Papers with tree expansion
ThoughtProbe: Classifier-Guided LLM Thought Space Exploration via Probing Representations (2025.emnlp-main)
Copied to clipboard
| Challenge: | Unlike previous works that manipulate representations to steer LLM generation, ThoughtProbe harnesses them as discriminative signals to guide the tree-structured response space exploration. |
| Approach: | They propose a tree-structured inference-time framework that leverages the hidden reasoning features of Large Language Models to improve their reasoning performance. |
| Outcome: | The proposed framework improves reasoning performance across multiple arithmetic reasoning benchmarks and covers valid reasoning chains and identifies optimal answers. |
TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling (2025.findings-emnlp)
Copied to clipboard
Jiahao Qiu, Yifu Lu, Yifan Zeng, Jiacheng Guo, Jiayi Geng, Chenhao Zhu, Xinzhe Juan, Ling Yang, Huazheng Wang, Kaixuan Huang, Yue Wu, Mengdi Wang
| Challenge: | Best-of-N (BoN) sampling generates multiple responses and selects the best one, achieving improved performance but with a high computational cost. |
| Approach: | They propose a framework that integrates a speculative tree-search strategy into Best-of-N (BoN) Sampling. |
| Outcome: | The proposed framework outperforms Best-of-N (BoN) sampling but has high computational cost . tree-search strategy reduces computational overhead while maintaining high output quality . |