CollabSim is a new CSCW-grounded simulation framework that enables controlled multi-agent experiments to measure collaborative competence in LLM agents.
Multi-Agent-as-Judge: Aligning LLM-Agent-Based Automated Evaluation with Multi-Dimensional Human Evaluation
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2026 5representative citing papers
Scoping review of 134 studies on LLM-as-a-Judge in healthcare finds concentration in clinical decision support and NLP, frequent use of OpenAI models with prompt engineering, and moderate-to-strong human alignment where validated.
TopOptAgents deploys six LLM agents in self-refining loops to automate the full topology optimization workflow and succeeds on problem classes where single LLMs fail.
Bayesian deep learning method rankings are unreliable under data scarcity, reversing across datasets and sample sizes, and a hierarchical Bayesian framework with predictive detectability curves is needed to assess evaluation sufficiency.
SocialGrid benchmark shows even top LLMs achieve below 60% in embodied planning and task completion, with deception detection near random chance regardless of model scale.
citing papers explorer
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CollabSim: A CSCW-Grounded Methodology for Investigating Collaborative Competence of LLM Agents through Controlled Multi-Agent Experiments
CollabSim is a new CSCW-grounded simulation framework that enables controlled multi-agent experiments to measure collaborative competence in LLM agents.
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LLM-as-a-Judge in Healthcare: A Scoping Analysis of Applications, Methods, and Human Alignment
Scoping review of 134 studies on LLM-as-a-Judge in healthcare finds concentration in clinical decision support and NLP, frequent use of OpenAI models with prompt engineering, and moderate-to-strong human alignment where validated.
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Self-Refining Topology Optimization via an LLM-Based Multi-Agent Framework
TopOptAgents deploys six LLM agents in self-refining loops to automate the full topology optimization workflow and succeeds on problem classes where single LLMs fail.
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ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation
Bayesian deep learning method rankings are unreliable under data scarcity, reversing across datasets and sample sizes, and a hierarchical Bayesian framework with predictive detectability curves is needed to assess evaluation sufficiency.
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SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systems
SocialGrid benchmark shows even top LLMs achieve below 60% in embodied planning and task completion, with deception detection near random chance regardless of model scale.