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cs.CL2026
Reward Prediction with Factorized World States
Yijun Shen, Delong Chen, Xianming Hu +4
Agents must infer action outcomes and select actions that maximize a reward signal indicating how close the goal is to being reached. Supervised learning of reward models could int…
cs.CL2024
End-to-End Graph Flattening Method for Large Language Models
Bin Hong, Jinze Wu, Jiayu Liu +5
In recent years, the breakthrough of Large Language Models (LLMs) offers new ideas for achieving universal methods on graph data. The common practice of converting graphs into natu…