Papers by Yudai Yamazaki
When Instructions Multiply: Measuring and Estimating LLM Capabilities of Multiple Instructions Following (2025.findings-emnlp)
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Keno Harada, Yudai Yamazaki, Masachika Taniguchi, Edison Marrese-Taylor, Takeshi Kojima, Yusuke Iwasawa, Yutaka Matsuo
| Challenge: | a large number of languages are increasingly used to evaluate their ability to follow multiple instructions simultaneously. |
| Approach: | They propose two benchmarks to evaluate LLMs' ability to follow multiple instructions simultaneously . they use many instruction-following eval and style-aware Mostly Basic programming problems . |
| Outcome: | The proposed models predict performance on unseen instruction combinations and not used during training with 10% error. |
Zero-shot Persuasive Chatbots with LLM-Generated Strategies and Information Retrieval (2024.findings-emnlp)
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Kazuaki Furumai, Roberto Legaspi, Julio Romero, Yudai Yamazaki, Yasutaka Nishimura, Sina Semnani, Kazushi Ikeda, Weiyan Shi, Monica Lam
| Challenge: | Existing methods to improve persuasive chatbots use only a handful of predefined strategies. |
| Approach: | They propose a persuasive chatbot based on large language models that is factual and more persuasive by leveraging many more nuanced strategies. |
| Outcome: | The proposed chatbot is factual and more persuasive by leveraging many more nuanced strategies. |