31 citations · 127 across the 16 of their papers we have counts for
17 papers
IFC-MCQ: Automatically Generating Multiple-Choice Benchmarks for Evaluating LLM Agents on IFC Data Retrieval
Rabindra Lamsal, Sisi Zlatanova, Xuesong Shen
Industry Foundation Classes (IFC), the standard for building information exchange in architecture, engineering, and construction (AEC), is increasingly queried through large langua…
CityLLM: A framework for natural-language querying of semantic 3D city models
Rabindra Lamsal, Sisi Zlatanova, Johnson Xuesong Shen
Semantic 3D city models provide rich geometric and semantic information, but remain challenging for non-experts and interdisciplinary researchers to access and query due to their c…
IfcLLM: Natural Language Querying of IFC Models through Complementary Relational and Graph Representations
Rabindra Lamsal, Sisi Zlatanova, Haowen Xu +3
The Industry Foundation Classes (IFC) standard is central to building data exchange across the lifecycle, from design and construction to facility management and Digital Twin integ…
Langformers: Unified NLP Pipelines for Language Models
Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera
Transformer-based language models have revolutionized the field of natural language processing (NLP). However, using these models often involves navigating multiple frameworks and…
"Actionable Help" in Crises: A Novel Dataset and Resource-Efficient Models for Identifying Request and Offer Social Media Posts
Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera +1
During crises, social media serves as a crucial coordination tool, but the vast influx of posts--from "actionable" requests and offers to generic content like emotional support, be…
CReMa: Crisis Response through Computational Identification and Matching of Cross-Lingual Requests and Offers Shared on Social Media
Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera +1
During times of crisis, social media platforms play a crucial role in facilitating communication and coordinating resources. In the midst of chaos and uncertainty, communities ofte…
Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts
Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera
Tasks such as semantic search and clustering on crisis-related social media texts enhance our comprehension of crisis discourse, aiding decision-making and targeted interventions.…
From Pro, Anti to Informative and Hesitant: An Infoveillance study of COVID-19 vaccines and vaccination discourse on Twitter
Pardeep Singh, Rabindra Lamsal, Monika Singh +2
COVID-19 pandemic has brought unprecedented challenges to the world, and vaccination has been a key strategy to combat the disease. Since Twitter is one of the most widely used pub…
CrisisTransformers: Pre-trained language models and sentence encoders for crisis-related social media texts
Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera
Social media platforms play an essential role in crisis communication, but analyzing crisis-related social media texts is challenging due to their informal nature. Transformer-base…
A Twitter narrative of the COVID-19 pandemic in Australia
Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera
Social media platforms contain abundant data that can provide comprehensive knowledge of historical and real-time events. During crisis events, the use of social media peaks, as pe…
GeoCovaxTweets: COVID-19 Vaccines and Vaccination-specific Global Geotagged Twitter Conversations
Pardeep Singh, Rabindra Lamsal, Monika +2
Social media platforms provide actionable information during crises and pandemic outbreaks. The COVID-19 pandemic has imposed a chronic public health crisis worldwide, with experts…
BillionCOV: An Enriched Billion-scale Collection of COVID-19 tweets for Efficient Hydration
Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera
The COVID-19 pandemic introduced new norms such as social distancing, face masks, quarantine, lockdowns, travel restrictions, work/study from home, and business closures, to name a…
Where did you tweet from? Inferring the origin locations of tweets based on contextual information
Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read
Public conversations on Twitter comprise many pertinent topics including disasters, protests, politics, propaganda, sports, climate change, epidemics/pandemic outbreaks, etc., that…
Socially Enhanced Situation Awareness from Microblogs using Artificial Intelligence: A Survey
Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read
The rise of social media platforms provides an unbounded, infinitely rich source of aggregate knowledge of the world around us, both historic and real-time, from a human perspectiv…
Twitter conversations predict the daily confirmed COVID-19 cases
Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read
As of writing this paper, COVID-19 (Coronavirus disease 2019) has spread to more than 220 countries and territories. Following the outbreak, the pandemic's seriousness has made peo…
Determining Optimal Number of k-Clusters based on Predefined Level-of-Similarity
Rabindra Lamsal, Shubham Katiyar
This paper proposes a centroid-based clustering algorithm which is capable of clustering data-points with n-features, without having to specify the number of clusters to be formed.…
Predicting Outcome of Indian Premier League (IPL) Matches Using Machine Learning
Rabindra Lamsal, Ayesha Choudhary
Cricket, especially the Twenty20 format, has maximum uncertainty, where a single over can completely change the momentum of the game. With millions of people following the Indian P…