1.5k citations · 3k across the 43 of their papers we have counts for
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Post-Training Language Models for Gold-Medal Performance in Coding Competitions
Aleksander Ficek, Sean Narenthiran, Mehrzad Samadi +2
Competitive programming has become a key test of large language model reasoning, with international competitions such as IOI and ICPC representing its most challenging settings. We…
Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
NVIDIA, :, Aakshita Chandiramani +544
We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…
Learning Generative Selection for Best-of-N
Shubham Toshniwal, Aleksander Ficek, Siddhartha Jain +5
Scaling test-time compute via parallel sampling can substantially improve LLM reasoning, but is often limited by Best-of-N selection quality. Generative selection methods, such as…
Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models
Mehrzad Samadi, Aleksander Ficek, Sean Narenthiran +5
Competitive programming has become a rigorous benchmark for evaluating the reasoning and problem-solving capabilities of large language models (LLMs). The International Olympiad in…
A Study on Regularization-Based Continual Learning Methods for Indic ASR
Gokul Adethya T, S. Jaya Nirmala
Indias linguistic diversity poses significant challenges for developing inclusive Automatic Speech Recognition (ASR) systems. Traditional multilingual models, which require simulta…
Adversarial Attacks on Time Series
Fazle Karim, Somshubra Majumdar, Houshang Darabi
Time series classification models have been garnering significant importance in the research community. However, not much research has been done on generating adversarial samples f…
Insights into LSTM Fully Convolutional Networks for Time Series Classification
Fazle Karim, Somshubra Majumdar, Houshang Darabi
Long Short Term Memory Fully Convolutional Neural Networks (LSTM-FCN) and Attention LSTM-FCN (ALSTM-FCN) have shown to achieve state-of-the-art performance on the task of classifyi…
Multivariate LSTM-FCNs for Time Series Classification
Fazle Karim, Somshubra Majumdar, Houshang Darabi +1
Over the past decade, multivariate time series classification has received great attention. We propose transforming the existing univariate time series classification models, the L…
LSTM Fully Convolutional Networks for Time Series Classification
Fazle Karim, Somshubra Majumdar, Houshang Darabi +1
Fully convolutional neural networks (FCN) have been shown to achieve state-of-the-art performance on the task of classifying time series sequences. We propose the augmentation of f…