most citedUncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation

2 citations · 2 across the 10 of their papers we have counts for

collaborators
Showing cs.AIShow all

2 papers · 1 filter

cs.AI2026

ARCO: Adaptive Rubrics with Co-Evolution for Multi-Step LLM-Based Agents

Zihang Tian, Jingsen Zhang, Rui Li +3

Reinforcement learning for multi-step LLM agents often relies on scalar rewards that indicate success but cannot explain why a trajectory is good or bad. Rubric-based rewards impro…

cs.AI2026

LLM Agents as Social Scientists: A Human-AI Collaborative Platform for Social Science Automation

Lei Wang, Yuanzi Li, Jinchao Wu +4

Traditional social science research often requires designing complex experiments across vast methodological spaces and depends on real human participants, making it labor-intensive…