Understanding the social intelligence of large language models (LLMs) is increasingly important for applications involving human-AI interaction and multi-agent environments. Social intelligence comprises two aspects: cognitive intelligence, the ability to infer others'mental states, and behavioral intelligence, the abi...
Alieh Zamani, Soroush Esfahanian, Erfan Shahabi et al.· 0 citations
Conversational Recommender Systems (CRSs) require reliable user simulators for cost-effective evaluation. LLM-based simulators have made realistic simulation possible but typically condition on profiles derived from explicit ratings, demographics, and static sources capturing surface preferences while omitting implicit...
Erfan Shahabi, Amirhossein Roshandel, Mohammad Sadegh Sadeghi et al.· 0 citations
Across most tasks, text-only baselines outperform their audio counterparts, so audio understanding rather than language knowledge remains the main limitation, and supplying the transcript alongside the audio lifts weak models to near their text-only level.
Mohammad Javad Ranjbar Kalahroodi, M. Amini, Parmis Bathayan et al.· arXiv.org· 2 citations
ParsVoice is introduced, the largest publicly available Persian speech-text corpus tailored for training multi-speaker TTS systems, along with a scalable pipeline to construct high-quality speech-text data from long-form audiobook recordings, supporting reproducible research on Persian speech synthesis and low-resource...
