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cs.CL2025
R-WoM: Retrieval-augmented World Model For Computer-use Agents
Kai Mei, Jiang Guo, Shuaichen Chang +4
Large Language Models (LLMs) can serve as world models to enhance agent decision-making in digital environments by simulating future states and predicting action outcomes, potentia…
cs.CL2024
MATTER: Memory-Augmented Transformer Using Heterogeneous Knowledge Sources
Dongkyu Lee, Chandana Satya Prakash, Jack FitzGerald +1
Leveraging external knowledge is crucial for achieving high performance in knowledge-intensive tasks, such as question answering. The retrieve-and-read approach is widely adopted f…