Voice agents are moving beyond rigid turn based systems toward real time, natural conversation, streaming understanding and generation simultaneously. However, most existing benchmarks are either turn-based or latency-focused and do not directly test whether models can maintain reasoning when users interrupt or update objectives mid-utterance.
In our latest Applied Research, we introduce EchoChain 🔊, a novel benchmark for evaluating reasoning under pressure in full-duplex dialogue.
Key findings:
- Full-duplex models often fail to properly integrate interruption information, even so far as ignoring the interruption entirely in some cases.
- A major weakness in today’s most advanced models is that they struggle to stay consistent when new input arrives while they’re still responding.
- In many cases, a model performs well when it can respond without interruption, but struggles once it’s interrupted mid-response.
Check out the full analysis in our blog post. Stay tuned for the arXiv paper as well which will be released in the coming days.
https://t.co/GfYAstHEQ6
@HTX_Global
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HELP
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this isn't the way you people keep on extending 30 min more
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