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This work proposes Targeted Anti-obfuscation with Mechanistic Enforcement (TAME), which uses Sparse Autoencoders (SAEs) to combine behavioral feedback with targeted suppression of template-associated activations during RL, providing a path from behavioral monitoring to representation-level oversight for more auditable...
DRNOISE, a 100-task benchmark for answer recovery under misleading evidence, is introduced, a 100-task benchmark for answer recovery under misleading evidence that requires active reconciliation of direct claims with record-level evidence.
SmartNIC-based in-network prediction is a practical complement to partitioning and compression techniques for communicationefficient full-graph GNN training at scale, and results indicate SmartNIC-based in-network prediction is a practical complement to partitioning and compression techniques for communicationefficient...
BiDiRL, a hybrid time-space multiplexing architecture for asynchronous, disaggregated RL designed to reduce resource idleness, is presented, including a hot-switch runtime that enables rapid switching between rollout and training resources with negligible overhead and a static, scheduling-aware planner based on time-pe...
Xema is presented, a memory-efficient diffusion serving system that exploits predictable tensor lifetimes for trace-guided memory optimization and introduces an offline planner that jointly selects parallelism, concurrency, and memory control under GPU memory and SLO constraints.
KernelFlume is presented, a decode-centric architecture that disaggregates the stable projection/FFN path from core-attention computation: weight nodes execute dense projection/FFN kernels, while weightless attention nodes store token-range KV partitions and scale with request-state demand.
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