@inproceedings{koki-etal-2026-interviewarena,
title = "{I}nterview{A}rena: Estimating Uninformative Participants through Interactive Dialogue under Incomplete Information",
author = "Koki, Raika and
Karasawa, Karina and
Kanayama, Ryoki and
Suzumura, Yuki and
Fujita, Haruto and
Obara, Ryoma and
Sakai, Yusuke and
Kamigaito, Hidetaka and
Hayashi, Katsuhiko and
Matsuno, Shogo",
editor = "Suglia, Alessandro and
Giulianelli, Mario and
Schlangen, David and
Bernardi, Raffaella and
Fern{\'a}ndez, Raquel and
Hakimov, Sherzod and
McCallum, Sabrina and
Mazzaccara, Davide and
Le, Dieu-Thu and
Lemon, Oliver and
Koller, Alexander",
booktitle = "The Proceedings of Improving Language Models through Learning from Dialogue Game Interaction",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.lmplayschool-1.5/",
pages = "49--56",
ISBN = "979-8-89176-467-5",
abstract = "We introduce InterviewArena, an interview-style multi-agent framework for evaluating large language models (LLMs) under incomplete information. By treating missing information as a single factor, we disentangle missing-information identification from dialogue-based reasoning. Experimental results show that while LLMs can capture relative differences between participants, predicting specific missing information remains unstable, highlighting the need to evaluate these capabilities separately."
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%0 Conference Proceedings
%T InterviewArena: Estimating Uninformative Participants through Interactive Dialogue under Incomplete Information
%A Koki, Raika
%A Karasawa, Karina
%A Kanayama, Ryoki
%A Suzumura, Yuki
%A Fujita, Haruto
%A Obara, Ryoma
%A Sakai, Yusuke
%A Kamigaito, Hidetaka
%A Hayashi, Katsuhiko
%A Matsuno, Shogo
%Y Suglia, Alessandro
%Y Giulianelli, Mario
%Y Schlangen, David
%Y Bernardi, Raffaella
%Y Fernández, Raquel
%Y Hakimov, Sherzod
%Y McCallum, Sabrina
%Y Mazzaccara, Davide
%Y Le, Dieu-Thu
%Y Lemon, Oliver
%Y Koller, Alexander
%S The Proceedings of Improving Language Models through Learning from Dialogue Game Interaction
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-467-5
%F koki-etal-2026-interviewarena
%X We introduce InterviewArena, an interview-style multi-agent framework for evaluating large language models (LLMs) under incomplete information. By treating missing information as a single factor, we disentangle missing-information identification from dialogue-based reasoning. Experimental results show that while LLMs can capture relative differences between participants, predicting specific missing information remains unstable, highlighting the need to evaluate these capabilities separately.
%U https://aclanthology.org/2026.lmplayschool-1.5/
%P 49-56
Markdown (Informal)
[InterviewArena: Estimating Uninformative Participants through Interactive Dialogue under Incomplete Information](https://aclanthology.org/2026.lmplayschool-1.5/) (Koki et al., LM Playschool 2026)
ACL
- Raika Koki, Karina Karasawa, Ryoki Kanayama, Yuki Suzumura, Haruto Fujita, Ryoma Obara, Yusuke Sakai, Hidetaka Kamigaito, Katsuhiko Hayashi, and Shogo Matsuno. 2026. InterviewArena: Estimating Uninformative Participants through Interactive Dialogue under Incomplete Information. In The Proceedings of Improving Language Models through Learning from Dialogue Game Interaction, pages 49–56, Budapest, Hungary. Association for Computational Linguistics.