SMAC-Talk is a new benchmark that adds natural language messaging and deceptive-agent scenarios to SMAC for testing LLM coordination in multi-agent environments.
Llm-hanabi: Evaluating multi- agent gameplays with theory-of-mind and rationale inference in imperfect information collaboration game
3 Pith papers cite this work. Polarity classification is still indexing.
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SciLens introduces an evidence-conditioned atomic entailment framework that grounds claims to modality-specific witnesses in tables and figures, achieving 79.2% macro-F1 on SciClaimEval.
The paper organizes research on generalist game AI into Dataset, Model, Harness, and Benchmark pillars and charts a five-level progression from single-game mastery to agents that create and live inside game multiverses.
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SciLens: Multi-modal Scientific Claim Verification with Agentic Entailment and Grounding
SciLens introduces an evidence-conditioned atomic entailment framework that grounds claims to modality-specific witnesses in tables and figures, achieving 79.2% macro-F1 on SciClaimEval.