3 papers
cs.CL2025
CoT-based Synthesizer: Enhancing LLM Performance through Answer Synthesis
Bohan Zhang, Xiaokang Zhang, Jing Zhang +3
Current inference scaling methods, such as Self-consistency and Best-of-N, have proven effective in improving the accuracy of LLMs on complex reasoning tasks. However, these method…
cs.CL2025
Dynamic Scaling of Unit Tests for Code Reward Modeling
Zeyao Ma, Xiaokang Zhang, Jing Zhang +3
Current large language models (LLMs) often struggle to produce accurate responses on the first attempt for complex reasoning tasks like code generation. Prior research tackles this…
cs.CL2024
SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation
Zeyao Ma, Bohan Zhang, Jing Zhang +6
We introduce SpreadsheetBench, a challenging spreadsheet manipulation benchmark exclusively derived from real-world scenarios, designed to immerse current large language models (LL…