Methods for improving knowledge use in large language models typically fall into two regimes. Non-parametric retrieval offers flexible access to external knowledge, but adds retrieval latency, context overhead, and only shallow integration with the backbone. Parametric adaptation is efficient at inference time, but ent...
Ming-Yuan Li, Guang-Sheng Yu, Xu Wang et al.· 3 citations
Traffic Signal Control (TSC) is a safety-critical cyber-physical system that relies on real-time sensing. Corrupted observations caused by adversarial perturbations or sensor failures can propagate from the sensing layer into the controller and degrade traffic efficiency. Existing robust Reinforcement Learning (RL)-bas...
Ming-Yuan Li, Chun-Yu Liu, Xiao Liu et al.· 0 citations
Generalized least squares (GLS) analysis shows that, under exchangeability, the optimal symmetric linear combiner of latent embeddings is uniform, supporting majority vote as the natural default in standard SC while leaving room for weighting or pruning under heterogeneous prompt-template branches.
Guang-Sheng Yu, Litianyi Zhang, Qin Wang et al.· 0 citations
A residual-stream covert-channel attack is introduced that maps messages to codewords and injects them into an intermediate residual stream through a compromised runtime hook and is scaled with the local residual norm using the signal-to-residual-norm ratio.
Ming-Yuan Li, Yan-Na Jiang, Guang-Sheng Yu et al.· 0 citations
The results support generated memory as a selective correction to direct retrieval and highlight routing when, which, and how strongly to intervene as the central challenge.
Ming-Yuan Li, Guang-Sheng Yu, Ju-Yuan Zhang et al.· 0 citations
A label-free bias-only TTRL, which uses majority-vote pseudolabels as rewards and optimizes only ~100K bias parameters while keeping the pretrained backbone frozen, demonstrating that substantial test-time adaptation can emerge from optimizing a tiny bias-only subspace using entirely label-free rewards.
The results suggest that Engram can serve as a reusable external knowledge artifact, provided that the target has access to a compatible reader interface and target-side adaptation can further improve alignment when direct reader reuse is insufficient.
Mingyuan Li, Guangsheng Yu, Xu Wang et al.· 0 citations
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