3 papers
cs.AI2026
Exploration and Exploitation Errors Are Measurable for Language Model Agents
Jaden Park, Jungtaek Kim, Jongwon Jeong +3
Language Model (LM) agents are increasingly used in complex open-ended decision-making tasks, from AI coding to physical AI. A core requirement in these settings is the ability to…
cs.AI2026
The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break
Xinyu Jessica Wang, Haoyue Bai, Yiyou Sun +7
Large language model (LLM) agents perform strongly on short- and mid-horizon tasks, but often break down on long-horizon tasks that require extended, interdependent action sequence…
cs.LG2025
Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning
Subhojyoti Mukherjee, Josiah P. Hanna, Qiaomin Xie +1
We study learning to learn for the multi-task structured bandit problem where the goal is to learn a near-optimal algorithm that minimizes cumulative regret. The tasks share a comm…