5 papers
Batch-wise Adaptive Pruning: Periodic Neuron Activation-Aware Weight Pruning for Language Reasoning Model
Yongmin Kim, Shota Takashiro, Yusuke Iwasawa +2
Large Reasoning Models (LRMs) achieve strong performance on complex tasks through extended chain-of-thought generation, but incur substantial computational costs during inference.…
On the Existence of Universal Simulators of Attention
Debanjan Dutta, Anish Chakrabarty, Faizanuddin Ansari +1
Previous work on the learnability of transformers \textemdash\ focused primarily on examining their ability to approximate specific algorithmic patterns through training \textemdas…
Rebalancing with Calibrated Sub-classes (RCS): A Statistical Fusion-based Framework for Robust Imbalanced Classification across Modalities
Priyobrata Mondal, Faizanuddin Ansari, Swagatam Das
Class imbalance, where certain classes have insufficient data, poses a critical challenge for robust classification, often biasing models toward majority classes. Distribution cali…
APFEx: Adaptive Pareto Front Explorer for Intersectional Fairness
Priyobrata Mondal, Faizanuddin Ansari, Swagatam Das
Ensuring fairness in machine learning models is critical, especially when biases compound across intersecting protected attributes like race, gender, and age. While existing method…
Assessing the Limits of In-Context Learning beyond Functions using Partially Ordered Relation
Debanjan Dutta, Faizanuddin Ansari, Swagatam Das
Generating rational and generally accurate responses to tasks, often accompanied by example demonstrations, highlights Large Language Model's (LLM's) remarkable In-Context Learning…