3 papers
cs.AI2026
DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints
Yinger Zhang, Shutong Jiang, Renhao Li +6
While agent evaluation has shifted toward long-horizon tasks, most benchmarks still emphasize local, step-level reasoning rather than the global constrained optimization (e.g., tim…
cs.AI2025
ToolRM: Towards Agentic Tool-Use Reward Modeling
Renhao Li, Jianhong Tu, Yang Su +6
Reward models (RMs) play a critical role in aligning large language models (LLMs) with human preferences. Yet in the domain of tool learning, the lack of RMs specifically designed…
cs.CL2025
RMTBench: Benchmarking LLMs Through Multi-Turn User-Centric Role-Playing
Hao Xiang, Tianyi Tang, Yang Su +10
Recent advancements in Large Language Models (LLMs) have shown outstanding potential for role-playing applications. Evaluating these capabilities is becoming crucial yet remains ch…