most citedWord Sense Induction with Knowledge Distillation from BERT

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

DocTalkBN: A Novel Dataset of Expert Telemedicine Conversations in Bengali

Anik Saha, Fahmida Sultana Naznin, Sadatul Islam Sadi +3

Reliable medical conversational AI requires authentic expert--patient interaction data, yet such datasets remain scarce, especially for low-resource languages such as Bengali. We p…

cs.CL2026

CBRS: Cognitive Blood Request System with Bilingual Dataset and Dual-Layer Filtering for Multi-Platform Social Streams

Anik Saha, Mst. Fahmida Sultana Naznin, Zia Ul Hassan Abdullah +3

Urgent blood donation seeking posts and messages on social media often go unnoticed due to the overwhelming volume of daily communications. Traditional app-based systems, reliant o…

cs.SD2026

Bengali-Loop: Community Benchmarks for Long-Form Bangla ASR and Speaker Diarization

H. M. Shadman Tabib, Istiak Ahmmed Rifti, Abdullah Muhammed Amimul Ehsan +24

Bengali (Bangla) remains under-resourced in long-form speech technology despite its wide use. We present Bengali-Loop, two community benchmarks to address this gap: (1) a long-form…

cs.IR2023

Improving Neural Ranking Models with Traditional IR Methods

Anik Saha, Oktie Hassanzadeh, Alex Gittens +3

Neural ranking methods based on large transformer models have recently gained significant attention in the information retrieval community, and have been adopted by major commercia…

cs.CL2023

A Cross-Domain Evaluation of Approaches for Causal Knowledge Extraction

Anik Saha, Oktie Hassanzadeh, Alex Gittens +3

Causal knowledge extraction is the task of extracting relevant causes and effects from text by detecting the causal relation. Although this task is important for language understan…

cs.CL2023★ 1 cited

Word Sense Induction with Knowledge Distillation from BERT

Anik Saha, Alex Gittens, Bulent Yener

Pre-trained contextual language models are ubiquitously employed for language understanding tasks, but are unsuitable for resource-constrained systems. Noncontextual word embedding…