TalkMatrix: Generating Character Dialogue that is Both Consistent and Diverse
Candidate-based decoding typically selects a completion for each prompt independently, but many applications require a collection of outputs that satisfies global, non-decomposable requirements. We formulate this setting as structured multi-prompt, multi-completion selection: given a candidate pool for every prompt, select one completion per prompt to optimize a collection-level objective. We instantiate the problem in character dialogue, where each character should remain consistent across situations, each line should fit its situation, and characters and situations should remain distinguishable. Our method, TalkMatrix, generates multiple candidates for every character--situation pair an...
| Authors | Ayuto Tsutsumi, Yuu Jinnai |
|---|---|
| Primary category | cs.CL |
| Published | 20 July 2026 |
| Last updated at source | 20 July 2026 |
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