2 citations · 7 across the 12 of their papers we have counts for
6 papers · 1 filter
In-context Continual Learning Assisted by an External Continual Learner
Saleh Momeni, Sahisnu Mazumder, Zixuan Ke +1
Existing continual learning (CL) methods mainly rely on fine-tuning or adapting large language models (LLMs). They still suffer from catastrophic forgetting (CF). Little work has b…
Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models
Shachi H Kumar, Saurav Sahay, Sahisnu Mazumder +6
Large Language Models (LLMs) have excelled at language understanding and generating human-level text. However, even with supervised training and human alignment, these LLMs are sus…
Sample Efficient Multimodal Semantic Augmentation for Incremental Summarization
Sumanta Bhattacharyya, Ramesh Manuvinakurike, Sahisnu Mazumder +1
In this work, we develop a prompting approach for incremental summarization of task videos. We develop a sample-efficient few-shot approach for extracting semantic concepts as an i…
Position Matters! Empirical Study of Order Effect in Knowledge-grounded Dialogue
Hsuan Su, Shachi H Kumar, Sahisnu Mazumder +7
With the power of large pretrained language models, various research works have integrated knowledge into dialogue systems. The traditional techniques treat knowledge as part of th…
Lifelong and Continual Learning Dialogue Systems
Sahisnu Mazumder, Bing Liu
Dialogue systems, commonly known as chatbots, have gained escalating popularity in recent times due to their wide-spread applications in carrying out chit-chat conversations with u…
Semantic Novelty Detection and Characterization in Factual Text Involving Named Entities
Nianzu Ma, Sahisnu Mazumder, Alexander Politowicz +3
Much of the existing work on text novelty detection has been studied at the topic level, i.e., identifying whether the topic of a document or a sentence is novel or not. Little wor…