7 citations · 18 across the 7 of their papers we have counts for
7 papers
SpecBench: Evaluating Specification-Level Reasoning for Software Engineering LLM Agents
Grant Hamblin, Kevin Song, Zhanda Zhu +4
Software engineering (SWE) agents are transitioning from code generation to full software development lifecycle automation. A critical phase in this lifecycle is specification desi…
LoRAFusion: Efficient LoRA Fine-Tuning for LLMs
Zhanda Zhu, Qidong Su, Yaoyao Ding +3
Low-Rank Adaptation (LoRA) has become the leading Parameter-Efficient Fine-Tuning (PEFT) method for Large Language Models (LLMs), as it significantly reduces GPU memory usage while…
Aegis: Taxonomy and Optimizations for Overcoming Agent-Environment Failures in LLM Agents
Kevin Song, Anand Jayarajan, Yaoyao Ding +4
Large Language Models (LLMs) agents augmented with domain tools promise to autonomously execute complex tasks requiring human-level intelligence, such as customer service and digit…
Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization
Zhanda Zhu, Christina Giannoula, Muralidhar Andoorveedu +4
Various parallelism, such as data, tensor, and pipeline parallelism, along with memory optimizations like activation checkpointing, redundancy elimination, and offloading, have bee…
Seesaw: High-throughput LLM Inference via Model Re-sharding
Qidong Su, Wei Zhao, Xin Li +6
To improve the efficiency of distributed large language model (LLM) inference, various parallelization strategies, such as tensor and pipeline parallelism, have been proposed. Howe…
Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction
Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng +1
Training deep learning models can be computationally expensive. Prior works have shown that increasing the batch size can potentially lead to better overall throughput. However, th…
RGB Matters: Learning 7-DoF Grasp Poses on Monocular RGBD Images
Minghao Gou, Hao-Shu Fang, Zhanda Zhu +3
General object grasping is an important yet unsolved problem in the field of robotics. Most of the current methods either generate grasp poses with few DoF that fail to cover most…