3 citations · 5 across the 11 of their papers we have counts for
11 papers
ReDepress: A Cognitive Framework for Detecting Depression Relapse from Social Media
Aakash Kumar Agarwal, Saprativa Bhattacharjee, Mauli Rastogi +4
Almost 50% depression patients face the risk of going into relapse. The risk increases to 80% after the second episode of depression. Although, depression detection from social med…
Ta-G-T: Subjectivity Capture in Table to Text Generation via RDF Graphs
Ronak Upasham, Tathagata Dey, Pushpak Bhattacharyya
In Table-to-Text (T2T) generation, existing approaches predominantly focus on providing objective descriptions of tabular data. However, generating text that incorporates subjectiv…
StereoDetect: Detecting Stereotypes and Anti-stereotypes the Correct Way Using Social Psychological Underpinnings
Kaustubh Shivshankar Shejole, Pushpak Bhattacharyya
Stereotypes are known to have very harmful effects, making their detection critically important. However, current research predominantly focuses on detecting and evaluating stereot…
Main Predicate and Their Arguments as Explanation Signals For Intent Classification
Sameer Pimparkhede, Pushpak Bhattacharyya
Intent classification is crucial for conversational agents (chatbots), and deep learning models perform well in this area. However, little research has been done on the explainabil…
"My life is miserable, have to sign 500 autographs everyday": Exposing Humblebragging, the Brags in Disguise
Sharath Naganna, Saprativa Bhattacharjee, Biplab Banerjee +1
Humblebragging is a phenomenon in which individuals present self-promotional statements under the guise of modesty or complaints. For example, a statement like, "Ugh, I can't belie…
Can MLLMs generate human-like feedback in grading multimodal short answers?
Pritam Sil, Pushpak Bhattacharyya, Pawan Goyal +1
In education, the traditional Automatic Short Answer Grading (ASAG) with feedback problem has focused primarily on evaluating text-only responses. However, real-world assessments o…
DocCGen: Document-based Controlled Code Generation
Sameer Pimparkhede, Mehant Kammakomati, Srikanth Tamilselvam +3
Recent developments show that Large Language Models (LLMs) produce state-of-the-art performance on natural language (NL) to code generation for resource-rich general-purpose langua…
"I understand why I got this grade": Automatic Short Answer Grading with Feedback
Dishank Aggarwal, Pritam Sil, Bhaskaran Raman +1
In recent years, there has been a growing interest in using Artificial Intelligence (AI) to automate student assessment in education. Among different types of assessments, summativ…
ConCodeEval: Evaluating Large Language Models for Code Constraints in Domain-Specific Languages
Mehant Kammakomati, Sameer Pimparkhede, Srikanth Tamilselvam +2
Recent work shows Large Language Models (LLMs) struggle to understand natural language constraints for various text generation tasks in zero- and few-shot settings. While, in the c…
We Care: Multimodal Depression Detection and Knowledge Infused Mental Health Therapeutic Response Generation
Palash Moon, Pushpak Bhattacharyya
The detection of depression through non-verbal cues has gained significant attention. Previous research predominantly centred on identifying depression within the confines of contr…
Facts-and-Feelings: Capturing both Objectivity and Subjectivity in Table-to-Text Generation
Tathagata Dey, Pushpak Bhattacharyya
Table-to-text generation, a long-standing challenge in natural language generation, has remained unexplored through the lens of subjectivity. Subjectivity here encompasses the comp…