143 citations · 182 across the 15 of their papers we have counts for
15 papers
Revisiting Word Embeddings in the LLM Era
Yash Mahajan, Matthew Freestone, Sathyanarayanan Aakur +1
Large Language Models (LLMs) have recently shown remarkable advancement in various NLP tasks. As such, a popular trend has emerged lately where NLP researchers extract word/sentenc…
LLMs as Meta-Reviewers' Assistants: A Case Study
Eftekhar Hossain, Sanjeev Kumar Sinha, Naman Bansal +11
One of the most important yet onerous tasks in the academic peer-reviewing process is composing meta-reviews, which involves assimilating diverse opinions from multiple expert peer…
Revisiting Word Embeddings in the LLM Era
Yash Mahajan, Matthew Freestone, Naman Bansal +2
Large Language Models (LLMs) have recently shown remarkable advancement in various NLP tasks. As such, a popular trend has emerged lately where NLP researchers extract word/sentenc…
FaNS: a Facet-based Narrative Similarity Metric
Mousumi Akter, Shubhra Kanti Karmaker Santu
Similar Narrative Retrieval is a crucial task since narratives are essential for explaining and understanding events, and multiple related narratives often help to create a holisti…
Redundancy Aware Multi-Reference Based Gainwise Evaluation of Extractive Summarization
Mousumi Akter, Santu Karmaker
The ROUGE metric is commonly used to evaluate extractive summarization task, but it has been criticized for its lack of semantic awareness and its ignorance about the ranking quali…
ChatGPT as your Personal Data Scientist
Md Mahadi Hassan, Alex Knipper, Shubhra Kanti Karmaker Santu
The rise of big data has amplified the need for efficient, user-friendly automated machine learning (AutoML) tools. However, the intricacy of understanding domain-specific data and…
TELeR: A General Taxonomy of LLM Prompts for Benchmarking Complex Tasks
Shubhra Kanti Karmaker Santu, Dongji Feng
While LLMs have shown great success in understanding and generating text in traditional conversational settings, their potential for performing ill-defined complex tasks is largely…
Zero-Shot Multi-Label Topic Inference with Sentence Encoders
Souvika Sarkar, Dongji Feng, Shubhra Kanti Karmaker Santu
Sentence encoders have indeed been shown to achieve superior performances for many downstream text-mining tasks and, thus, claimed to be fairly general. Inspired by this, we perfor…
Processing Natural Language on Embedded Devices: How Well Do Transformer Models Perform?
Souvika Sarkar, Mohammad Fakhruddin Babar, Md Mahadi Hassan +2
This paper presents a performance study of transformer language models under different hardware configurations and accuracy requirements and derives empirical observations about th…
Joint Upper & Lower Bound Normalization for IR Evaluation
Shubhra Kanti Karmaker Santu, Dongji Feng
In this paper, we present a novel perspective towards IR evaluation by proposing a new family of evaluation metrics where the existing popular metrics (e.g., nDCG, MAP) are customi…
Multi-Narrative Semantic Overlap Task: Evaluation and Benchmark
Naman Bansal, Mousumi Akter, Shubhra Kanti Karmaker Santu
In this paper, we introduce an important yet relatively unexplored NLP task called Multi-Narrative Semantic Overlap (MNSO), which entails generating a Semantic Overlap of multiple…
Towards Automated Sexual Violence Report Tracking
Naeemul Hassan, Amrit Poudel, Jason Hale +4
Tracking sexual violence is a challenging task. In this paper, we present a supervised learning-based automated sexual violence report tracking model that is more scalable, and rel…
MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data
Lei Xu, Shubhra Kanti Karmaker Santu, Kalyan Veeramachaneni
Most automation in machine learning focuses on model selection and hyper parameter tuning, and many overlook the challenge of automatically defining predictive tasks. We still heav…
On Application of Learning to Rank for E-Commerce Search
Shubhra Kanti Karmaker Santu, Parikshit Sondhi, ChengXiang Zhai
E-Commerce (E-Com) search is an emerging important new application of information retrieval. Learning to Rank (LETOR) is a general effective strategy for optimizing search engines,…
JIM: Joint Influence Modeling for Collective Search Behavior
Shubhra Kanti Karmaker Santu, Liangda Li, Yi Chang +1
Previous work has shown that popular trending events are important external factors which pose significant influence on user search behavior and also provided a way to computationa…