2 citations · 6 across the 15 of their papers we have counts for
6 papers · 1 filter
SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
Md Kowsher, Ali O. Polat, Ehsan Mohammady Ardehaly +4
This paper presents a theoretical framework explaining why fine tuning small, randomly selected subnetworks (slices) within pre trained models can be sufficient for downstream adap…
Explainable Detection of Implicit Influential Patterns in Conversations via Data Augmentation
Sina Abdidizaji, Md Kowsher, Niloofar Yousefi +1
In the era of digitalization, as individuals increasingly rely on digital platforms for communication and news consumption, various actors employ linguistic strategies to influence…
FlowNIB: An Information Bottleneck Analysis of Bidirectional vs. Unidirectional Language Models
Md Kowsher, Nusrat Jahan Prottasha, Shiyun Xu +4
Bidirectional language models have better context understanding and perform better than unidirectional models on natural language understanding tasks, yet the theoretical reasons b…
PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models
Nusrat Jahan Prottasha, Upama Roy Chowdhury, Shetu Mohanto +7
Large models such as Large Language Models (LLMs) and Vision Language Models (VLMs) have transformed artificial intelligence, powering applications in natural language processing,…
User Profile with Large Language Models: Construction, Updating, and Benchmarking
Nusrat Jahan Prottasha, Md Kowsher, Hafijur Raman +4
User profile modeling plays a key role in personalized systems, as it requires building accurate profiles and updating them with new information. In this paper, we present two high…
Predicting Through Generation: Why Generation Is Better for Prediction
Md Kowsher, Nusrat Jahan Prottasha, Prakash Bhat +6
This paper argues that generating output tokens is more effective than using pooled representations for prediction tasks because token-level generation retains more mutual informat…