EigenData: A Self-Evolving Multi-Agent Platform for Function-Calling Data Synthesis, Auditing, and Repair
2026-03-09T08:51:50Z•a45493a8a2ed52d891a728de64c9b39e33faa5fff7220f1e8b4b631681812ce3
API-differential-testingAPIDifferEthereumMCP-faultsModel-Context-ProtocolXAIagent-debuggingautomated-test-generationbenchmarkingblockchain-securityevaluation-metricsexecution-tracesfunction-calling-agentslarge-language-modelsnative-crashespython-c-extensionsself-evolving-agentssoftware-reliabilitysubprocess-isolationtool-synthesis
What happened
This batch of CS papers highlights growing reliability and security risks from tightly integrating foundation models with executable environments, developer tools, and blockchain infrastructure. Key findings: (1) EigenData offers an automated multi-agent pipeline for generating, auditing, and repairing function-calling training artifacts and repaired the BFCL-V3 benchmark with outcome-aware (database-state) metrics; (2) Tool-Genesis shows that autonomous tool synthesis from abstract requirements often produces subtle interface and logic errors that amplify downstream failures; (3) a large MCP(
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_se
- Record identifier
- a45493a8a2ed52d891a728de64c9b39e33faa5fff7220f1e8b4b631681812ce3
- Enrichment time
- 2026-03-09T08:51:50Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.