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continual learning 26 reinforcement learning 9 language models 5 large language models 4 robotics 4 agents 3 generative models 3 multi-agent systems 3 recursive self-improvement 3 vision-language models 3

15 SEP 2026 · Paper

ImpossibleRubrics: Stress-Testing Generated Rubrics as Reward Signals

This paper tests the robustness of rubrics generated by language models as reward signals in reinforcement learning, finding that even generic rubrics can be exploited 64% of the time, while tailored rubrics can be used to create fake answers. Practitioners should care because this can lead to biased grading and evaluation.

language models rubric-based reinforcement learning adversarial examples evaluation benchmarks

14 SEP 2026 · Paper

Pick Your Poison: Learning to Select Poison Sets for Stronger LLM Backdoor Attacks

This paper helps developers make stronger backdoor attacks on large language models by learning to select the most effective set of poisoned examples. Practitioners might care about this because it can be used to improve the security of these models in real-world applications.

backdoor attacks continual learning language models poisoning attacks adversarial examples