Long-form RewardBench: Evaluating Reward Models for Long-form Generation
The widespread adoption of reinforcement learning-based alignment highlights the growing importance of reward models. Various benchmarks have been built to evaluate reward models in various domains and scenarios. However, a significant gap remains in assessing reward models for long-form generation, despite its critical role in real-world applications. To bridge this, we introduce Long-form RewardBench, the first reward modeling testbed specifically designed for long-form generation. Our benchmark encompasses five key subtasks: QA, RAG, Chat, Writing, and Reasoning. We collected instruction and preference data through a meticulously designed multi-stage data collection process, and conduc...
| Authors | Hui Huang, Yancheng He, Wei Liu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 13 March 2026 |
| Last updated at source | 13 March 2026 |
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