作者位次 #2/5ACL 2026Poster· Natural Language Processing
E mo S : A High-Fidelity Multimodal Benchmark for Fine-grained Streaming Emotional Understanding
Pengze Guo · Jingxi Liang · Zhiwen Xie · Qifeng Wang · Derek F. Wong
摘要
In the context of today’s high-pressure, aging society, the demand for large-scale emotional models capable of providing empathetic support is more critical than ever. However, existing benchmarks fail to simultaneously achieve ecological validity, signal clarity, and reliable fine-grained labeli...