Chronicle is the first model jointly pretrained from scratch on text and time series in a unified transformer that matches a comparable language model on NLU tasks and sets new bars for time series classification and multimodal forecasting.
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2026 3verdicts
UNVERDICTED 3representative citing papers
Cattle Trade benchmark shows heuristic code agents outperforming most LLMs in integrated strategic tasks like bidding, bluffing, and resource allocation across 242 games, with strategic coherence predicting rank better than spending volume.
In agentic AI, safety and fairness are governed by interaction topology rather than model scale or alignment.
citing papers explorer
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Chronicle: A Multimodal Foundation Model for Joint Language and Time Series Understanding
Chronicle is the first model jointly pretrained from scratch on text and time series in a unified transformer that matches a comparable language model on NLU tasks and sets new bars for time series classification and multimodal forecasting.
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Cattle Trade: A Multi-Agent Benchmark for LLM Bluffing, Bidding, and Bargaining
Cattle Trade benchmark shows heuristic code agents outperforming most LLMs in integrated strategic tasks like bidding, bluffing, and resource allocation across 242 games, with strategic coherence predicting rank better than spending volume.
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Position: Safety and Fairness in Agentic AI Depend on Interaction Topology, Not on Model Scale or Alignment
In agentic AI, safety and fairness are governed by interaction topology rather than model scale or alignment.