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$\tau$-Elicitation: Benchmarking multi-turn entity extraction in voice agents

arXiv:2609.13602v1 Announce Type: new Abstract: Voice agents often need to collect names, addresses, identifiers, dates, and times exactly, yet end-to-end benchmarks obscure where capture fails. We introduce $\tau$-Elicitation, a 200-task voice benchmark spanning 10 entity types, controlled difficulty, caller realisms, and three environments. A matched text agent passes all tasks, but four voice configurations achieve robust exact success from 0.14 to 0.41. Agents increase verification for hard and unfamiliar entities and sometimes for incorrect captures, but not for their weakest caller voic

Tier 2 NotableMethodology 0.2
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+0.19

3 base · Notable (tier 2 of 5, 3 pts)
× 0.7500 attribution · Critical contribution
× 0.3000 evidence · Technical disclosure or preprint
× 0.5500 realization · Experimentally validated
× 0.5000 durability · Medium-term
Event-level product before credit split: 0.19

Ingest update: raised magnitude to tier 2; raised attribution; independent source raised evidence; raised realization; added a follow-up source. Score remains provisional until review. Follow-up ingest: independent source raised evidence; added a follow-up source.

What happened

arXiv:2609.13602v1 Announce Type: new Abstract: Voice agents often need to collect names, addresses, identifiers, dates, and times exactly, yet end-to-end benchmarks obscure where capture fails. We introduce $\tau$-Elicitation, a 200-task voice benchmark spanning 10 entity types, controlled difficulty, caller realisms, and three environments. A matched text agent passes all tasks, but four voice configurations achieve robust exact success from 0.14 to 0.41. Agents increase verification for hard and unfamiliar entities and sometimes for incorrect captures, but not for their weakest caller voice; only 24 to 37 percent of verified errors are repaired. A scaffold that prescribes spelling, read-back, correction, and confirmation raises robust Pass$^3$ by 14 to 31 points, at a cost of 21 to 28 seconds per call. Realisms such as spelling variations and restarts do not detectably affect exact success; mispronunciation increases repair effort. These results identify strategy selection and successful recovery as the central bottlenecks in exact spoken entity collection. Update (2026-09-19): Google’s Gemini hacked three companies in new AI safety incident - Financial Times. Google’s Gemini hacked three companies in new AI safety incident  Financial Times Update (2026-09-21): GameASG-Bench: Benchmarking Autonomous Software Generation for Game Development. arXiv:2609.21293v1 Announce Type: new Abstract: Autonomous software generation (ASG) aims to turn human requirements into executable applications, but delivering these applications does not necessarily establish that their interacting components satisfy the specified behavioral requirements. We introduce GameASG-Bench, a benchmark that makes behavioral testability part of the generation task for game development. Our design declares an evaluation interface specification before generation, fixing legal starting scenarios, player-level actions, stable snapshots, rejection behavior, and invariants while leaving private implementations open. Concretely, we include: (i) static L1 checks that assess source-level compliance; and (ii) browser-executed L2 checks that combine semantic observations with real input and runtime evidence. We implement this protocol as 47 browser-native game-generation tasks spanning 12 primary genres and both 2D and 3D interaction, each with executable checks and an independently verified reference implementation. Our experiments answer four key questions abo

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Attribution 0.7500 · Credit share 100% · Unknown

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  • $\tau$-Elicitation: Benchmarking multi-turn entity extraction in voice agents

    outcome · supported

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Revision history

  • 17 Sep 2026 · 0.00 → 0.00

    Auto-published from news ingest.

  • 19 Sep 2026 · 0.00 → 0.12

    Ingest update: raised magnitude to tier 2; raised attribution; independent source raised evidence; raised realization; added a follow-up source.

  • 21 Sep 2026 · 0.12 → 0.19

    Ingest update: independent source raised evidence; added a follow-up source.