Speech-LLMs often exhibit prompt overfitting, where models solely trained on automatic speech recognition (ASR) instruction fail to generalize to new instructions such as speech translation and continue to behave primarily as ASR system. We propose DirectSpeech2LLM, a simple end-to-end framework that preserves the inst...
Hemant Yadav, Sunayana Sitaram, R. Zimmermann et al.· 0 citations
It is found that current LLM-based agents reach agreement reliably, and negotiate efficient contracts when environmental uncertainty is low, but under high uncertainty, they often fail to negotiate satisfiable, efficient, or mutually beneficial contracts.
Bhavyesh Sajja, Max Kleiman-Weiner, R. Zimmermann et al.· 0 citations
A benchmark with tab-and-blank interlocking pieces where geometric constraints provide strong local compatibility requirements that, combined with visual content, yield unambiguous ground truth is introduced, establishing scalable geometric reasoning as an open challenge for vision-language models.
FinDeepIndicator is proposed, the first benchmark dedicated to evaluating Deep Research agents in end-to-end financial indicator construction, and covers fundamental, technical, and macroeconomic indicators organized into 21 fine-grained sub-categories.
Chaoqun Yang, Fengbin Zhu, Xinyu Lin et al.· 0 citations
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