6 papers
Herculean: An Agentic Benchmark for Financial Intelligence
Xueqing Peng, Zhuohan Xie, Yupeng Cao +60
As AI agents improve, the central question is no longer whether they can solve isolated well-defined financial tasks, but whether they can reliably carry out financial professional…
Concordia: Self-Improving Synthetic Tables for Federated LLMs
Jimin Huang, Duanyu Feng, Nuo Chen +8
Federated learning (FL) enables training large language models (LLMs) without sharing raw data, but adapting LLMs under strict data isolation and non-IID client distributions remai…
EmoMM: Benchmarking and Steering MLLM for Multimodal Emotion Recognition under Conflict and Missingness
Yueru Sun, Yimeng Zhang, Haoyu Gu +5
Multimodal Emotion Recognition (MER) is critical for interpreting real-world interactions. While Multimodal Large Language Models (MLLM) have shown promise in MER, their internal d…
MELLA: Bridging Linguistic Capability and Cultural Groundedness for Low-Resource Language MLLMs
Yufei Gao, Jiaying Fei, Nuo Chen +4
Multimodal Large Language Models (MLLMs) perform strongly in high-resource languages, yet often produce fluent but culturally "thin" descriptions in low-resource settings. We argue…
Is Your LLM Outdated? A Deep Look at Temporal Generalization
Chenghao Zhu, Nuo Chen, Yufei Gao +3
The rapid advancement of Large Language Models (LLMs) has led to the development of benchmarks that consider temporal dynamics, however, there remains a gap in understanding how we…
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Guorui Zheng, Xidong Wang, Juhao Liang +3
Adapting medical Large Language Models to local languages can reduce barriers to accessing healthcare services, but data scarcity remains a significant challenge, particularly for…