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cs.LG2025
Adapting World Models with Latent-State Dynamics Residuals
JB Lanier, Kyungmin Kim, Armin Karamzade +5
Simulation-to-reality reinforcement learning (RL) faces the critical challenge of reconciling discrepancies between simulated and real-world dynamics, which can severely degrade ag…
cs.CL2025
Learning to Search Effective Example Sequences for In-Context Learning
Xiang Gao, Ankita Sinha, Kamalika Das
Large language models (LLMs) demonstrate impressive few-shot learning capabilities, but their performance varies widely based on the sequence of in-context examples. Key factors in…