19 citations · 37 across the 6 of their papers we have counts for
7 papers
Legal Research Bench: Measuring End-to-End Reliability in Long-Horizon Legal Research Agents
Katrina Drozdov, Oliver Chen, Langston Nashold +1
Legal research is a core and time-consuming legal workflow. Lawyers must identify controlling authority, verify that it remains valid, reconcile statutes and cases, and synthesize…
FormalProofBench: Can Models Write Graduate Level Math Proofs That Are Formally Verified?
Nikil Ravi, Kexing Ying, Vasilii Nesterov +5
We present FormalProofBench, a private benchmark designed to evaluate whether AI models can produce formally verified mathematical proofs at the graduate level. Each task pairs a n…
Vibe Code Bench: Evaluating AI Models on End-to-End Web Application Development
Hung Tran, Langston Nashold, Rayan Krishnan +2
Code generation has emerged as one of AI's highest-impact use cases, yet existing benchmarks measure isolated tasks rather than the complete "zero-to-one" process of building a wor…
Finance Agent Benchmark: Benchmarking LLMs on Real-world Financial Research Tasks
Antoine Bigeard, Langston Nashold, Rayan Krishnan +1
Artificial Intelligence (AI) technology has emerged as a transformative force in financial analysis and the finance industry, though significant questions remain about the full cap…
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays
Emma Chen, Andy Kim, Rayan Krishnan +3
A major obstacle to the integration of deep learning models for chest x-ray interpretation into clinical settings is the lack of understanding of their failure modes. In this work,…
Using LSTM and SARIMA Models to Forecast Cluster CPU Usage
Langston Nashold, Rayan Krishnan
As large scale cloud computing centers become more popular than individual servers, predicting future resource demand need has become an important problem. Forecasting resource nee…
CheXphoto: 10,000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness
Nick A. Phillips, Pranav Rajpurkar, Mark Sabini +10
Clinical deployment of deep learning algorithms for chest x-ray interpretation requires a solution that can integrate into the vast spectrum of clinical workflows across the world.…