Tag: adversarial machine learning
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AI Alignment: From Consensus to Pluralistic Repair
Explore why AI alignment must surface disagreement, moving beyond consensus to embrace pluralistic repair for robust, value-driven AI systems.
KGPFN: Enhancing Knowledge Graph Models with In-Context Learning
Discover how KGPFN boosts knowledge graph reasoning by combining in-context learning and transferable relational structures for superior AI performance.
Interestingness as a Heuristic for AI Compression Progress
Explore how interestingness guides future AI compression progress using algorithmic heuristics and Kolmogorov Complexity for self-improving systems.
Probabilistic Verification of RNNs in Reinforcement Learning
Discover RNN-ProVe, a scalable probabilistic verification method for recurrent neural networks in single and multi-agent reinforcement learning tasks.
Enhancing LLMs with Temporal Critique for Accurate Reasoning
Discover how Temporal Critique Fine-Tuning (TCFT) improves large language models' temporal reasoning by reducing information leakage after cutoff dates.