3 citations · 12 across the 10 of their papers we have counts for
5 papers · 1 filter
DALE: Generative Data Augmentation for Low-Resource Legal NLP
Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar +4
We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP. DALE addresses the challenges existing frameworks pose in generating effec…
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…
CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models
Sreyan Ghosh, Ashish Seth, Sonal Kumar +7
A fundamental characteristic of audio is its compositional nature. Audio-language models (ALMs) trained using a contrastive approach (e.g., CLAP) that learns a shared representatio…
ACLM: A Selective-Denoising based Generative Data Augmentation Approach for Low-Resource Complex NER
Sreyan Ghosh, Utkarsh Tyagi, Manan Suri +3
Complex Named Entity Recognition (NER) is the task of detecting linguistically complex named entities in low-context text. In this paper, we present ACLM Attention-map aware keywor…
MEMEX: Detecting Explanatory Evidence for Memes via Knowledge-Enriched Contextualization
Shivam Sharma, Ramaneswaran S, Udit Arora +2
Memes are a powerful tool for communication over social media. Their affinity for evolving across politics, history, and sociocultural phenomena makes them an ideal communication v…