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cs.LG2026
Co-Evolving LLM Evaluators and Policies via DynamicRubric
Beining Wang, Weihang Su, Hongtao Tian +8
Post-training with evaluator feedback on policy-induced samples serves as a major mechanism for improving large language models. As policies improve, these sampled responses become…
cs.LG2025
MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems
Qingyao Ai, Yichen Tang, Changyue Wang +3
Scaling up data, parameters, and test-time computation has been the mainstream methods to improve LLM systems (LLMsys), but their upper bounds are almost reached due to the gradual…