DIRECT uses a three-level multi-agent framework to solve video mashup creation as a multimodal coherency problem, outperforming baselines on a new benchmark.
Advanced Smart Contract Vulnerability Detection via LLM-Powered Multi-Agent Systems
4 Pith papers cite this work, alongside 8 external citations. Polarity classification is still indexing.
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Veritas detects memory corruption vulnerabilities in stripped binaries by combining static value-flow slicing, dual-view LLM reasoning, and multi-agent runtime validation, reporting 90% recall, zero false positives on 623 exhaustive cases, and discovery of a real Apple CVE.
AgentGR uses semantic-aware LLM agents to simulate group decision dynamics and improve group recommendation accuracy over traditional aggregation methods.
MGA is a memory-driven GUI agent that uses an observer for bias-free screen reading and structured memory for compact state transitions to enable efficient long-horizon automation.
citing papers explorer
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DIRECT: Video Mashup Creation via Hierarchical Multi-Agent Planning and Intent-Guided Editing
DIRECT uses a three-level multi-agent framework to solve video mashup creation as a multimodal coherency problem, outperforming baselines on a new benchmark.
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Veritas: A Semantically Grounded Agentic Framework for Memory Corruption Vulnerability Detection in Binaries
Veritas detects memory corruption vulnerabilities in stripped binaries by combining static value-flow slicing, dual-view LLM reasoning, and multi-agent runtime validation, reporting 90% recall, zero false positives on 623 exhaustive cases, and discovery of a real Apple CVE.
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AgentGR: Semantic-aware Agentic Group Decision-Making Simulator for Group Recommendation
AgentGR uses semantic-aware LLM agents to simulate group decision dynamics and improve group recommendation accuracy over traditional aggregation methods.
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MGA: Memory-Driven GUI Agent for Observation-Centric Interaction
MGA is a memory-driven GUI agent that uses an observer for bias-free screen reading and structured memory for compact state transitions to enable efficient long-horizon automation.