4 papers · 1 filter
MultiGA: Leveraging Multi-Source Seeding in Genetic Algorithms
Isabelle Diana May-Xin Ng, Tharindu Cyril Weerasooriya, Haitao Zhu +1
In this paper, we introduce, MultiGA, an optimization framework which applies genetic algorithm principles to address complex natural language tasks and reasoning problems by sampl…
ProRefine: Inference-Time Prompt Refinement with Textual Feedback
Deepak Pandita, Tharindu Cyril Weerasooriya, Ankit Parag Shah +3
Agentic workflows, where multiple AI agents collaborate to accomplish complex tasks like reasoning or planning, play a substantial role in many cutting-edge commercial applications…
Learning a Canonical Basis of Human Preferences from Binary Ratings
Kailas Vodrahalli, Wei Wei, James Zou
Recent advances in generative AI have been driven by alignment techniques such as reinforcement learning from human feedback (RLHF). RLHF and related techniques typically involve c…
VecTrans: Enhancing Compiler Auto-Vectorization through LLM-Assisted Code Transformations
Zhongchun Zheng, Kan Wu, Long Cheng +7
Auto-vectorization is a fundamental optimization for modern compilers to exploit SIMD parallelism. However, state-of-the-art approaches still struggle to handle intricate code patt…