Bounded Interfaces
Shaun Christopher Lee, Sangeetha Abdu Jyothi
Backpropagation is inherently sequential across depth, creating an -deep dependency chain that bottlenecks parallel training. While parallel-scan formulations theoretically r…
FlexiCache: Leveraging Temporal Stability of Attention Heads for Efficient KV Cache Management
Nazmul Takbir, Hamidreza Alikhani, Nikil Dutt +1
Large Language Model (LLM) serving is increasingly constrained by the growing size of the key-value (KV) cache, which scales with both context length and generation length. Prior w…
AMAQ: Adaptive Mixed-bit Activation Quantization for Collaborative Parameter Efficient Fine-tuning
Yurun Song, Zhuoyi Yang, Ian G. Harris +1
Large Language Models (LLMs) are scaling rapidly, creating significant challenges for collaborative server client distributed training, particularly in terms of communication effic…
CoopQ: Cooperative Game Inspired Layerwise Mixed Precision Quantization for LLMs
Junchen Zhao, Ali Derakhshan, Jayden Kana Hyman +3
Large Language Models (LLMs) promise impressive capabilities, yet their multi-billion-parameter scale makes on-device or low-resource deployment prohibitive. Mixed-precision quanti…
LinguaLinked: A Distributed Large Language Model Inference System for Mobile Devices
Junchen Zhao, Yurun Song, Simeng Liu +2
Deploying Large Language Models (LLMs) locally on mobile devices presents a significant challenge due to their extensive memory requirements. In this paper, we introduce LinguaLink…
CrystalBox: Future-Based Explanations for Input-Driven Deep RL Systems
Sagar Patel, Sangeetha Abdu Jyothi, Nina Narodytska
We present CrystalBox, a novel, model-agnostic, posthoc explainability framework for Deep Reinforcement Learning (DRL) controllers in the large family of input-driven environments…