Classical Chinese poetry composition has long valued Tuiqiao, the iterative refinement of words, imagery, and prosody. However, many current AI poetry systems follow a one-shot generation paradigm, which reduces users to prompt providers and weakens their creative agency. We present Jiuge-Tuiqiao, an interactive human-...
Yufeng Han, Lifan Deng, Cunliang Kong et al.· 0 citations
TIPS (Thinking-Induced Process Supervision), an outcome-only reinforcement learning (RL) framework for training generative PRMs, is introduced and validated, demonstrating the effectiveness of TIPS across math and agent benchmarks and four backbone families.
Sheng-Da Fan, Xin Cong, Zhong Zhang et al.· 0 citations
This work finds that finetuning a reward model to guide the policy model is more robust than directly finetuning the policy model, and proposes AgentRM, a generalizable reward model, to guide the policy model for effective test-time search.
Yu Xia, Jing-Ru Fan, Weize Chen et al.· Annual Meeting of the Associ...· 26 citations· ⚡3
StatFormBench is introduced, a benchmark built from five cross-domain statistics textbooks and a data science case library, covering diverse problem types, data representations, and scenario styles, and no model performs consistently best across the two subtasks.
Chen Wang, Jun-Zhe Zhao, Xin Cong et al.· 0 citations
Analyzing a large corpus of publicly released post-training trajectories, it is found that across different tasks, the agent's training strategy is locked in at the very beginning, and the entire remaining budget is spent on local adjustments within the selected strategy.
J. Lim, Xin Huang, Hao Peng et al.· 2 citations· ⚡1
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