7 citations · 24 across the 13 of their papers we have counts for
13 papers
From Passive Delegates to Strategic Negotiators: Reinforcing Social Reasoning in Small Language Models with SocialRL
Wenyue Hua, Zachary Huang, Tyler Payne +3
AI agents increasingly act on their users' behalf, handling tasks such as scheduling meetings, comparing offers, and haggling over prices. These principal-driven tasks routinely pl…
Tracing the Traces: Latent Temporal Signals for Efficient and Accurate Reasoning
Martina G. Vilas, Safoora Yousefi, Besmira Nushi +2
Reasoning models improve their problem-solving ability through inference-time scaling, allocating more compute via longer token budgets. Identifying which reasoning traces are like…
Phi-4-reasoning Technical Report
Marah Abdin, Sahaj Agarwal, Ahmed Awadallah +20
We introduce Phi-4-reasoning, a 14-billion parameter reasoning model that achieves strong performance on complex reasoning tasks. Trained via supervised fine-tuning of Phi-4 on car…
Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead
Vidhisha Balachandran, Jingya Chen, Lingjiao Chen +8
Inference-time scaling can enhance the reasoning capabilities of large language models (LLMs) on complex problems that benefit from step-by-step problem solving. Although lengtheni…
Unearthing Skill-Level Insights for Understanding Trade-Offs of Foundation Models
Mazda Moayeri, Vidhisha Balachandran, Varun Chandrasekaran +6
With models getting stronger, evaluations have grown more complex, testing multiple skills in one benchmark and even in the same instance at once. However, skill-wise performance i…
Improving Instruction-Following in Language Models through Activation Steering
Alessandro Stolfo, Vidhisha Balachandran, Safoora Yousefi +2
The ability to follow instructions is crucial for numerous real-world applications of language models. In pursuit of deeper insights and more powerful capabilities, we derive instr…
Eureka: Evaluating and Understanding Large Foundation Models
Vidhisha Balachandran, Jingya Chen, Neel Joshi +6
Rigorous and reproducible evaluation is critical for assessing the state of the art and for guiding scientific advances in Artificial Intelligence. Evaluation is challenging in pra…
Decoding In-Context Learning: Neuroscience-inspired Analysis of Representations in Large Language Models
Safoora Yousefi, Leo Betthauser, Hosein Hasanbeig +2
Large language models (LLMs) exhibit remarkable performance improvement through in-context learning (ICL) by leveraging task-specific examples in the input. However, the mechanisms…
Streaming Active Learning with Deep Neural Networks
Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy +2
Active learning is perhaps most naturally posed as an online learning problem. However, prior active learning approaches with deep neural networks assume offline access to the enti…
Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting
Chen Lin, Safoora Yousefi, Elvis Kahoro +4
Real-time air pollution monitoring is a valuable tool for public health and environmental surveillance. In recent years, there has been a dramatic increase in air pollution forecas…
Learning Clinical Outcomes from Heterogeneous Genomic Data Sources
Safoora Yousefi, Amirreza Shaban, Mohamed Amgad +2
Translating the vast data generated by genomic platforms into reliable predictions of clinical outcomes remains a critical challenge in realizing the promise of genomic medicine la…
Learning Genomic Representations to Predict Clinical Outcomes in Cancer
Safoora Yousefi, Congzheng Song, Nelson Nauata +1
Genomics are rapidly transforming medical practice and basic biomedical research, providing insights into disease mechanisms and improving therapeutic strategies, particularly in c…
A Continuous-time Mutually-Exciting Point Process Framework for Prioritizing Events in Social Media
Mehrdad Farajtabar, Safoora Yousefi, Long Q. Tran +2
The overwhelming amount and rate of information update in online social media is making it increasingly difficult for users to allocate their attention to their topics of interest,…