FuzzAgent deploys specialized agents that collaborate on harness generation, execution, and crash triage to evolve fuzzing campaigns, delivering 45-191% more branch coverage than four baselines on 20 C/C++ libraries and surfacing 102 real bugs.
Cottontail: Large Language Model-Driven Concolic Execution for Highly Structured Test Input Generation
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Semia synthesizes Datalog representations of agent skills via constraint-guided loops to enable reachability queries for semantic risks, finding critical issues in over half of 13,728 real skills with 97.7% recall on expert-labeled samples.
GPIR achieves up to 297 times higher throughput than prior GPU PIR systems by fusing operations in stages and using pipelined transposed layouts to cut DRAM traffic during batched lattice-based queries.
citing papers explorer
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FuzzAgent: Multi-Agent System for Evolutionary Library Fuzzing
FuzzAgent deploys specialized agents that collaborate on harness generation, execution, and crash triage to evolve fuzzing campaigns, delivering 45-191% more branch coverage than four baselines on 20 C/C++ libraries and surfacing 102 real bugs.
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Semia: Auditing Agent Skills via Constraint-Guided Representation Synthesis
Semia synthesizes Datalog representations of agent skills via constraint-guided loops to enable reachability queries for semantic risks, finding critical issues in over half of 13,728 real skills with 97.7% recall on expert-labeled samples.
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GPIR: Enabling Practical Private Information Retrieval with GPUs
GPIR achieves up to 297 times higher throughput than prior GPU PIR systems by fusing operations in stages and using pipelined transposed layouts to cut DRAM traffic during batched lattice-based queries.