6 citations · 9 across the 7 of their papers we have counts for
9 papers
What "Form'' of Uncertainty Does Conformal Prediction Quantify?
Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Rebekka Burkholz +1
Conformal prediction (CP) is a post-hoc calibration method that returns prediction sets with distribution-free coverage guarantees, and the size of the output set is often interpre…
Reward-Gated On-Policy Distillation
Mohammad Sadegh Akhondzadeh, Vijay Lingam, Atula Tejaswi +3
On-policy distillation is a powerful way to transfer reasoning ability from a strong teacher to a smaller student: the student samples trajectories from its own policy, and the tea…
EvA: Evolutionary Attacks on Graphs
Mohammad Sadegh Akhondzadeh, Soroush H. Zargarbashi, Jimin Cao +1
Even a slight perturbation in the graph structure can cause a significant drop in the accuracy of graph neural networks (GNNs). Most existing attacks leverage gradient information…
One Sample is Enough to Make Conformal Prediction Robust
Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
For any black-box model, conformal prediction (CP) returns prediction sets guaranteed to include the true label with high adjustable probability. Robust CP (RCP) extends the guaran…
KurTail : Kurtosis-based LLM Quantization
Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski, Evangelos Eleftheriou +1
One of the challenges of quantizing a large language model (LLM) is the presence of outliers. Outliers often make uniform quantization schemes less effective, particularly in extre…
Robust Yet Efficient Conformal Prediction Sets
Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
Conformal prediction (CP) can convert any model's output into prediction sets guaranteed to include the true label with any user-specified probability. However, same as the model i…
Probing Graph Representations
Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski
Today we have a good theoretical understanding of the representational power of Graph Neural Networks (GNNs). For example, their limitations have been characterized in relation to…
Evaluating Sparse Interpretable Word Embeddings for Biomedical Domain
Mohammad Amin Samadi, Mohammad Sadegh Akhondzadeh, Sayed Jalal Zahabi +3
Word embeddings have found their way into a wide range of natural language processing tasks including those in the biomedical domain. While these vector representations successfull…
Wide-AdGraph: Detecting Ad Trackers with a Wide Dependency Chain Graph
Amir Hossein Kargaran, Mohammad Sadegh Akhondzadeh, Mohammad Reza Heidarpour +3
Websites use third-party ads and tracking services to deliver targeted ads and collect information about users that visit them. These services put users' privacy at risk, and that…