16 citations · 43 across the 9 of their papers we have counts for
9 papers
An Ensemble Embedding Approach for Improving Semantic Caching Performance in LLM-based Systems
Shervin Ghaffari, Zohre Bahranifard, Mohammad Akbari
Semantic caching enhances the efficiency of large language model (LLM) systems by identifying semantically similar queries, storing responses once, and serving them for subsequent…
EnrichEvent: Enriching Social Data with Contextual Information for Emerging Event Extraction
Mohammadali Sefidi Esfahani, Mohammad Akbari
Social platforms have emerged as crucial platforms for distributing information and discussing social events, offering researchers an excellent opportunity to design and implement…
A Persian Benchmark for Joint Intent Detection and Slot Filling
Masoud Akbari, Amir Hossein Karimi, Tayyebeh Saeedi +5
Natural Language Understanding (NLU) is important in today's technology as it enables machines to comprehend and process human language, leading to improved human-computer interact…
Bagging Supervised Autoencoder Classifier for Credit Scoring
Mahsan Abdoli, Mohammad Akbari, Jamal Shahrabi
Credit scoring models, which are among the most potent risk management tools that banks and financial institutes rely on, have been a popular subject for research in the past few d…
MarlRank: Multi-agent Reinforced Learning to Rank
Shihao Zou, Zhonghua Li, Mohammad Akbari +2
When estimating the relevancy between a query and a document, ranking models largely neglect the mutual information among documents. A common wisdom is that if two documents are si…
Using Contextual Information to Improve Blood Glucose Prediction
Mohammad Akbari, Rumi Chunara
Blood glucose value prediction is an important task in diabetes management. While it is reported that glucose concentration is sensitive to social context such as mood, physical ac…
From the User to the Medium: Neural Profiling Across Web Communities
Mohammad Akbari, Kunal Relia, Anas Elghafari +1
Online communities provide a unique way for individuals to access information from those in similar circumstances, which can be critical for health conditions that require daily an…
Named Entity Disambiguation using Deep Learning on Graphs
Alberto Cetoli, Mohammad Akbari, Stefano Bragaglia +2
We tackle \ac{NED} by comparing entities in short sentences with \wikidata{} graphs. Creating a context vector from graphs through deep learning is a challenging problem that has n…
Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social Processes
Kunal Relia, Mohammad Akbari, Dustin Duncan +1
Social media offers a unique window into attitudes like racism and homophobia, exposure to which are important, hard to measure and understudied social determinants of health. Howe…