3 papers
cs.SE2025
Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency
Junwei Hu, Weicheng Zheng, Yihan Liu +1
With the increasing adoption of large language models (LLMs) in software engineering, the Chain of Thought (CoT) reasoning paradigm has become an essential approach for automated c…
cs.LG2024
Combining Induction and Transduction for Abstract Reasoning
Wen-Ding Li, Keya Hu, Carter Larsen +11
When learning an input-output mapping from very few examples, is it better to first infer a latent function that explains the examples, or is it better to directly predict new test…
cs.SE2024
Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
Hao Tang, Keya Hu, Jin Peng Zhou +4
Iteratively improving and repairing source code with large language models (LLMs), known as refinement, has emerged as a popular way of generating programs that would be too comple…