SMI replaces MIA-based unlearned model auditing with training-free statistical estimation of non-member mixture proportions in feature space, yielding reliable forgetting rates and bootstrap reliability ranges.
SMoA modulates spectra via block-diagonal Hadamard low-rank branches to expand representational coverage under small parameter budgets, outperforming LoRA on multiple tasks.
A game-theoretic framework predicts and steers LLM populations via Nash equilibrium analysis, deriving closed-form alignments that prevent political exclusion and guide socially desirable outcomes.
PRO closes the indexing-decoding gap in multimodal generative retrieval via prefix ranking distillation, vocabulary scheduling, and geometric score fusion to improve beam search retention and retrieval accuracy.
EcoGym benchmarks long-horizon LLM economic planning across open-source environments, revealing no single model dominates and exposing strategic and execution suboptimalities.
ChunkFT enables memory-efficient full-parameter fine-tuning via dynamically activated sub-tensors, cutting 7B model memory to 13.72GB and outperforming baselines.