1 citations · 1 across the 4 of their papers we have counts for
4 papers
Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability
Alicia Parrish, Rajat Shinde, Sanket Badhe +57
Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional laws, socio-linguistic nuances,…
SongFormer: Scaling Music Structure Analysis with Heterogeneous Supervision
Chunbo Hao, Ruibin Yuan, Jixun Yao +5
Music structure analysis (MSA) underpins music understanding and controllable generation, yet progress has been limited by small, inconsistent corpora. We present SongFormer, a sca…
MMMT-IF: A Challenging Multimodal Multi-Turn Instruction Following Benchmark
Elliot L. Epstein, Kaisheng Yao, Jing Li +2
Evaluating instruction following capabilities for multimodal, multi-turn dialogue is challenging. With potentially multiple instructions in the input model context, the task is tim…
Faithful Persona-based Conversational Dataset Generation with Large Language Models
Pegah Jandaghi, XiangHai Sheng, Xinyi Bai +2
High-quality conversational datasets are essential for developing AI models that can communicate with users. One way to foster deeper interactions between a chatbot and its user is…