79 citations · 81 across the 9 of their papers we have counts for
12 papers
Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: A Benchmark Study
Prottay Kumar Adhikary, Aseem Srivastava, Shivani Kumar +7
Comprehensive summaries of sessions enable an effective continuity in mental health counseling, facilitating informed therapy planning. Yet, manual summarization presents a signifi…
SemEval 2024 -- Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)
Shivani Kumar, Md Shad Akhtar, Erik Cambria +1
We present SemEval-2024 Task 10, a shared task centred on identifying emotions and finding the rationale behind their flips within monolingual English and Hindi-English code-mixed…
Harmonizing Code-mixed Conversations: Personality-assisted Code-mixed Response Generation in Dialogues
Shivani Kumar, Tanmoy Chakraborty
Code-mixing, the blending of multiple languages within a single conversation, introduces a distinctive challenge, particularly in the context of response generation. Capturing the…
From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed Dialogues
Shivani Kumar, Ramaneswaran S, Md Shad Akhtar +1
Understanding emotions during conversation is a fundamental aspect of human communication, driving NLP research for Emotion Recognition in Conversation (ERC). While considerable re…
Dialogue Agents 101: A Beginner's Guide to Critical Ingredients for Designing Effective Conversational Systems
Shivani Kumar, Sumit Bhatia, Milan Aggarwal +1
Sharing ideas through communication with peers is the primary mode of human interaction. Consequently, extensive research has been conducted in the area of conversational AI, leadi…
Emotion Flip Reasoning in Multiparty Conversations
Shivani Kumar, Shubham Dudeja, Md Shad Akhtar +1
In a conversational dialogue, speakers may have different emotional states and their dynamics play an important role in understanding dialogue's emotional discourse. However, simpl…
Speaker Profiling in Multiparty Conversations
Shivani Kumar, Rishabh Gupta, Md Shad Akhtar +1
In conversational settings, individuals exhibit unique behaviors, rendering a one-size-fits-all approach insufficient for generating responses by dialogue agents. Although past stu…
Explaining (Sarcastic) Utterances to Enhance Affect Understanding in Multimodal Dialogues
Shivani Kumar, Ishani Mondal, Md Shad Akhtar +1
Conversations emerge as the primary media for exchanging ideas and conceptions. From the listener's perspective, identifying various affective qualities, such as sarcasm, humour, a…
When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party Dialogues
Shivani Kumar, Atharva Kulkarni, Md Shad Akhtar +1
Indirect speech such as sarcasm achieves a constellation of discourse goals in human communication. While the indirectness of figurative language warrants speakers to achieve certa…
Multi-modal Sarcasm Detection and Humor Classification in Code-mixed Conversations
Manjot Bedi, Shivani Kumar, Md Shad Akhtar +1
Sarcasm detection and humor classification are inherently subtle problems, primarily due to their dependence on the contextual and non-verbal information. Furthermore, existing stu…
Discovering Emotion and Reasoning its Flip in Multi-Party Conversations using Masked Memory Network and Transformer
Shivani Kumar, Anubhav Shrimal, Md Shad Akhtar +1
Efficient discovery of a speaker's emotional states in a multi-party conversation is significant to design human-like conversational agents. During a conversation, the cognitive st…
Spotting Collective Behaviour of Online Frauds in Customer Reviews
Sarthika Dhawan, Siva Charan Reddy Gangireddy, Shiv Kumar +1
Online reviews play a crucial role in deciding the quality before purchasing any product. Unfortunately, spammers often take advantage of online review forums by writing fraud revi…