4 citations · 5 across the 3 of their papers we have counts for
4 papers
Greedy-Gnorm: A Gradient Matrix Norm-Based Alternative to Attention Entropy for Head Pruning
Yuxi Guo, Paul Sheridan
Attention head pruning has emerged as an effective technique for transformer model compression, an increasingly important goal in the era of Green AI. However, existing pruning met…
A Fisher's exact test justification of the TF-IDF term-weighting scheme
Paul Sheridan, Zeyad Ahmed, Aitazaz A. Farooque
Term frequency-inverse document frequency, or TF-IDF for short, is arguably the most celebrated mathematical expression in the history of information retrieval. Conceived as a simp…
Heaps' Law in GPT-Neo Large Language Model Emulated Corpora
Uyen Lai, Gurjit S. Randhawa, Paul Sheridan
Heaps' law is an empirical relation in text analysis that predicts vocabulary growth as a function of corpus size. While this law has been validated in diverse human-authored text…
A statistical significance testing approach for measuring term burstiness with applications to domain-specific terminology extraction
Samuel Sarria Hurtado, Todd Mullen, Taku Onodera +1
A term in a corpus is said to be ``bursty'' (or overdispersed) when its occurrences are concentrated in few out of many documents. In this paper, we propose Residual Inverse Collec…