28 citations · 66 across the 18 of their papers we have counts for
20 papers
AgriLens: Semantic Retrieval in Agricultural Texts Using Topic Modeling and Language Models
Heba Shakeel, Tanvir Ahmad, Tanya Liyaqat +1
As the volume of unstructured text continues to grow across domains, there is an urgent need for scalable methods that enable interpretable organization, summarization, and retriev…
Holistix: A Dataset for Holistic Wellness Dimensions Analysis in Mental Health Narratives
Heba Shakeel, Tanvir Ahmad, Chandni Saxena
We introduce a dataset for classifying wellness dimensions in social media user posts, covering six key aspects: physical, emotional, social, intellectual, spiritual, and vocationa…
Stacked ensemble\-based mutagenicity prediction model using multiple modalities with graph attention network
Tanya Liyaqat, Tanvir Ahmad, Mohammad Kashif +1
Mutagenicity is a concern due to its association with genetic mutations which can result in a variety of negative consequences, including the development of cancer. Earlier identif…
Advancements in Molecular Property Prediction: A Survey of Single and Multimodal Approaches
Tanya Liyaqat, Tanvir Ahmad, Chandni Saxena
Molecular Property Prediction (MPP) plays a pivotal role across diverse domains, spanning drug discovery, material science, and environmental chemistry. Fueled by the exponential g…
Exploring learning environments for label\-efficient cancer diagnosis
Samta Rani, Tanvir Ahmad, Sarfaraz Masood +1
Despite significant research efforts and advancements, cancer remains a leading cause of mortality. Early cancer prediction has become a crucial focus in cancer research to streaml…
JMI at SemEval 2024 Task 3: Two-step approach for multimodal ECAC using in-context learning with GPT and instruction-tuned Llama models
Arefa, Mohammed Abbas Ansari, Chandni Saxena +1
This paper presents our system development for SemEval-2024 Task 3: "The Competition of Multimodal Emotion Cause Analysis in Conversations". Effectively capturing emotions in human…
InterPrompt: Interpretable Prompting for Interrelated Interpersonal Risk Factors in Reddit Posts
MSVPJ Sathvik, Surjodeep Sarkar, Chandni Saxena +2
Mental health professionals and clinicians have observed the upsurge of mental disorders due to Interpersonal Risk Factors (IRFs). To simulate the human-in-the-loop triaging scenar…
LonXplain: Lonesomeness as a Consequence of Mental Disturbance in Reddit Posts
Muskan Garg, Chandni Saxena, Debabrata Samanta +1
Social media is a potential source of information that infers latent mental states through Natural Language Processing (NLP). While narrating real-life experiences, social media us…
Causal Categorization of Mental Health Posts using Transformers
Simranjeet Kaur, Ritika Bhardwaj, Aastha Jain +2
With recent developments in digitization of clinical psychology, NLP research community has revolutionized the field of mental health detection on social media. Existing research i…
NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media
Muskan Garg, Chandni Saxena, Usman Naseem +1
Interactions among humans on social media often convey intentions behind their actions, yielding a psychological language resource for Mental Health Analysis (MHA) of online users.…
Explainable Causal Analysis of Mental Health on Social Media Data
Chandni Saxena, Muskan Garg, Gunjan Ansari
With recent developments in Social Computing, Natural Language Processing and Clinical Psychology, the social NLP research community addresses the challenge of automation in mental…
A Methodology for the Prediction of Drug Target Interaction using CDK Descriptors
Tanya Liyaqat, Tanvir Ahmad, Chandni Saxena
Detecting probable Drug Target Interaction (DTI) is a critical task in drug discovery. Conventional DTI studies are expensive, labor-intensive, and take a lot of time, hence there…
CAMS: An Annotated Corpus for Causal Analysis of Mental Health Issues in Social Media Posts
Muskan Garg, Chandni Saxena, Veena Krishnan +4
Research community has witnessed substantial growth in the detection of mental health issues and their associated reasons from analysis of social media. We introduce a new dataset…
Cross-lingual Word Embeddings in Hyperbolic Space
Chandni Saxena, Mudit Chaudhary, Helen Meng
Cross-lingual word embeddings can be applied to several natural language processing applications across multiple languages. Unlike prior works that use word embeddings based on the…
Data Augmentation for Mental Health Classification on Social Media
Gunjan Ansari, Muskan Garg, Chandni Saxena
The mental disorder of online users is determined using social media posts. The major challenge in this domain is to avail the ethical clearance for using the user generated text o…
Countering Online Hate Speech: An NLP Perspective
Mudit Chaudhary, Chandni Saxena, Helen Meng
Online hate speech has caught everyone's attention from the news related to the COVID-19 pandemic, US elections, and worldwide protests. Online toxicity - an umbrella term for onli…
Tie Strength in Online Social Networks and its Applications: A Brief Study
Chandni Saxena, Tanvir Ahmad
In online social network (OSN), understanding the factors bound to the role and strength of interaction(tie) are essential to model a wide variety of network-based applications. Th…
Aspect Term Extraction using Graph-based Semi-Supervised Learning
Gunjan Ansari, Chandni Saxena, Tanvir Ahmad +1
Aspect based Sentiment Analysis is a major subarea of sentiment analysis. Many supervised and unsupervised approaches have been proposed in the past for detecting and analyzing the…
Group based Centrality for Immunization of Complex Networks
Chandni Saxena, M. N. Doja, Tanvir Ahmad
Network immunization is an extensively recognized issue in several domains like virtual network security, public health and social media, to deal with the problem of node inoculati…
Stability of Local Information based Centrality Measurements under Degree Preserving Randomizations
Chandni Saxena, M. N. Doja, Tanvir Ahmad
Node centrality is one of the integral measures in network analysis with wide range of applications from socio-economic to personalized recommendation. We argue that an effective c…