163 citations · 190 across the 8 of their papers we have counts for
8 papers
Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
Microsoft, :, Abdelrahman Abouelenin +73
We introduce Phi-4-Mini and Phi-4-Multimodal, compact yet highly capable language and multimodal models. Phi-4-Mini is a 3.8-billion-parameter language model trained on high-qualit…
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Marah Abdin, Jyoti Aneja, Hany Awadalla +126
We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal test…
SciAgent: Tool-augmented Language Models for Scientific Reasoning
Yubo Ma, Zhibin Gou, Junheng Hao +8
Scientific reasoning poses an excessive challenge for even the most advanced Large Language Models (LLMs). To make this task more practical and solvable for LLMs, we introduce a ne…
Language Models can be Logical Solvers
Jiazhan Feng, Ruochen Xu, Junheng Hao +4
Logical reasoning is a fundamental aspect of human intelligence and a key component of tasks like problem-solving and decision-making. Recent advancements have enabled Large Langua…
A Mobility-Aware Deep Learning Model for Long-Term COVID-19 Pandemic Prediction and Policy Impact Analysis
Danfeng Guo, Zijie Huang, Junheng Hao +3
Pandemic(epidemic) modeling, aiming at disease spreading analysis, has always been a popular research topic especially following the outbreak of COVID-19 in 2019. Some representati…
Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification
Yu Zhang, Zhihong Shen, Chieh-Han Wu +5
Large-scale multi-label text classification (LMTC) aims to associate a document with its relevant labels from a large candidate set. Most existing LMTC approaches rely on massive h…
Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts
Junheng Hao, Muhao Chen, Wenchao Yu +2
Many large-scale knowledge bases simultaneously represent two views of knowledge graphs (KGs): an ontology view for abstract and commonsense concepts, and an instance view for spec…
Bio-JOIE: Joint Representation Learning of Biological Knowledge Bases
Junheng Hao, Chelsea Ju, Muhao Chen +3
The widespread of Coronavirus has led to a worldwide pandemic with a high mortality rate. Currently, the knowledge accumulated from different studies about this virus is very limit…