10 citations · 12 across the 9 of their papers we have counts for
9 papers
MatrAIx: Simulating the World with 8.3 Billion Persona Agents
Xiaomin Li, Yuexing Hao, Jianheng Hou +90
Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…
CoMem: Context Management with A Decoupled Long-Context Model
Yuwei Zhang, Chengyu Dong, Shuowei Jin +11
Context management enables agentic models to solve long-horizon tasks through iterative summarization of previous interaction histories. However, this process typically incurs subs…
EHRBench: An Automated and Reliable EHR-based Benchmark for Clinical Decision Making with LLMs
Yuzhang Xie, Keqi Han, Yunpeng Xiao +7
Clinical decision-making (CDM) is central to real-world clinical workflows, where clinicians infer diagnoses, select treatments, or anticipate future health outcomes under incomple…
Structured Prompts Improve Evaluation of Language Models
Asad Aali, Muhammad Ahmed Mohsin, Vasiliki Bikia +15
As language models (LMs) are increasingly adopted across domains, high-quality benchmarking frameworks are essential for guiding deployment decisions. In practice, however, framewo…
MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks
Suhana Bedi, Hejie Cui, Miguel Fuentes +78
While large language models (LLMs) achieve near-perfect scores on medical licensing exams, these evaluations inadequately reflect the complexity and diversity of real-world clinica…
CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models
Wei Dai, Peilin Chen, Malinda Lu +4
Recent advances in clinical AI have enabled remarkable progress across many clinical domains. However, existing benchmarks and models are primarily limited to a small set of modali…
TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records
Hejie Cui, Alyssa Unell, Bowen Chen +4
Large language models (LLMs) have emerged as promising tools for assisting in medical tasks, yet processing Electronic Health Records (EHRs) presents unique challenges due to their…
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium
Amin Adibi, Xu Cao, Zongliang Ji +39
The fourth Machine Learning for Health (ML4H) symposium was held in person on December 15th and 16th, 2024, in the traditional, ancestral, and unceded territories of the Musqueam,…
Microstructures and Accuracy of Graph Recall by Large Language Models
Yanbang Wang, Hejie Cui, Jon Kleinberg
Graphs data is crucial for many applications, and much of it exists in the relations described in textual format. As a result, being able to accurately recall and encode a graph de…