This study describes GPU-fabric contention in LLM workloads and presents GPUWeaver, a context-aware communication scheduler that monitors application progress and fabric state, identifies contention, and dynamically regulates communication injection according to application performance goals.
Dan-Yang Chen, Yu-Feng Gu, Yi-Bo Huang et al.· Proceedings of the 17th ACM...· 2 citations
Retrieval-augmented generation (RAG) grounds large language models in external sources, but retrieved passages often name the right entities without providing the facts needed to answer. Even when instructed to abstain, 12 generators answer 40.0-99.3% of insufficient-evidence questions. Training generators to abstain t...
This work proposes a controlled inject-and-remove cycle: deliberately inject a weaker backdoor and then unlearn it, which weakens detector-visible signatures and fools the backdoor detectors with an illusion of purification while preserving the malicious retrieval behavior.
This work proposes Semantics Delivery Network (SemDN): an origin-authorized, hierarchical edge substrate that indexes, searches, and smart-caches web content at chunk granularity, and serves agents on behalf of participating websites, amortizes data acquisition and processing across agents, and supports tenant-specific...
This work introduces Matryoshka Hash Representations (MHR), a two-stage procedure that separates full-width training from prefix organization and strengthens two common pipelines: shortlisting candidates for full-precision reranking, and pruning a low-storage graph index such as LEANN.
SkillClone is introduced, a black-box attack that clones a target skill by forming an interface hypothesis from its public advertisement, issuing structured benign probes, synthesizing an executable replica, and iteratively repairing it through differential validation against the victim skill.
This shortlist short-circuits full-corpus cryptographic search without sacrificing retrieval quality: with 200-500 candidates, it closely matches full-corpus retrieval across five zero-shot corpora spanning 25K to 5.4M documents.
Pei-Chun Hua, Dan-Yang Chen, Ju-Nan Zhang et al.· 2 citations
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