Papers by Zhiyong Bai
CogBench: Benchmarking Cognitive Alignment of Large Language Models in Educational Question Answering (2026.findings-acl)
Copied to clipboard
| Challenge: | Large language models (LLMs) possess strong capabilities in language understanding and generation, as well as remarkable problem-solving abilities. |
| Approach: | They propose a benchmark to assess the cognitive alignment capabilities of large language models in educational QA. |
| Outcome: | The proposed evaluation benchmark assesses the cognitive alignment capabilities of large language models in educational QA. |
ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks (2025.emnlp-main)
Copied to clipboard
| Challenge: | Multi-agent systems (MAS) are limited by poor flexibility and scalability, with underdeveloped optimization strategies. |
| Approach: | They propose a task graph generation and a reward-driven two-stage agent selection process to integrate multi-agent systems to improve their reasoning capabilities. |
| Outcome: | The proposed model outperforms existing methods on Math-MAS and SciBench-MAS SciBech, while other methods completely fail. |