aiBACKGROUND
JFTA-Bench: Evaluate LLM's Ability of Tracking and Analyzing Malfunctions Using
BACKGROUND
1 SIGNALFIRST DETECTED 25 March 2026
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How the story developed
25 Mar
JFTA-Bench: Evaluate LLM's Ability of Tracking and Analyzing Malfunctions Using Fault Trees
REPORT · HOW · ArXiv CS.AI
6.0
Other feeds and industry voices
30 Mar
BeSafe-Bench: Unveiling Behavioral Safety Risks of Situated Agents in Functional Environments
arXiv:2603.25747v1 Announce Type: new Abstract: The rapid evolution of Large Multimodal Models (LMMs) has enabled agents to perform complex digital and physical tasks, yet their
REPORT · WHAT · ArXiv CS.AIOPEN STORY
27 Mar
Rethinking Failure Attribution in Multi-Agent Systems: A Multi-Perspective Benchmark and Evaluation
arXiv:2603.25001v1 Announce Type: new Abstract: Failure attribution is essential for diagnosing and improving multi-agent systems (MAS), yet existing benchmarks and methods
REPORT · WHAT · ArXiv CS.AIOPEN STORY
11 Aug
TeXFix-Bench: An Empirically Grounded Multi-Format Benchmark for LLM-Based Document Source Repair
arXiv:2608.07617v1 Announce Type: new Abstract: Scientific and technical writing depends on markup sources that must compile: LaTeX, Typst, and Markdown pipelines fail on missing
REPORT · WHAT · ArXiv CS.AIOPEN STORY
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