TiFF
A category of language models designed for system-level decision-making that produce decision outputs via token-by-token generation. TiFF models serve as a baseline model category in CLM comparative experiments.
Timeline (last 90 days)
CLM's decision speed is up to 13 times faster than TiFF-class models, while matching them in accuracy.
CLM is compatible with TiFF's API and offers three primitives—yes/no questions, multiple-choice questions, and scoring—unified at the underlying level as 'one state plus a closed set of candidates,' meaning it will not fabricate answers outside the list but can still pick the wrong item from the list.
In CLM experiments, the accuracy of selecting the correct tool from 8 tools was 86%, but dropped sharply to 17% when selecting from all 1,080 tools, with the main error being confusion between tools with similar names; TiFF is limited to a maximum of 255 options.
All Facts (3)
CLM's decision speed is up to 13 times faster than TiFF-class models, while matching them in accuracy.
50%UnverifiedCLM is compatible with TiFF's API and offers three primitives—yes/no questions, multiple-choice questions, and scoring—unified at the underlying level as 'one state plus a closed set of candidates,' meaning it will not fabricate answers outside the list but can still pick the wrong item from the list.
50%UnverifiedIn CLM experiments, the accuracy of selecting the correct tool from 8 tools was 86%, but dropped sharply to 17% when selecting from all 1,080 tools, with the main error being confusion between tools with similar names; TiFF is limited to a maximum of 255 options.
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