3 citations · 6 across the 9 of their papers we have counts for
10 papers
Attacking Only Half the Data: Two-Sided Evaluation of AI-Text Detector Robustness
Apu Chandraw Shill, Rabindra Nath Nandi
We investigate the robustness of widely used AI text detectors under attacks applied to both human and machine text. Prior evaluations typically attack only machine text, overlooki…
Surpassing Scale by Efficiency: A Compact 135M Parameter Foundational LLM Natively Adapted for the Bangla Language
Rabindra Nath Nandi
While the NLP landscape is dominated by multi-billion parameter architectures, their deployment in low-resource, non-Latin scripts remains computationally prohibitive for edge conf…
MENASpeechBank: A Reference Voice Bank with Persona-Conditioned Multi-Turn Conversations for AudioLLMs
Zien Sheikh Ali, Hunzalah Hassan Bhatti, Rabindra Nath Nandi +2
Audio large language models (AudioLLMs) enable instruction following over speech and general audio, but progress is limited by the scarcity of diverse, conversational, and instruct…
BnTTS: Few-Shot Speaker Adaptation in Low-Resource Setting
Mohammad Jahid Ibna Basher, Md Kowsher, Md Saiful Islam +8
This paper introduces BnTTS (Bangla Text-To-Speech), the first framework for Bangla speaker adaptation-based TTS, designed to bridge the gap in Bangla speech synthesis using minima…
TituLLMs: A Family of Bangla LLMs with Comprehensive Benchmarking
Shahriar Kabir Nahin, Rabindra Nath Nandi, Sagor Sarker +7
In this paper, we present TituLLMs, the first large pretrained Bangla LLMs, available in 1b and 3b parameter sizes. Due to computational constraints during both training and infere…
Pseudo-Labeling for Domain-Agnostic Bangla Automatic Speech Recognition
Rabindra Nath Nandi, Mehadi Hasan Menon, Tareq Al Muntasir +5
One of the major challenges for developing automatic speech recognition (ASR) for low-resource languages is the limited access to labeled data with domain-specific variations. In t…
QCRI at SemEval-2023 Task 3: News Genre, Framing and Persuasion Techniques Detection using Multilingual Models
Maram Hasanain, Ahmed Oumar El-Shangiti, Rabindra Nath Nandi +2
Misinformation spreading in mainstream and social media has been misleading users in different ways. Manual detection and verification efforts by journalists and fact-checkers can…
Device-friendly Guava fruit and leaf disease detection using deep learning
Rabindra Nath Nandi, Aminul Haque Palash, Nazmul Siddique +1
This work presents a deep learning-based plant disease diagnostic system using images of fruits and leaves. Five state-of-the-art convolutional neural networks (CNN) have been empl…
TeamX@DravidianLangTech-ACL2022: A Comparative Analysis for Troll-Based Meme Classification
Rabindra Nath Nandi, Firoj Alam, Preslav Nakov
The spread of fake news, propaganda, misinformation, disinformation, and harmful content online raised concerns among social media platforms, government agencies, policymakers, and…
Detecting the Role of an Entity in Harmful Memes: Techniques and Their Limitations
Rabindra Nath Nandi, Firoj Alam, Preslav Nakov
Harmful or abusive online content has been increasing over time, raising concerns for social media platforms, government agencies, and policymakers. Such harmful or abusive content…