3 citations · 3 across the 4 of their papers we have counts for
3 papers · 1 filter
REALM: Reliable Expertise-Aware Language Model Fine-Tuning from Noisy Annotations
Sajjad Ghiasvand, Mark Beliaev, Mahnoosh Alizadeh +1
Supervised fine-tuning of large language models relies on human-annotated data, yet annotation pipelines routinely involve multiple crowdworkers of heterogeneous expertise. Standar…
Inverse Reinforcement Learning by Estimating Expertise of Demonstrators
Mark Beliaev, Ramtin Pedarsani
In Imitation Learning (IL), utilizing suboptimal and heterogeneous demonstrations presents a substantial challenge due to the varied nature of real-world data. However, standard IL…
Efficient and Robust Classification for Sparse Attacks
Mark Beliaev, Payam Delgosha, Hamed Hassani +1
In the past two decades we have seen the popularity of neural networks increase in conjunction with their classification accuracy. Parallel to this, we have also witnessed how frag…